Forthcoming and Online First Articles

International Journal of Industrial and Systems Engineering

International Journal of Industrial and Systems Engineering (IJISE)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

Forthcoming articles must be purchased for the purposes of research, teaching and private study only. These articles can be cited using the expression "in press". For example: Smith, J. (in press). Article Title. Journal Title.

Articles marked with this shopping trolley icon are available for purchase - click on the icon to send an email request to purchase.

Online First articles are published online here, before they appear in a journal issue. Online First articles are fully citeable, complete with a DOI. They can be cited, read, and downloaded. Online First articles are published as Open Access (OA) articles to make the latest research available as early as possible.

Open AccessArticles marked with this Open Access icon are Online First articles. They are freely available and openly accessible to all without any restriction except the ones stated in their respective CC licenses.

Register for our alerting service, which notifies you by email when new issues are published online.

We also offer which provide timely updates of tables of contents, newly published articles and calls for papers.

International Journal of Industrial and Systems Engineering (109 papers in press)

Regular Issues

  • Stability Analysis of Asynchronous Switched Positive Systems with Unstable Subsystems   Order a copy of this article
    by Jingjing Hu, Pingping Gu, Huiwen Liu, Dexiang Liu 
    Abstract: This paper investigates the stability problems of asynchronous switched positive systems based on mode-dependent average dwell time method in continuous-time context. While using mode-dependent average dwell time to study the stability of switched systems, each subsystem must be stable, otherwise a state feedback controller should be designed for the unstable subsystem. But in practical application, when the subsystem is activated one by one, it usually takes a period of time to identify which one of the state feedback controllers should be activated, which causes the asynchronisation. Next, in consideration of the difficulty of designing an appropriate state feedback controller for some unstable subsystems, this paper is aimed at obtaining the stability condition of asynchronous switched positive systems with both stable and unstable subsystems.
    Keywords: asynchronization; mode-dependent average dwell time; stabilization; switched positive systems; unstable subsystem.
    DOI: 10.1504/IJISE.2020.10016058
     
  • Modelling of Critical Success Factors for Blockchain Technology Adoption Readiness in the Context of Agri-Food Supply Chain   Order a copy of this article
    by Vipulesh Shardeo, Anchal Patil, Ashish Dwivedi, Jitendra Madaan 
    Abstract: The agri-food supply chain is continuously facing several challenges; the most severe are food quality and safety issues. These issues debilitate the performance of the supply chain and often harm the consumers health. Therefore, there is an urgent need to address food quality and safety assurance in the supply chain. Blockchain technology (BCT) holds the potential to resolve these issues by enhancing security and transparency. The present study explores the critical success factors (CSFs) of BCT adoption readiness in the AFSC. Initially, CSFs are identified through a literature survey and finalised by experts opinion. The finalised factors are prioritised using the fuzzy best-worst method, followed by sensitivity analysis. The results reflect that food quality control, provenance tracking and traceability, and partnership and trust as the top three success factors. The studys findings will assist policymakers, managers, and practitioners in strategising the decision-making process while BCT dissemination.
    Keywords: blockchain technology; agri-food supply chain; AFSC; fuzzy; best-worst method; BWM; trust.
    DOI: 10.1504/IJISE.2021.10037223
     
  • Simulation-based Optimization: Analysis of the Emergency Department Resources under COVID-19 Conditions   Order a copy of this article
    by Shahla Jahangiri, Milad Abolghasemian, Peiman Ghasemi, Adel Pourghader Chobar 
    Abstract: The emergency department (ED) is the most important section in every hospital. The ED behaviour is adequately complex, because the ED has several uncertain parameters such as the waiting time of patients or arrival time of patients. To deal with ED complexities, this paper presents a simulation-based optimisation-based meta-model (S-BO-BM-M) to minimise total waiting time of the arriving patients in an emergency department under COVID-19 conditions. A full-factorial design used meta-modelling approach to identify scenarios of systems to estimate an integer nonlinear programming model for the patient waiting time minimisation under COVID-19 conditions. Findings showed that the S-BO-BM-M obtains the new key resources configuration. Simulation-based optimisation meta-modelling approach in this paper is an invaluable contribution to the ED and medical managers for the redesign and evaluates of current situation ED system to reduce waiting time of patients and improve resource distribution in the ED under COVID-19 conditions to improve efficiency.
    Keywords: emergency department; simulation-based optimisation; S-BO; meta-model; COVID-19.
    DOI: 10.1504/IJISE.2021.10037641
     
  • Lot Streaming of Hybrid Flowshops with Variable Lot Sizes and Eligible Machines   Order a copy of this article
    by Enas Ahmed Zaky, Tamer F. Abdelmaguid, Tamer Adel Mohamed, Sayed Taha Mohamed 
    Abstract: Hybrid flowshops are a special type of manufacturing systems, in which a stage may contain identical or unrelated parallel machines. This paper deals with a more practical approach for lot streaming hybrid flowshop in which the sublot sizes of jobs can vary from one stage to the next according to machines `speed. Two models of mixed-integer nonlinear programming are developed to minimise the make-span of two different hybrid flowshop systems. The first model deals with unrelated parallel machines with eligibility, independent setup time, and variable sublot sizes. The second model is a special case of the hybrid flowshop as it consists of multi-stages comprising one machine at the stages preceding the final stage, while the final stage includes unrelated parallel machines. The first model was studied and the data gathered were analyzed using ANOVA test to evaluate the factors’ effect on system. The factors are number of jobs, maximum number of batches, setup time, and machine’s configuration. The analysis revealed that all the factors were effective. The second model was compared to benchmarking published paper and it gets better results.
    Keywords: hybrid flowshop; HFS; sublots; make-span; mixed-integer nonlinear programming; eligible machines.
    DOI: 10.1504/IJISE.2021.10038498
     
  • Effect of mesh phasing on dynamic response of rotate vector reducer   Order a copy of this article
    by Chuan Chen, Hanbing Zhang, Wujiu Pan 
    Abstract: The effectiveness of mesh phasing to suppress certain orders of harmonic responses of RV reducer is investigated with Fourier series method. The lumped-parameter method is used to develop a transverse-torsional dynamic model, which considers key factors such as mesh stiffnesses of involute and cycloidal gears, bearing stiffnesses and support stiffnesses. The Fourier series method is used to solve dynamic response excited by the mesh stiffness. According to characteristics of the central components, each order of harmonic responses belongs to one of three typical types: rotational, translational and planetary component response modes. The typical response mode is related to mesh phasing factor. The law of mesh phasing is revealed by exploring the relationship between suppression of certain harmonic and mesh phasing factor, which is due to inherent symmetrical structure. Finally, the influence of the stiffness and torque on dynamic response is studied. The research provides some referential value for the reduction of vibration and dynamic design of RV reducer.
    Keywords: RV reducer; dynamic response; mesh phasing; influence factor.
    DOI: 10.1504/IJISE.2021.10041580
     
  • A new hybrid method for optimizing multi-surface problems: DSM method (Power plants of IRAN)   Order a copy of this article
    by Elham Shadkam 
    Abstract: In this paper, a new hybrid method is proposed for optimising multi-response surfaces simultaneously which is a combination of data envelopment analysis and the response surface method. For this reason, the proposed method is called the DSM method. This method not only investigates optimising multi-response surfaces but also considers the efficiency maximisation of decision-making units (DMUs). As a result, the outcome of this method is an optimised set of inputs and outputs with high efficiency of DMUs. DMS considers each DMU as an experiment in the design of the experiment and multi-response surfaces are transformed into a single-response surface, and instead of different response surfaces, an efficiency surface is replaced. Due to the high importance of the electricity industry and energy production, power plants, which are responsible for a very important part of electricity generation, have to increase the efficiency of their activities in order to make better use of resources. In this regard, the proposed method is implemented to account for the efficiencies of the power plan of Iran, and determine the optimum factors for the construction of a new one.
    Keywords: data envelopment analysis; DEA; response surface method; RSM; efficiency; optimisation; power plant.
    DOI: 10.1504/IJISE.2021.10039272
     
  • A prospect secondary goal model for ranking DMUs in DEA-R   Order a copy of this article
    by Simin Tohidnia, Ghasem Tohidi 
    Abstract: This paper presents a prospect DEA-R model by combining the DEA-R model and prospect theory that can be used to evaluate DMUs in decision making under risk. In this study, the proposed model is used as a secondary goal model to determine a unique set of weights in the evaluation of DMUs by cross-efficiency method and thus the psychological behaviours of experts are incorporated in the evaluations. In fact, the present paper introduces an approach for ranking DMUs in DEA-R that can be useful in decision making under risk and especially for decision makers who are familiar with ratio analysis. An empirical application also will be presented to illustrate the applicability of the proposed model.
    Keywords: data envelopment analysis; DEA; DEA-R; secondary goal model; prospect theory; cross-efficiency.
    DOI: 10.1504/IJISE.2021.10039541
     
  • Data-Driven Prognostic Framework for Remaining Useful Life Prediction   Order a copy of this article
    by Asmaa Motrani, Rachid Noureddine 
    Abstract: Industrial prognostic, based on data resulting from a monitoring up stream, is considered as a crucial stage in making complex industrial systems more reliable. The purpose of the industrial prognostic is to predict the future state of the monitored system, and to give, more specifically, an estimation of its remaining useful lifetime (RUL). Among the used approaches, data-driven prognostic is the most promising when dealing with multitude heterogeneous data. The aim of this work is to present a data-driven prognostic framework implementation, where the RUL is determined through the association of statistical and artificial intelligence methods. This framework is based on the relevance vector machine (RVM) technique to build the predictive degradation model in the offline part, and on the similarity-based interpolation (SBI) technique for the prediction of the remaining useful life in the online part. The different steps of the proposed framework are described and implemented through a case study.
    Keywords: prognostic and health management; PHM; data-driven prognostic; sparse Bayesian learning; SBL; relevance vector machine; RVM; sparse Bayesian interpolation; SBI.
    DOI: 10.1504/IJISE.2021.10039700
     
  • Sustainability in Indian Manufacturing Sector: An empirical study on challenges   Order a copy of this article
    by Biswajit Mohapatra, Aneesh Kuruvilla, Deepak Singhal, Sushnata Tripathy 
    Abstract: Sustainability is an inexorably pertinent issue in all nations for building a cleaner, greener and prosperous industry around the globe. The concerned research is to build a model delineating the factors affecting sustainability and their degree of hindrance in the Indian industrial paradigm. The authors, through extensive literature review and expert opinions, have identified the factors affecting sustainability in India and then have attempted to structure a model by taking the seven major factors as constructs to the central construct called sustainability challenges. The degree of hindrance has been elucidated in the model and suitable inferences having a high future impact are drawn as a consequence of this rigorous effort. The multivariate statistical analysis method of structural equation modelling (SEM) has been utilised to capture the solution of the problem. The results of the research have a meaningful set of insights about the Indian chapter of sustainability in industries.
    Keywords: sustainability; challenges; structural equation modelling; SEM; manufacturing.
    DOI: 10.1504/IJISE.2021.10039817
     
  • An assembly process simulation method in immersive virtual reality environment   Order a copy of this article
    by Hui Zhang, Biao Yan, Liling Xia, Qiucheng Wang 
    Abstract: Virtual assembly process simulation is difficult to simulate the real assembly process completely due to the imperfection of haptic and force feedback. To solve this problem, a novel assembly process simulation method is proposed in this paper. Firstly, the rough and exact placement stages were divided according to the actual assembly process, and then a series of judgment rules were formulated to determine their assembly completeness according to the differences of geometric features and assembly methods of different parts. Meanwhile, to let users feel the constraint effect of contacts on part motion in the virtual environment without force feedback, a heuristic analysis method is introduced. The results show that the proposed method can better reflect the uncertainty of human’s actual assembly operation compared with the method based on geometric constraints, and it can better meet the needs of assembly analysis of mechanical products.
    Keywords: virtual assembly; virtual environment; force feedback; heuristic analysis method; constraint effect.
    DOI: 10.1504/IJISE.2021.10039818
     
  • Two-Wheeler Authorised Service Centre: A System Dynamics Study of “Limits to Growth” Archetype   Order a copy of this article
    by Virupaxi Bagodi, BISWAJIT MAHANTY 
    Abstract: Two-wheelers have become a common mode of transportation India, 1/3rd households own them and more than 225 million two-wheeler move on the roads. The corresponding growth in two-wheeler services is not observed. The purpose of the paper is to investigate the reasons for stagnation in the growth of services despite better service quality and experienced service personnel in a two-wheeler service centre. It is also intended to demonstrate the short comings in decision-making, using the limits to growth archetype, that nothing grows unabated and in a complex system, compensating feedback loops slow down the growth. The data from the service centre of a premier manufacturer was gathered for three months during 2019. A system dynamics model is developed iteratively for the problem the entrepreneur is facing. Policy experimentations are carried out. The results corroborate that just pushing the growth engine is inadequate for sustainable growth and compensatory feedback loops inhibit the growth of performance measures. Results also indicate that starting the business with higher service capacity and adding capacity at appropriate time is vital in a service firm.
    Keywords: limit to growth; service centre; two-wheelers; decision-making; India.
    DOI: 10.1504/IJISE.2021.10040216
     
  • Identification and generalizability of key causes of challenges in the implementation of IPD contract in construction projects with the perspective of Iran road construction projects   Order a copy of this article
    by Mohammadjavad Nasiri Jahroudi, Mehdi Nani, Ebrahim Safa, Ehsan Sadeh 
    Abstract: Integrated project delivery (IPD) system is one of the new achievements of the construction industry in the field of contracting and project implementation, especially infrastructure projects in the construction industry, which tries to improve the project output by integrating the project team and working together between different factors and elements involved in the project. Despite of many advantages and increasing applications of the IPD contract method revealed in developed countries, there are so much challenges in using that, due to lack of familiarity and sufficient information, in developing countries such as Iran. In this article, after extensive studies and investigations, the most important causes of challenges in the implementation of IPD contract and its generalisability with the nine principles of this type of contract and their correlation with Pearson statistical method were identified. Then, the challenges identified in IPD with methods Friedman were ranked and the most important items were extracted.
    Keywords: generalisability; correlation; causes of challenge; IPD principles; statistical tests.
    DOI: 10.1504/IJISE.2021.10040220
     
  • Optimizing Patient Revisit Intervals for Virtual and Office Appointments in Chronic Care   Order a copy of this article
    by Xiao Yu, ARMAGAN BAYRAM 
    Abstract: Virtual appointments are cost-effective alternatives to the traditional office appointments where patients receive the required care remotely. Virtual appointments are used to complement or substitute for office appointments due to the limitations on the availability of office appointments. They improve patients’ access to care and provide convenient care for the patients. However, it is challenging to integrate these appointments with traditional appointments and to decide the visit frequency of patients for different types of appointments since these appointments have different effectiveness. In this paper, we consider a clinic that provides both virtual and office appointments in a chronic care setting. We develop an open migration network to simulate the patients’ flow in the clinic system and build mathematical models to investigate the optimal follow-up rates (i.e., revisit intervals) for both virtual and office appointments. With the model developed, more systematic decisions can be made to determine follow-up rates.
    Keywords: virtual appointments; revisit intervals; chronic care; migration network model.
    DOI: 10.1504/IJISE.2021.10040234
     
  • Research on Cross platform information transmission method of industrial Internet of things based on XML Technology   Order a copy of this article
    by Changhong Zhu, Tianci Pan 
    Abstract: Aiming at problems of large error in data feature extraction and high congestion in the traditional information transmission methods, this paper proposes a cross-platform information transmission method of industrial internet of things based on XML technology. Based on the networked information features of extract, SUM function was used to complete the feature fusion. Then, the XML technology is used to obtain the optimal segmentation of tree, and the fitting training of tree data is carried out to realise the safe storage of information. Then, the information distribution probability is obtained according to the nature of XML file, so as to realise the cross-platform transmission of information. According to the simulation results, it can be seen that: the data feature extraction error of this method is at least 2.1%, the sample data transmission time is always lower than 6 s, and the transmission process congestion is low, which fully proves its effectiveness.
    Keywords: XML technology; industrial internet; SUM function; cross-platform transmission; distribution probability.
    DOI: 10.1504/IJISE.2021.10040357
     
  • A Decision Support System for Selecting Augmentative and Alternative Communication Devices   Order a copy of this article
    by Eduardo Pérez, Mahima S. Varghese, Amy L. Schwarz 
    Abstract: The goal of this research is to improve access to services for patients in need of augmentative and alternative communication (AAC). The specific aim of this paper is to develop a decision-making model that evaluates an exhaustive list of AAC devices and recommends the best alternative(s) for the patient. The model maximises a best-fit function that considers the patient’s disability profile and the capabilities of each device. Currently, there are multiple private and government companies that offer a large variety of devices targeting patients in need of AAC. However, the decision-making process of what device to try on the patient is largely based on the health professional’s experience and familiarity with specific companies. The proposed decision-model has the capability of improving patient experience of care by reducing the assessment time required to find the best device.
    Keywords: decision making; augmented and alternative communication; AAC; healthcare; medical devices.
    DOI: 10.1504/IJISE.2021.10040471
     
  • Safety Requirement Verification of Train-centric CBTC by Integrating STPA with Coloured Petri Net   Order a copy of this article
    by Qian Xu, Junting Lin 
    Abstract: Train-centric communication-based train control (TcCBTC) system is characterised by core functions centralised into on-board facilities with simplified trackside equipment. Coloured Petri net (CPN) is one of the classical model checking methods and system-theoretic process analysis (STPA) is a relatively new hazard identification method based on system thinking and control theory. STPA and CPN are mutually complementary because STPA provides the verification basis for CPN while CPN makes STPA’s results written by natural language verifiable. The functional requirements of TcCBTC are analysed first. Secondly, via the assistant analysis tool XSTAMPP 2.0, the hierarchical control structure is built and the refined unsafe control actions are obtained to generate the safety requirements. Thirdly, CPN models are constructed for verifying the basic properties and the safety. Results show that the potential unsafe control paths can be identified by the proposed method on the system level and the dependence severity on the manual analysis is considerably reduced.
    Keywords: train-centric CBTC; system-theoretic process analysis; STPA; coloured Petri net; CPN; safety requirements verification; unsafe control actions.
    DOI: 10.1504/IJISE.2021.10040903
     
  • Service Level and Profit Maximization in Order Acceptance and Scheduling Problem with Weighted Tardiness   Order a copy of this article
    by Mohammad Yavari, Amir Hosein Akbari 
    Abstract: Traditional order acceptance and scheduling (OAS) problem focused on profit optimisation and the number of accepted orders has been only regarded as a constraint in the OAS model in a few research studies. The current paper investigates a bi-objective OAS problem to maximise profit and service level. There are two categories of regular and special orders in a single-machine environment. We have proposed a mixed integer linear program using goal programming. Due to the NP-hard nature of the problem, we have developed a simulated annealing-based heuristic to solve the problem, and a lower bound to assess its performance. Both single objective and bi-objective versions of the problem have been studied. Computational experiments demonstrate the ability of the proposed heuristic. The advantages and disadvantages of the proposed bi-objective OAS problem are discussed. Also, the relation between service level and profit objectives is studied in both problems with and without special orders.
    Keywords: order acceptance and scheduling; OAS; service level; simulated annealing-based heuristic; mixed-integer linear programming; MILP; goal programming; bi-objective; lower bound.
    DOI: 10.1504/IJISE.2021.10041481
     
  • Insightful Implementation of Lean Tools to Cultivate Lean Culture in Small Scale Manufacturing Organization a case study   Order a copy of this article
    by Jaydeepsinh Ravalji, Shruti Raval, Gulamkhwaza Qureshi, Himadri Shukla 
    Abstract: Small and medium-scale organisations are the backbone of the Indian manufacturing sector. Awareness and proper use of the Lean approach can improve their productivity. This paper demonstrates insightful use of some of the Lean tools to a small subcontractor organisation; for improvement in its current process with less expenditure. The second objective was to develop an attitude among production people for waste-free practices through innovative ideas. To achieve these objectives, the current state VSM was prepared to identify wastes in the process. Kaizen, Pacemaker, PEEP, and two-Bin Kanban system were used to achieve the ideal process. By implementing these tools, the total cycle time for one rotor assembly is reduced by 37.12%, the total lead time is reduced by 7.1%, and inter-departmental material movement per day is reduced by 37.5%. This paper will motivate researchers and practitioners to develop specific but effective solutions with knowledge of Lean philosophy.
    Keywords: lean manufacturing; 5S; value stream mapping; VSM; Kaizen.
    DOI: 10.1504/IJISE.2021.10041486
     
  • Cost Optimality of an erratic Geo^{X}/G/1 Retrial Queue under J-vacation scheme using Nature Inspired Algorithms   Order a copy of this article
    by Radhika Agarwal, Shweta Upadhyaya, Divya Agarwal, Sumit Kumar 
    Abstract: In this article, we have explored a GeoX/G/1 model with Bernoulli feedback wherein the clients that enter and find the system to be busy, halt for a while prior to attempting again to enter the system. The server is erratic and can take utmost J-vacations regularly unless one client appears in the virtual track (orbit) again on returning from vacation. Also, the server is sent for repair on an urgent basis as soon as it breaks down. Using the probability generating function technique, the system size distribution of the server during busy, breakdown, vacation state and orbit size along with some performance measures have been derived. These derived quotients are then visualised and validated with the help of tables and graphs. Further, the cost analysis of the model is carried out and the optimal cost for the system is obtained. We have used direct search method, particle swarm optimisation (PSO), artificial bee colony (ABC) and cuckoo search (CS) techniques for the comparative study and presented the graphs for the convergence of these techniques.
    Keywords: discrete-time; starting failure; normal breakdown; J-vacation; Bernoulli feedback; cost optimisation; direct search; particle swarm optimisation; PSO.
    DOI: 10.1504/IJISE.2021.10041559
     
  • Manufacturing Management of Productivity in the Steel Industry Using System Dynamics Modelling and Statistical Evaluation   Order a copy of this article
    by Thomas Munyai, MAKINDE OLASUMBO, Michael Ayomoh, Alufeli A.E. Nesamvuni, Boitumelo B.I. Ramatsetse 
    Abstract: This paper has identified and analysed various drivers capable of influencing the level of productivity in steel manufacturing. The South African Steel Manufacturing Industries (SASMI) was used as a case study for this research. In order to achieve this, a comparative analysis of factors that could influence the productivity of SASMI was conducted using the exploratory factor analysis. Next was the creation of an integrated network of the systemic factors and lastly, the development of a system dynamics model for insight into the sensitivity of productivity dynamics per factor over a period of 30 months. Multiple regression analysis (MRA) was used to establish the relationship between productivity and its drivers. The results of the MRA, showed that competitiveness in terms of (production strategy, speed, cost, quality monitoring strategy and market share); facility layout and government support with weights of 0.319, 0.249 and 0.153, respectively, are critical to the productivity of SASMI.
    Keywords: productivity; system dynamics; steel manufacturing; manufacturing management; multiple regression analysis; MRA.
    DOI: 10.1504/IJISE.2021.10041636
     
  • Design of a mathematical model and a simulation-optimization approach for master surgical scheduling considering uncertainty in length of stay, demands and duration of surgery   Order a copy of this article
    by Mohammad Ebrahimi, Arezoo Atighehchian 
    Abstract: In this research a master surgical scheduling problem in conditions of uncertainty of demand, duration of surgery and length of patients’ stay is studied. First, an MIP model is developed in which the length of patients’ stay is considered probabilistic. Then, allowing for uncertainty in demand, a robust model is presented. Finally, a simulation-optimisation approach is developed in which three parameters are considered as uncertain. In this approach, the Grey Wolf and genetic algorithms are designed as the optimisation, and the Mont Carlo simulation is used in the simulation module. The results show that the maximum gap in the comparison of the simulation-optimisation algorithms and the lower-bound solution of the mathematical models in small-scale problems is only 9.36% while the algorithms are much faster. In larger-scale problems, the average improvement percentage of the proposed approach with the Grey Wolf optimisation module as compared to the genetic algorithm module is 2.93%.
    Keywords: master surgical scheduling; MSS; simulation-optimisation approach; mixed integer programming; uncertainty; robust optimisation.
    DOI: 10.1504/IJISE.2021.10041644
     
  • Toward Smart Manufacturing Systems incorporating Reconfiguration Issues   Order a copy of this article
    by Ibrahim H. Garbie, Abdelrahman I. Garbie 
    Abstract: Nowadays, Industry 4.0 will become urgent to be implemented in most of the developed countries, although it is still mainly conceptually. As there are three different aspects consisting of Industry 4.0 (I4.0) such as digital systems, biological systems, and physical systems, most of the research published works were focused on mainly the first one. The smart manufacturing system (SMS) is not an invention, although it is representing the heart of I4.0. The SMS is a rebirth of a new version and innovation of production systems taken into consideration reconfiguring the existing manufacturing systems through adding machines with sensors, actuators, and control architectures for achieving the ultimate goals of I4.0. There are many challenges when reconfiguring these systems as an essential requirement to implement I4.0, representing the degree of individual system complexity, reconfigurable machines, material handling systems, system layout; competitive manufacturing strategies; and leanness agility), and embedded systems (cyber-physical systems). In this paper, a new perspective of reconfiguring manufacturing systems will be figured out, and the reconfigurability level toward I4.0 will be presented.
    Keywords: Industry 4.0; smart manufacturing systems; SMSs; reconfiguration.
    DOI: 10.1504/IJISE.2021.10041796
     
  • An aircraft position updating based algorithm for single runway scheduling with normal and alternate aircrafts   Order a copy of this article
    by Hong-Da Dou, Feng Wang, He Pan, Yi-Fan Wang, Tsui-Ping Chung 
    Abstract: This paper investigates the problem of scheduling normal and alternate landing aircrafts at a single runway on Changchun Longjia International Airport. Usually, if the destination airport does not satisfy the landing conditions, then the aircraft has to use an alternate airport. Both normal and alternate landing aircrafts arrive at a fixed time window. Meanwhile, safety interval of adjacent landing aircrafts depends on their sizes. An integer programming model is proposed to minimise the landing completion time. Since the problem is NP-hard, an aircraft position updating based algorithm is proposed. To evaluate the performance of the proposed algorithm, a real case from Changchun Longjia International Airport and randomly generated problem instances are tested. The results show that the proposed algorithm has a better performance than the first-come first-served order and the landing constraints-based heuristic algorithms.
    Keywords: normal landing aircrafts; alternate landing aircrafts; single runway; fixed time window; safety interval; landing completion times.
    DOI: 10.1504/IJISE.2021.10041834
     
  • Modeling Customer Demand for Mobile Value-Added Services: Non-Stationary Time Series Models or Neural Networks Time Series Analysis?   Order a copy of this article
    by Mohammad Hossein Vaghefzadeh, Behrooz Karimi, Abbas Ahmadi 
    Abstract: The present research applies two different modeling approaches to evaluate the historical demand for a special mobile value-added service (VAS) that is offered and delivered to airline customers. The first method is deterministic and includes non-stationary time series models that cover both mean and variance fluctuation, as well as seasonality effect, in the dataset. The second method is a metaheuristic approach in the form of artificial neural network time series analysis (ANN-TSA). These methods are used to evaluate the power of each category and to choose the best model based on appropriate criteria. The results show that non-stationary time series models outperform ANN-TSA, as indicated by the smaller number of errors in the simulation of the demand dataset.
    Keywords: time series; analysis; non-stationary; artificial neural network; mobile value-added; seasonal effect; demand; forecasting.
    DOI: 10.1504/IJISE.2021.10041835
     
  • Investigating the challenges faced by Indian Automotive Industry for adopting technology organically   Order a copy of this article
    by Mudita Dixit, Gopakumaran Thampi 
    Abstract: The Indian automobile sector is the sixth-largest producer of automobiles globally in terms of worth and volume. India has a steady trade deficit of US$ 2 billion in auto components every year. This paper critically examined reasons for India lagging in technology adoption and transfer organically in different sectors (OEM, large, medium and small enterprises) of the automotive industry (AI). A survey was conducted on 272 enterprises located in the western region of India. The result shows that the high purchasing cost of technology, lack of awareness of IT tools, availability and retainability of skilled workforce are critical issues for small and medium enterprises compared to large enterprises and OEMs. This study determines the role of government policies, state policies, and proactive measures to contribute to AIs fortune. It is observed that AI shall replicate success stories of the Indian IT industry in terms of global reach and quality arbitrage offering to the export market.
    Keywords: advanced manufacturing technology; R&D; Indian automotive sector; latest technology adoption; original equipment manufacturer; OEM.
    DOI: 10.1504/IJISE.2021.10041846
     
  • Implementing Lean-Kaizen for Manufacturing Operations Improvement: A Case-Study in Plastics Industry   Order a copy of this article
    by Tareq Issa 
    Abstract: Lean manufacturing is concerned with the implementation of several tools and techniques that aim for the continuous elimination of waste in order to achieve competitive production systems. This research addresses the implementation of lean-kaizen concept and related techniques as part of a framework to achieve lean operation in a small-medium sized plastic bag manufacturing enterprise. The primary goal is to implement the lean-kaizen methodology to eliminate/reduce cycle time waste for the material mixing and roll formation processes in the manufacturing operation under study. The current state map was constructed, the processes identified for cycle time reductions were considered as well as the future state map was developed that served as a guide for lean-kaizen implementation. Root causes of waste were identified and two kaizen events were proposed as solutions. In the first kaizen event, the poka-yoke technique was used to automate the mixing process and eliminate variation and, for the second kaizen event, process standardisation was achieved in the roll formation process. As a result of implementing kaizen events, total cycle time was reduced and, consequently, productivity performance has increased to 94.7%.
    Keywords: lean-kaizen concept; kaizen event; cycle-time reduction; plastic bags industry; value stream map.
    DOI: 10.1504/IJISE.2021.10042029
     
  • A Tutorial on Optimization involving David Ricardo Theory on Comparative Advantage   Order a copy of this article
    by Tapan P. Bagchi, R.P. Mohanty, Surajit Sinha 
    Abstract: Ricardo (1821) showed how two countries producing two different goods using a single endowed factor of production (the 2-2-1 situation), but operating with unequal efficiency, can benefit if they freely barter certain parts of their production, even if one is more efficient in producing every good. When done, such trade produces more goods in total using the same amount of total resource, rather than each producing enough goods only for own consumption, as in autarky. Ricardo showed that global benefits (measured in units of total goods produced) can accrue if each country specialises
    Keywords: comparative advantage; factor of production; free trade; linear programming; international trade; optimisation; Ricardo’s principle of trade.
    DOI: 10.1504/IJISE.2021.10042185
     
  • Prediction of uncertainty risk factors in engineering management system based on improved decision tree   Order a copy of this article
    by Rong Tang, Guoxiong Zhang, Yunxia Li 
    Abstract: In order to overcome the problem of low efficiency of the current prediction method for uncertainty risk factors in engineering management system, this paper proposes a prediction method for uncertainty risk factors in engineering management system based on improved decision tree. In this method, the reason model (accident causal model of complex system) and software, hardware, environment and livewar (SHEL) model are used to analyse the uncertainty risk factors in engineering management system, and the prediction system of uncertainty risk factors is established. The fuzzy clustering analysis method is used to judge the expert weight of risk factors, and the improved decision tree algorithm combined with the judgment results is used to predict the uncertainty risk factors in engineering management system. The simulation results show that the proposed method can reduce the prediction error rate by 1.5% in the following time.
    Keywords: engineering management system; uncertainty; risk factors; improved decision tree; fuzzy clustering; prediction.
    DOI: 10.1504/IJISE.2021.10042297
     
  • A Machine Learning Algorithm for Scheduling a Burn-in Oven Problem   Order a copy of this article
    by Mathirajan M, Sujan Reddy, Vimala Rani M, Dhaval P 
    Abstract: This study applies artificial neural network (ANN) to achieve more accurate parameter estimations in calculating job-priority-data of jobs and the same is applied in a proposed dispatching rule-based greedy heuristic algorithm (DR-GHA) for efficiently scheduling a burn-in oven (BO) problem. The integration of ANN and DR-GHA is called as a hybrid neural network (HNN) algorithm. Accordingly, this study proposed eight variants of HNN algorithms by proposing eight variants of DR-GHA for scheduling a BO. The series of computational analyses (empirical and statistical) indicated that each of the variants of proposed HNN is significantly enhancing the performance of the respective proposed variants of DR-GHA for scheduling a BO. That is, more accurate parameter estimations in calculating job-priority-data for DR-GHA via back-propagation ANN leads to high-quality schedules w.r.t. total weighted tardiness. Further, proposed HNN variant: HNN-ODD is outperforming relatively with other HNN variants and provides very near optimal/estimated solution.
    Keywords: dispatching rules; semiconductor manufacturing; greedy heuristic algorithm; GHA; artificial neural network; ANN; optimal solution; estimated optimal solution.
    DOI: 10.1504/IJISE.2021.10042607
     
  • Use of heuristic methods for the optimization of truck loading in a steel company   Order a copy of this article
    by Andre Luis Korzenowsk, Felipe Kirsch Hoerbe, Taciana Mareth, Lucas Schmidt Goecks 
    Abstract: The correct layout of goods, objects or cargo, in the container’s available space is considered a complex task. The study was motivated by the need to implement a solution to optimise container use in a steel industry company in the South of Brazil. This article has contributed to synthesising research on the three-dimensional container loading problem, highlighting classifications, constraints, and algorithms used in its resolution. A framework is presented and may be used as a road map for practical implementation as used in this research. As a practical contribution, this article presents several instances of one actual case application. Results showed reducing of formatting loads processing time in comparison with the traditional company approach.
    Keywords: operational research; three-dimensional; container loading problem; CLP; steel industry.
    DOI: 10.1504/IJISE.2021.10042608
     
  • An Innovation Ontology for Idea Forecasting and Measurement   Order a copy of this article
    by Andrew N. Forde, Mark Fox 
    Abstract: Before managers are able to forecast the utility of an idea, there must be a common definition and basis for measuring the potential radicalness of an idea. In this paper, we introduce an ontology to represent an innovation and derive properties that can be used to define and measure an ideas potential to be classified as a radical or incremental innovation. Our proposed ontology captures the concepts of an incremental or radical innovation, and further concepts to support the grouping of innovations. We begin with an extensive review of the literature and identify the categories of innovation, from this group we apply competency questions that allow us to define properties that are the basis for valuing an ideas utility, and classifying an innovation.
    Keywords: innovation management; ontology; semantic web; open innovation; radicalness; incrementalness; innovation properties; innovation categories.
    DOI: 10.1504/IJISE.2021.10042662
     
  • Inventory management of manufacturers with yield uncertainty and lateral transshipment   Order a copy of this article
    by Arash Ashjaee, Mohammadali Pirayesh, Farzad Dehghanian 
    Abstract: This article deals with the issue of inventory management of one identical product in a manufacturers network. Manufacturers use lateral transshipments between each other in response to uncertainties in yield and demand to maximise the total profit. The demand of each manufacturer is considered random as a non-identical continuous probability distribution and their corresponding yield follows some possible scenarios. The objective of our model is to determine the optimal production amount and lateral transshipments in order to maximise the total profit considering the proceeds from sale of goods and salvage of remaining product and the cost of production, lateral transshipments, and shortages. The problem is modelled as a nonlinear constrained programming and the optimal solution is obtained by Karush-Kuhn-Tucker approach. Sensitivity analysis of uncertainty parameters based on a numerical example showed that the utility of using lateral transshipment policy increases with increasing the uncertainty in production yield.
    Keywords: inventory management; yield uncertainty; lateral transshipment.
    DOI: 10.1504/IJISE.2021.10042971
     
  • Risk Warning Method of Computerized Accounting Information Distortion Based on Deep Integration Model   Order a copy of this article
    by Wenyuan Chen 
    Abstract: In order to improve the early warning accuracy of accounting information distortion risk and reduce the resource occupancy rate in the early warning process, this paper designs a deep integrated model-based computerised accounting information distortion risk early warning method. The distortion risk identification model is constructed to avoid the interference of invalid information and reduce the resource occupancy rate. Then the quantitative index is used to improve its effectiveness and improve the accuracy of the subsequent warning. Then the deep integration model is used to judge whether there is distortion node in the current computerised accounting information, so as to complete the high precision early warning of distortion risk. Simulation results show that the warning accuracy of this method is always above 0.9, and the resource occupancy rate of the warning process is less than 40%, which proves that this method achieves the design expectation.
    Keywords: computerised accounting information; index quantification; distortion risk identification; risk warning; deep integration model.
    DOI: 10.1504/IJISE.2021.10043036
     
  • Integrated Scheduling and Vehicle Routing at Cross-dock Distribution Centre: A Simulated Annealing Approach   Order a copy of this article
    by Shikhar Saxena, Rajesh Piplani 
    Abstract: Cross-docking is a popular strategy for distributing products with short shelf-life that must be delivered within their pre-specified time windows to customers. Cross-docks receive shipments from suppliers which are stored in a temporary storage area before being consolidated and transferred to outbound vehicles for delivery to customers. This research tackles the joint problems of vehicle routing and scheduling at the cross-dock, along with product consolidation, by means of a mixed-integer programming model with the objective of minimising the total cost of operations. Our approach does not pre-cluster customers into zones and allows vehicles to deliver in less than truckload. To solve real-life sized problems, we develop simulated annealing algorithms which can solve the instances in 2 to 3 hours, achieving close to optimal solutions, making them suitable for decision support at cross-dock distribution centres, which process dozens of vehicles and deliver to hundreds of customers daily.
    Keywords: cross-docking; routing and scheduling; delivery window; meta-heuristic; product consolidation; simulated annealing.
    DOI: 10.1504/IJISE.2021.10043156
     
  • Copper Futures Hedging based on Markov switching approach   Order a copy of this article
    by Jiaxuan Chen 
    Abstract: This paper selects the daily closing spot and futures prices of copper in China’s market from May 5, 1995 to February 28, 2020, and then proposes a two-regime bivariate Markov regime-switching model, DCC-GARCH, CCC-GARCH and the OLS model to estimate their time-varying minimum variance hedging ratio and hedging performance for comparison both in- and out-of-sample. The empirical results show that, whether in- or out-of-sample, the two-regime bivariate Markov regime-switching model can provide more detail depiction of dynamic correlation between spot and futures, and outperforms the others for hedging performance. Next is the DCC-GARCH model. CCC-GARCH model and the OLS model have similar performance. Besides, the rolling-window method can make the changes more obvious in the correlation of financial assets, which helps to estimate the time-varying optimal hedging ratio in the fast-changing market.
    Keywords: dynamic futures hedging; Markov regime-switching model; DCC-GARCH.
    DOI: 10.1504/IJISE.2021.10043159
     
  • New mechanism of credit risk control in order agriculture   Order a copy of this article
    by Dongwei Shi 
    Abstract: The bilateral default rate of farmers and companies is usually high in contract farming. Inspired by the rule of
    Keywords: contract farming; bilateral default risk; mark-to-market.
    DOI: 10.1504/IJISE.2021.10043399
     
  • IoT enabled smart window for controlling brightness: - A perspective of heat transfer rate   Order a copy of this article
    by Awais Kazi, Nikhil Shinde, Sumeet Mujumdar, Tejas Kulkarni, Prathamesh Potdar 
    Abstract: In a competitive environment, organisations are focusing on the energy-efficient smart system to reduce the expenses related to energy consumption and a comprehensive literature survey shows that windows are significant sources of heat and light in an enclosed space, which increases the load on air conditioner systems to maintain the comfortable conditions inside the room. There is a need to develop IoT enabled smart window for controlling heat and light in this context. In this study, suitable devices and sensors are identified based on a systematic literature survey to develop the IoT-enabled smart window. The experimental setup is also developed to evaluate the heat flow and luminosity inside the closed room. It has been observed that the maximum temperature recorded in the room in the range of 29
    Keywords: polymer dispersed liquid crystal; PDLC; internet of things; IoT; smart window; heating; ventilation; and air conditioning; HVAC.
    DOI: 10.1504/IJISE.2021.10043481
     
  • A STUDY ON WORK-RELATED MUSCULOSKELETAL COMPLAINT AND ASSOCIATED RISK FACTORS AMONG STEEL INDUSTRIAL WORKERS   Order a copy of this article
    by Samson Akindele, Olusegun Akanbi, Feyisayo Akinwande, Joshua Ade-Omowaye 
    Abstract: As a result of scarce information regarding the impact of work-related musculoskeletal complaints (WMSCs) in the Nigerian steel industry, this research investigates the frequency of complaints in the various body regions. Subsequently, the relationship between WMSC and the essential worker’s characteristics (age, work tenure and weight) and working posture were addressed. The frequency of complaints of the working population was collected and accessed using the Nordic musculoskeletal questionnaire (NMQ). The active stance of the workers was analysed using the rapid upper limb assessment (RULA). The results from NMQ showed a significant relationship between complaints of the upper and lower back regions among the workgroups. Significantly, there exists a strong correlation among workers characteristics with WMSC. Older workers complained more about specific body regions than the relatively younger workers. The RULA showed that the maintenance department workers had the most significant postural risk, followed by the melting section.
    Keywords: posture; casting; productivity; rapid upper limb assessment; RULA; musculoskeletal complaints; discomfort; safety; steel industry.
    DOI: 10.1504/IJISE.2021.10043568
     
  • A Case Study on the Design and Implementation of a New Product for Infants Learning to Walk   Order a copy of this article
    by Hu Shan, Jia Qi, Wang Yuqing, Fu Kaijie, Zhang Liyan, Guo Min, Guo Weiqi 
    Abstract: In order to solve the problem of the poor user experience and low satisfaction of infants and parents caused by insufficient research into existing products for toddlers. Based on the design and development process, this research takes pre-existing dual user research as its core and uses literature research, a focus group and other methods to determine dual user needs, as well as the Kano model to determine the demand attribute classification of the mixed methods of qualitative and quantitative research. Then, in this research, we design a system to help infants learn to walk that conforms to the characteristics of an infant’s physical and psychological development and meets the needs of parent users. The system can guide an infant to actively learn to walk through a multisensory interactive approach; meanwhile, parents’ fatigue and anxiety regarding children walking will be relieved during this period. In the final stage of this research, we design a product prototype to test the usability of the system. The research method can also be applied to other types of product design, and the design cue map obtained through user research has reference significance for other infant products.
    Keywords: infant; toddler; product design; user research.
    DOI: 10.1504/IJISE.2021.10043976
     
  • Asymptotic analysis of a Bernoulli Vacation non markovian Queuing system in Air traffic control system   Order a copy of this article
    by Radha S, S. Maragathasundari, P. Manikandan 
    Abstract: We examine a single server queue arriving with Poisson batches of varying sizes. When the system starts the service, it provides service to all the arriving customers on a first come first served basis. Before the first service starts after each system downtime, the server provides general services to the client for a specified time of random duration, known to be a set-up time stage. If the server is affected by random crashes, a delay time occurs before the commencement of repair process. If there are no clients in the queue after the service is complete, the server takes a Bernoulli vacation. Two new parameters, reneging and restricted admissibility happen during the process of vacation and repair process respectively. For the defined queuing issue, we find the length of the duration of the steady state of different states of the system according to the probability generating function. Other queue performance metrics are also exported. In addition, the disposal is legalised through a digital scheme and graphic representation. This model means that supervisors are aware of the structural difficulties of the client-server framework and the basic rules of investigation.
    Keywords: setup time; service interruption; repair process; restricted admissibility; Bernoulli schedule; reneging; supplementary variable technique.
    DOI: 10.1504/IJISE.2021.10043978
     
  • An integrated Fuzzy QFD approach to leagile supply chain assessment during COVID-19 crisis   Order a copy of this article
    by Fadoua Tamtam, Amina Tourabi 
    Abstract: The COVID-19 crisis has severely disrupted the Moroccan automotive production. This pandemic has weakened automotive supply chain; it faced a fall in demand and reduction in sales. Consequently, the automotive industry developed their production capabilities through constant innovation in resource reduction (leanness) while responding rapidly to demand changes (agility). A combination of lean-agile supply chain leads to obtain competitiveness in a time and cost effective manner. Successful implementation of leagile supply chain requires evaluation of criteria and attributes. To this end, the purpose of this paper is to propose a leagility evaluation framework using fuzzy quality function deployment approach. As a result, order guidance has been taken as the most important capability of automotive supply chain. E-fulfilment logistic has been considered as the most important enabler to gain supply chain leagility.
    Keywords: supply chain leagility; automotive industry; fuzzy quality function deployment; FQFD; leagile drivers; leagile capabilities; leagile enablers.
    DOI: 10.1504/IJISE.2021.10044277
     
  • New approaches for the Prize-Collecting Covering Tour problem   Order a copy of this article
    by FRANCISCO CLIMACO, Luidi Simonetti, Isabel Rosseti, Pedro Henrique González 
    Abstract: In this paper, we consider the prise-collecting covering tour problem (PCCTP), which intends to find a minimum cost tour for travelling teams that grant assistance to people located far from urban centres. We develop a branch-and-cut algorithm, some valid inequalities, and a new set of reduction rules as exact approaches. We also present a hybrid heuristic that combines a state-of-the-art heuristic for the PCCTP with integer programming techniques. Computational experiments showed that the exact approaches found several new optimal solutions while reducing CPU time, and the hybrid heuristic was able to match or improve the solution quality for many instances, along with a significant reduction of running time.
    Keywords: prise-collecting covering tour problem; PCCTP; greedy randomised adaptive search procedure; GRASP; random variable neighbourhood descent; RVND; hybrid heuristic; reduction rules.
    DOI: 10.1504/IJISE.2021.10044534
     
  • An Artificial Immune System Algorithm for Solving Stochastic Multi-Manned Assembly Line Balancing Problem   Order a copy of this article
    by Mohamamd Zakaria, Hegazy Zaher, Naglaa Ragaa 
    Abstract: In recent years, there has been an increasing interest in the multi-manned assembly line balancing problem (MALBP). It introduces the concept of assigning more operators at the same station to minimise the line length and to increase the production rate. Most of the previous works did not discuss such problems under uncertainty. Therefore, this paper presents a chance-constrained programming model that considers the processing times of the tasks as normally distributed random variables with known means and variances. The proposed algorithm for solving the problem is an artificial immune system algorithm. To get optimised results from the proposed algorithm, the parameters are tuned using a design of experiments. The computational results show the implementation of the proposed algorithm on 70 problems taken from well-known benchmarks in case that chance probability is equal to 0.95, 0.95, and 0.975.
    Keywords: MALBP; chance-constrained programming; artificial immune system; AIS; Taguchi orthogonal arrays; analysis of variance; ANOVA; Tukey’s HSD test.
    DOI: 10.1504/IJISE.2021.10044535
     
  • An evolutionary game model for low-carbon technology adoption by rival manufacturers   Order a copy of this article
    by Yuxiang Yang, Ying Xie 
    Abstract: Manufacturers’ decisions on adopting low carbon technology are influenced by many factors, including the consumers’ awareness of low carbon technology and governmental carbon tax scheme. In this research, we considered competition between two rival manufacturers and constructed a demand function that considers carbon emission and price as parameters rather than constraints. We developed an evolutionary game model in bounded rationality space and analysed the game between two manufacturers under four game scenarios. The impacts of consumers’ awareness of low-carbon technologies and governmental carbon tax scheme were clearly demonstrated in the manufacturers’ behaviour strategies towards the adoption of low carbon technology. The research findings offered insights into the level of consumers’ low carbon awareness that stimulates both manufactures to adopt low carbon technology, and the threshold of low carbon awareness that incentivises only one manufacturer to adopt low carbon technology. Meanwhile, authority should enact carbon tax within appropriate range in order to reduce carbon emissions.
    Keywords: low carbon technology; evolutionary game; low carbon awareness; carbon tax.
    DOI: 10.1504/IJISE.2021.10044582
     
  • Integrated optimisation of the unequal-area facility layout and the flowshop group scheduling problems for a case of the garment industry   Order a copy of this article
    by Sebastian Cáceres-Gelvez, Martín Darío Arango-Serna, Julian Zapata 
    Abstract: The unequal-area facility layout (UAFLP) and the flowshop group scheduling (FSGSP) problems are two important problems in both research literature and industrial applications. The former considers the location of departments with different area requirements within a floor plan. The latter seeks for a sequence of product families and jobs to be processed on groups of machines, called manufacturing cells. In this paper, an integrated approach for optimising both the UAFLP and the FSGSP is presented in the case of a sportswear manufacturing company. A genetic algorithm (GA) is proposed for minimising the sum of the total material handling and the tardiness costs. The results showed that the optimisation process obtained a reduction of 6.69% of the total costs for the proposed alternative, in comparison with the current situation of the case study.
    Keywords: unequal-area facility layout; flowshop group scheduling; genetic algorithm; garment industry; integrated optimisation; case study.
    DOI: 10.1504/IJISE.2021.10044730
     
  • A Bibliographic Study of Sustainability Research: Exploring Multidimensionality   Order a copy of this article
    by Soumyanath Chatterjee, R.P. Mohanty 
    Abstract: Sustainability has gained prominence as a discipline for academics and professional practitioners. This article presents a bibliographic account and related analysis of research in sustainability between 1990 and 2019. A critical study of different aspects of sustainability requires a multi/interdisciplinary systems approach. Such a study may encompass ecological, economical, and sociological perspectives. For this reason, the bibliometric analysis has covered a wide range of professional disciplines. 183,779 bibliographic entries from SCOPUS were analysed with latent Dirichlet allocation (LDA) to discover different aspects of publications in sustainability. The study showed that all publications can be classified according to 25 topics, showing how sustainability research has evolved and the consequent gaps that need to be filled for the advancement of the research and community of practice. The LDA analysis resulted in creating a topic model that facilitates the automated categorisation of publications regarding sustainability.
    Keywords: sustainability; systematic literature survey; text analytics; latent Dirichlet allocation; LDA; topic model; bibliographic analysis.
    DOI: 10.1504/IJISE.2021.10044764
     
  • Minimizing Makespan of a Batch Processing Machine with Unequal Job Ready Times Using Simulated Annealing   Order a copy of this article
    by Leena Ghrayeb, Purushothaman Damodaran 
    Abstract: Batch processing machines can process multiple jobs simultaneously. Given a set of jobs with their processing times, ready times, and sizes, the objective is to minimise the makespan. Two interdependent decisions are required: group jobs to form batches and schedule batches on the machine. The processing and ready times of the batch depends on the composition of the batch. Batch ready time is equal to the largest ready time of all the jobs in a batch. Similarly, batch processing time is equal to the largest processing time of all the jobs in a batch. As the problem under study is NP-hard, a simulated annealing (SA) approach is proposed. The proposed approach is evaluated by comparing its solution quality and run time with a commercial solver used to solve a mathematical formulation. An experimental study shows that the SA approach is fast in finding good solutions as the problem size increases.
    Keywords: scheduling; batch processing machine; BPM; makespan; simulated annealing.
    DOI: 10.1504/IJISE.2021.10045063
     
  • Performance Improvement: A Lean Manufacturing Case of Metal Tools Factory   Order a copy of this article
    by Angassu Girma Mullisa, Walid Abdul-Kader 
    Abstract: Lean manufacturing in small and medium enterprises (SMEs) and ultimately success from implementation is marginal as compared to large enterprises. Poor Lean implementation technique and understanding is cited as one of the prominent reasons for the low success. Towards bridging this gap, a methodology utilising proper Lean diagnostic tools that identify waste and selection of relevant Lean tools for future state improvement works is conducted. To further validate the improvement recommendations, the use of discrete-event simulation (DES) is integrated with value stream mapping (VSM) to analyse the effects of improvement measures. A case study was addressed in an SME to improve the production performance and has led to reducing production Lead times by 58.5%, increasing process efficiency by 141.28% and cutting manufacturing cost by 51.7%. The research assists decision makers in SMEs that are interested in implementing Lean for improving their production performances.
    Keywords: value stream mapping; lean manufacturing; discrete event simulation; production performances.
    DOI: 10.1504/IJISE.2021.10045253
     
  • Multi Objective Fuzzy Transportation Problem with Fuzzy Decision variables- NSGA-II Approach   Order a copy of this article
    by Admasu Tadesse, Srikumar Acharya, Manoranjan Sahoo 
    Abstract: In this paper, we consider a multi-objective fuzzy transportation problem with a fuzzy decision variable, with main objective and constraint parameters (supply and demand) considered to be triangular fuzzy numbers. Ranking function is used to convert fuzziness of objective and constraint functions into their equivalent crisp form.The crisp multi-objective transportation problem is solved using the non-dominated sorting genetic algorithm-II (NSGA-II), which is coded in MATLAB. A case study is provided to illustrate the methodology.
    Keywords: multi-objective programming; triangular fuzzy numbers; fuzzy transportation problem; fuzzy decision variables; ranking function; non-dominated sorting genetic algorithm-II; NSGA-II.
    DOI: 10.1504/IJISE.2022.10046605
     
  • Analysis of Situation Awareness-Related Incidents in the Food Manufacturing Industry   Order a copy of this article
    by Griffin Wilson, Richard Stone, Kristina Schaffhausen 
    Abstract: A situation awareness (SA) oriented perspective on user errors and safety incidents has been widely used within aviation but seen almost no use in the manufacturing setting. This study was conducted with the objective of determining the prevalence of SA-related incidents in the food manufacturing industry. Incident investigations produced over a 72-week period from 37 different food manufacturing plants of one large multinational food producer were reviewed and categorised according to their SA-relatedness, the level of SA error occurring in each SA-related incident, and each SA errors’ relation to Endsley’s taxonomy of SA errors. The relationship between SA errors and amputations, life-altering and potentially life-altering incidents, and lockout-tagout violations is also analysed and discussed. We argue that taking this approach may reveal some novel design and training strategies which may reduce the occurrence of SA-related safety incidents in manufacturing.
    Keywords: safety engineering; situation awareness; cognitive engineering; food manufacturing; ergonomics; user-centred design.
    DOI: 10.1504/IJISE.2022.10046606
     
  • Fear of COVID-19 Outbreak, Stress and Anxiety among working employees: A Multi-Service Sector Study   Order a copy of this article
    by Pratima Verma, Sumanjeet Singh, Vimal Kumar, Minakshi Paliwal, Preeti Sharma, Sung Chi Hsu 
    Abstract: The purpose of this study is to look at the link among financial stress, psychological stress, fear factors, and anxiety in the service industry as a result of the worldwide coronavirus epidemic. Additionally, the study also identified the various fear factors due to COVID-19. Regression analysis was applied to examine the responses of 539 service sector employees in India. The results revealed that the hypothesised variables’ connections had substantial effects. Through the numerous fear variables, this study gives vital insights into the impact of epidemics on diverse service industries. Based on the demographic analysis, this study revealed that employees of every service sector organisation had a different level of fear factors. The study assists managers and human resource practitioners in developing an action plan for the period leading up to and following COVID-19, as well as communicating with their employees, which includes managers, human resource practitioners, health and government officials.
    Keywords: COVID-19; psychological stress; financial stress; anxiety; fear factors.
    DOI: 10.1504/IJISE.2022.10046612
     
  • An Optimization Approach for Multi-floor Facility Layout Design Using Flexible Bays   Order a copy of this article
    by Forough Enayaty-Ahangar, Behrooz Karimi, Negin Enayaty Ahangar, Alireza Sheikh-Zadeh 
    Abstract: We present the problem of optimising a multi-floor facility layout using the flexible bay structure that assigns block-shaped departments in parallel bays. A mixed-integer linear programming formulation is proposed to solve this problem. The decisions are determining: 1) rectangular land dimensions; 2) the number of floors; 3) each floor’s layout with the bay structure. The proposed formulation minimises the total cost associated with the layout that includes land cost, floor construction cost, elevator installation cost, and material handling cost within and among floors. To address the challenge inherited from the problem’s combinatorial dynamics, we develop a genetic algorithm utilising novel crossovers and mutations. The model and the solution approach are tested on a suite of problems from the literature. Our computational results verify the model and demonstrate that the solution approach is able to find high-quality solutions for large-scale problems in less computational time compared to the standard software.
    Keywords: facility layout; optimisation; mixed-integer linear programming; metaheuristics; genetic algorithm.
    DOI: 10.1504/IJISE.2021.10046616
     
  • Measuring Warehouse Performance: A Systematic Literature Review   Order a copy of this article
    by Ayoub Ghaouta, Ahmed Ouiddad, Chafik OKAR 
    Abstract: Recently, there has been a huge of academic interest and publications in the area of warehouse performance (WP). This can be partly explained by the growing interest giving to warehouse performance (WP) in a wide variety of industrial sectors. In this context, this paper provides an overview of the methods in use in warehouse performance measurement (WPM) using a systematic literature review (SLR) which based on the principles of rigor, transparency and replicability required by the methodology. This review paper describes the budding area of WPM, provides an overview of warehouse performance measures/criteria/techniques and develops an architectural framework. The framework enables researchers to seek fundamental knowledge and pursue further research regarding WPM. This study also provides practical value by offering a guidance for decision makers considering the trade-off among different warehouse processes and performance measurement (PM). Findings disclose that PM in WM contexts is still a productive area of research.
    Keywords: key performance indicators; logistics; systematic literature review; SLR; warehouse management.
    DOI: 10.1504/IJISE.2022.10046645
     
  • Process Improvement Using Six-Sigma DMAIC in Bearing Component Manufacturing Industry: A Case Study   Order a copy of this article
    by Sandeep Kumar Bhaskar, Manoj Kumar Sain, Manu Augustine, Praveen Saraswat, Brij Mohan Sharma 
    Abstract: Bearing parts manufacturing process is highly crucial in maintaining the quality of final product. This paper elaborates the use of the Six Sigma DMAIC approach to minimise variation in dimensions of inner and outer races of ball bearings for enhancing process quality in a manufacturing firm. In various phases of DMAIC, Six Sigma quality improvement tools like voice of customers and employee, statistical process control, control charts, process capability charts, customer/employee survey, fishbone diagram were used. MINITAB18.0 software was used for data analysis. The results revealed that the adoption of the Six Sigma DMAIC approach significantly improved the process quality. Sigma level was improved from 2.5 to 3.8; defects per million opportunities were reduced from 0.632% to 0.023% and process variation was reduced from
    Keywords: process capability analysis; process capability indices; process improvement; quality improvement; Six Sigma DMAIC.
    DOI: 10.1504/IJISE.2021.10046658
     
  • Production and construction quality management system of prefabricated buildings based on BIM technology   Order a copy of this article
    by Huilin Liu, Yadi Duan 
    Abstract: In order to improve the efficiency of quality management of prefabricated building production and construction, a quality management model and system design method of prefabricated building production and construction based on building information modelling (BIM) technology are proposed. The BIM big data of prefabricated building production and construction quality management is collected by using Internet of things technology to build BIM information database. The method of fuzzy parameter fusion and performance tracking recognition is used to realise BIM data scheduling and feature distributed fusion. Through rough set feature matching and autocorrelation feature fusion, the model information is optimised and analysed by big data, and the optimal control and convergence judgment of prefabricated component production and construction quality management are realised. The simulation results show that this method has high degree of information fusion and strong resource scheduling ability in the production and construction quality management of prefabricated components.
    Keywords: BIM technology; prefabricated building; production and construction; quality management; big data; resource scheduling.
    DOI: 10.1504/IJISE.2021.10046663
     
  • A Lion Optimization Algorithm for a Two-Agent Single-Machine Scheduling with Periodic Maintenance to Minimize the Sum of Maximum Earliness and Tardiness   Order a copy of this article
    by Reza Yazdani, Mirpouya Mirmozaffari, Elham Shadkam, Seyed Mohammad Khalili 
    Abstract: The multi-agent scheduling with periodic maintenance concerns has received little attention till recently. The focus of this research is on the single machine scheduling problem that the machine goes under periodic maintenance, for two agents with the aim of minimising the sum of maximum earliness and tardiness of jobs from the first agent, while ensuring that the sum of maximum earliness and tardiness of jobs from the second agent does not exceed an upper bound. For this NP-hard problem, the Lion optimisation algorithm is employed to find the optimal solutions. Experimental results show that the suggested lion optimisation algorithm outperforms dragonfly algorithm (DA), grasshopper optimisation algorithm (GOA), sine cosine algorithm (SCA) and Salp swarm algorithm (SSA) in computational and optimisation stability.
    Keywords: lion optimisation algorithm; LOA; multi-agent; maintenance; single machine; metaheuristic; grasshopper optimisation algorithm; GOA; sine cosine algorithm; SCA; Salp swarm algorithm; SSA.
    DOI: 10.1504/IJISE.2023.10047110
     
  • The spillover effect of COVID-19 on US financial markets-based on MF-DCCA method   Order a copy of this article
    by Renzao Lin, Liang Ying, Zhe Wang 
    Abstract: This paper uses the S&P 500 (SPX.GI), the US dollar index (FTSE.GI) and the Libor interest rate to represent the US stock market, foreign exchange market and currency market respectively. The multifractal trend cross correlation analysis (MF-DCCA) method is used to study the influence of COVID-19 on the cross correlation between the three major financial markets in the USA. The results show that there are multifractal characteristics among US stock market, money market and foreign exchange market, which show the characteristics of persistence in small fluctuation and anti-persistence in large fluctuation. Moreover, the impact of COVID-19 has greatly affected the cross correlation between the multifractal characteristics of the three financial markets in the USA. The conclusions of this paper are helpful to sort out the nonlinear dependence and potential impact dynamic mechanism among the three major financial markets in the USA.
    Keywords: COVID-19; multifractal; detrended cross correlation; MF-DCCA.
    DOI: 10.1504/IJISE.2022.10047244
     
  • Integrated production and non-cyclical maintenance planning in flow-shop environment with limited buffer   Order a copy of this article
    by Shahrzad Derakhshan, Mehdi Bijari 
    Abstract: In this paper, we work on a problem of determination of production and maintenance scheduling as well as the production lot sizes in flow-shop environment with limited buffer. We introduce a new mathematical model that can schedule production and non-cyclical maintenance activities. The objective of the problem is minimising the total costs consisting of production, setup, inventory and preventive maintenance costs. A method for linearising the mathematical model is introduced. Since the problem is NP-hard, solving the problem with proposed mathematical model in large and medium sizes is hard and time consuming. Hence, two heuristic algorithms based on fix and optimise approach are developed. For checking the solution quality, the numerical results of heuristic algorithms are compared with optimal solution, lower bound value and the best answer that gained among the examples.
    Keywords: scheduling; lot-sizing; non-cyclical preventive maintenance; limited buffer; fix and optimise algorithm.
    DOI: 10.1504/IJISE.2022.10047246
     
  • Availability optimization of Heat Treatment Process using Particle Swarm optimization approach   Order a copy of this article
    by Ajay Kumar, Devender Punia 
    Abstract: In this research paper a methodology is presented for prediction of performance parameters of a series parallel industrial system. The particle swarm optimisation (PSO) technique is used for evaluating the performance of industrial system and the Markov method is used for mathematical modelling. The mean time to failure is calculated to be 352 days and it is observed that after 30 days the reliability of the system became steady state which shows the bathtub behaviour. Using the PSO technique for maximising the system availability (SA) with ranges of performance parameters selected from the real industrial system, the different economical possible performance measures for maximum availability is predicted which are helpful for reduction in cost of production. From the performance analysis the optimised availability using PSO is estimated 94.25% whereas it is 93.60% using Markov method.
    Keywords: availability; steady state analysis; SSA; particle swarm optimisation; PSO; reliability; transient state analysis; TSA.
    DOI: 10.1504/IJISE.2022.10047431
     
  • Decision Making Support System for Medical Devices Maintenance Using Artificial Neuro Fuzzy Inference System   Order a copy of this article
    by Akram Alsukker, Nour Afiouni, Morad Etier, Mohannad Jreissat 
    Abstract: Reliable and successful maintenance management system is needed to achieve the best system with lowest costs. The lack of proper medical devices maintenance management in healthcare facilities is leading to unreliable usage of medical devices. This study focused on the decision making process of maintenance of medical devices. Each device was classified according to multiple factors, such as their function, age, price, risk, availability, and utilisation. Artificial neuro fuzzy inference system (ANFIS) was used to choose the best maintenance strategy and compared to neural networks, fuzzy inference system (FIS), and linear regression. Results showed that the best applied method was ANFIS using subtractive clustering in terms of testing data accuracy, with the highest accuracy of 82.99% compared to neural networks (78.16%) and ordinal logistic regression (73.47%). This study recommends incorporating ANFIS approach to healthcare facilities medical devices maintenance management leading to better healthcare services with minimum costs.
    Keywords: decision making; maintenance management; neural network; artificial neuro fuzzy inference system; ANFIS; medical devices.
    DOI: 10.1504/IJISE.2022.10047433
     
  • Course Scheduling Problem with Cohort Group and Room Considerations   Order a copy of this article
    by Lijian Xiao, Pratik Parikh, Xinhui Zhang 
    Abstract: We consider a variation to the course scheduling problem (CSP), referred to as the course scheduling problem with cohort group and room considerations (CSP-CgR), that incorporates two considerations; cohort group-to-room and topic-to-room assignments. While the former refers to students in each group (within a cohort) staying in the same room for most of the week to reduce student travel distances, the latter ensures that topics will be assigned to preferred rooms. We first propose a mixed integer optimisation model and then develop a nested simulated annealing (SA) based algorithm to solve real-world instances. The algorithm utilises several neighbourhood operators and contains enhancements such as probability selection and candidate listing to guide the search process. Testing this algorithm on small and large problems instances (up to 450 students, ten cohorts, 16 groups and ten rooms) suggest that high quality solutions can be obtained in under four hours.
    Keywords: course scheduling; simulated annealing; multi-objective optimisation; room planning.
    DOI: 10.1504/IJISE.2022.10047812
     
  • Analysis of construction supply chain critical success factors: A Multicriteria decision making approach   Order a copy of this article
    by Kenan Sarayji, Sharfuddin Ahmed Khan, Muhammad Shujaat Mubarik 
    Abstract: This study analyse the critical success factors (CSF’s) of construction supply chain management (CSCM) using a mix-method approach to identify and prioritise the CSF’s for CSCM performance. An extensive literature review was conducted to identify the potential CSF’s and with the help of experts, 21 relevant CSFs were selected. The analytical hierarchy process (AHP) was employed to prioritise the selected CSF’s. Results showed that the top management commitment, information sharing and flow and supply chain finance are highly ranked among all the factors. Research findings will help to minimise resource wastage on less essential things and increase efficiency. This research is unique from several perspectives. Firstly, this study is one of the first studies, which identify CSF of construction supply chain in the context of UAE. Secondly, this study provides several managerial and practical implications to managers to minimise resource wastage on less essential things and increase productivity and efficiency.
    Keywords: supply chain management; construction supply chain; critical success factors; multi-criteria decision making; MCDM; analytical hierarchal process; AHP.
    DOI: 10.1504/IJISE.2022.10047831
     
  • Investment Efficiency Evaluation of Electric Power Substation Project by Stages Using the EWM   Order a copy of this article
    by Xu Ma, Zhenyu Zhao 
    Abstract: Power grid construction projects are crucial for national industrial development. To improve the investment efficiency (IE) of substation engineering construction, this study determines the influencing factors of the input and output of substation construction projects through the entropy weight method (EWM) principle and constructs the evaluation model of IE of substation engineering construction by using data envelopment analysis (DEA) theory. Considering substation projects of a power grid company as an example, this article evaluates and compares the investment economy of one-time and phased construction to maximise the economic efficiency of substation project construction. Hence, our study provides scientific reference for investment decision-making involving substation projects and promotes collaborative planning of various regions, projects, and assets under the construction of substation projects. The results show that the IE of phased substation construction projects is higher than that of one-time construction. This effectively improves the IE of power grid companies.
    Keywords: substation project; data envelopment analysis; DEA; entropy weight method; EWM; input–output index; construction by stages; investment efficiency; IE.
    DOI: 10.1504/IJISE.2022.10047832
     
  • Study on Optimization of Supply Chain Inventory Management Based on Particle Swarm Optimization   Order a copy of this article
    by Shanyin Yao, Yehui Dong, Jiawei Gao, Minglei Song 
    Abstract: Aiming at the problems of poor convergence, high cost and low efficiency of traditional supply chain inventory management model, a supply chain inventory management optimisation method based on particle swarm optimisation (PSO) is proposed. Firstly, the whole process of particle swarm optimisation (PSO) is described. Secondly, by introducing the inventory of different nodes in the supply chain, the optimal inventory management model meeting the requirements of the supply chain model is designed. Finally, the particle swarm optimisation algorithm is used to design the optimal inventory management model and generate the optimal inventory. The experimental results show that the total inventory cost of this model is only 3.682 million Yuan, which is much lower than other traditional models. It shows that the model can effectively reduce the inventory management cost of supply chain, has high convergence, and can reduce the work intensity of relevant personnel.
    Keywords: particle swarm optimisation; PSO; supply chain; inventory; management; model.
    DOI: 10.1504/IJISE.2022.10048297
     
  • A robust nonsingular fast terminal sliding mode controller for optimizing a wind energy process   Order a copy of this article
    by Dahech Karim, Moez Allouche, Tarak Damak 
    Abstract: This paper deals with the development of a non-singular fast terminal sliding mode controller for maximum power point tracking of wind energy conversion system. The studied system is made up of a wind turbine coupled to a permanent magnet synchronous generator, a three phase diode rectifier and supplying, through a boost converter, a resistive load. The principle of the control scheme is based on electrical measurements and the choice of a suitable sliding surface. This approach presents a good transition response, a low tracking error and a very fast reaction against wind speed variations compared to the traditional sliding mode controller. The effectiveness of the proposed control scheme is demonstrated by numerical simulations under different climatic conditions.
    Keywords: wind energy process; maximum power point tracking; robust control; non-singular fast terminal sliding mode controller; Lyapunov function.
    DOI: 10.1504/IJISE.2022.10048717
     
  • Application of Cognitive Work Analysis in support of Systems Engineering of a Sociotechnical System   Order a copy of this article
    by Henk Van Den Heever, Rudolph Oosthuizen 
    Abstract: This paper presents a validation workflow to support system requirements analysis. Systems engineering supports the development of sociotechnical systems. However, the traditional systems engineering approach of reducing the system to component level to perform detailed designs and integrate them into a solution system may miss unexpected emergent behaviour when introducing a new technology into a socio-technical system. It may require changes in the socio-technical systems information flows, processes and procedures. Ignoring these emerging requirements may result in undesirable results or failures in the system. Cognitive work analysis, with work domain analysis in particular, provides a framework for analysing, modelling and designing socio-technical systems. The output abstraction hierarchy models were evaluated using a focus group approach for perceived utility in uncovering potential design emergence. The focus groups supported both the models and the proposed method. This structured approach will support requirements capturing and analysis for developing and engineering socio-technical systems.
    Keywords: cognitive work analysis; CWA; systems engineering; requirements analysis; work domain analysis; WDA; emergence; socio-technical.
    DOI: 10.1504/IJISE.2023.10048719
     
  • A VNS-IG algorithm for dynamic seru scheduling problem with sequence-dependent setup time and resource constraints   Order a copy of this article
    by Yiran Xiang, Zhe Zhang, Xue Gong, Yong Yin 
    Abstract: This paper concerns with the unspecified dynamic scheduling problem by consideration of sequence-dependent setup time and resource constraints in the setups (UDSS-SR) in a new-type seru production system (SPS). The UDSS-SR problem is formulated as a mixed integer linear programming (MILP) model to minimise the makespan, and an iterative greedy algorithm based on variable neighbourhood search (VNS-IG) is designed subsequently to facilitate decision-making in the real environment to rationalise operations and additional resources. A set of test problems are generated, and computational experiments with different instance sizes are made finally. The results indicate that the proposed VNS-IG algorithm has good performance in solving seru scheduling problem in terms of solution quality and efficiency.
    Keywords: scheduling; seru production; sequence-dependent setup time; resource constraint; hybrid intelligent algorithm.
    DOI: 10.1504/IJISE.2022.10048721
     
  • An-Optimization based System For The University Course Timetabling: A novel integer linear programming model   Order a copy of this article
    by Olfa Khlif, Jouhaina Chaouachi, Mahdi Mrad 
    Abstract: University course timetabling is an ongoing challenge that most of educational institutions face when scheduling courses. The problem assigns lectures to specific numbers of time slots and rooms while including several conflicting constraints into account. Hence, effective decision making is strongly required to provide the timetabler’s a useful toolkit. This article integrates a user friendly decision support system for the university course timetabling problem. The system employs a novel linear programming formulation that provides constraints for a great number of operational rules and requirements. Treated as an optimisation problem, the objective is to provide a best solution satisfying at most teachers’ preferences. The case of the High Institute of Business Studies of Carthage with a huge number of courses and teachers is treated along. The computational results of our system demonstrate a significant performance over the manual process on both computation time and solution quality.
    Keywords: course timetabling; teacher preference; decision support system; DSS; sum colouring problem; integer linear programming; ILP.
    DOI: 10.1504/IJISE.2022.10048765
     
  • Research on the Design of Smart Sleep Aid Interac-tive Products   Order a copy of this article
    by Hu Shan, Zhang Liyan, Guo Weiqi, Dong Zhang, Jia Qi, Zitong Yang, Guo Min 
    Abstract: The purpose of this research is to solve their problems of being uncomfortable, easy to lose, and unable to accurately determine the user’s sleep state to cause second awakening, so as to maximise the needs of users and improve the user experience. The research uses the analytic hierarchy process (AHP), quality function deployment (QFD), and function behaviour structure (FBS) models to integrate an innovative design method. This method first extracts user needs and calculates weights through an AHP. The results use convolutional neural networks to build a user sleep state model with personal sleep characteristics to achieve effective transformation of user requirements to design results. This method can improve the user experience of intelligent sleep aid products from the perspective of user needs and provide a feasible reference for the design research of intelligent sleep aid products.
    Keywords: smart products; sleep aid; analytic hierarchy process; AHP; quality function deployment; QFD; function behaviour structure; FBS model; intelligent monitoring.
    DOI: 10.1504/IJISE.2022.10048766
     
  • A semi-Markov decision model for the optimal control of an Emergency Medical Service System   Order a copy of this article
    by Giannis Kechagias, Alexandros Diamantidis, Theodosis Dimitrakos 
    Abstract: A mathematical model for the analysis of an emergency medical service (EMS) system with a specific number of advanced life support units (ALS) and a specific number of basic life support (BLS) units is presented in this paper. The system admits incoming emergency calls which are divided into two classes: 1) urgent, high-priority calls for which the patient’s life is potentially at risk; 2) less urgent low-priority calls. Under a suitable cost structure, the system is modelled using an appropriate Markov decision process in continuous time for which we seek a stationary policy that minimises a predefined optimality criterion for vehicle mixes over a set of candidate ambulance fleets. Based on this formulation, it is possible to implement standard Markov decision algorithms, such as the standard value-iteration algorithm and the standard policy-iteration algorithm. A sensitivity analysis of some model parameters is provided to examine their effect in the vehicle mix and in the cost of the system. An integer programming formulation is also provided for the corresponding location-allocation problem of the model. Numerical results are also presented for the examined problem.
    Keywords: emergency medical service system; EMS; vehicle mix; Markov decision process; MDP; integer programming.
    DOI: 10.1504/IJISE.2022.10049019
     
  • New Order-picking Routing Heuristics for Single Block Rectangular Warehouse   Order a copy of this article
    by ?Hala Ahmed, Mahassen Khater, Raafat Elshaer 
    Abstract: Order picking is the most labour-intensive and costly activity for almost every warehouse. This paper has two main objectives: first, to propose two new routing heuristics for order-picking in a rectangular warehouse, Ascending and Ascending+, and second, to investigate the impact of order region on the performance of routing heuristics. Four experiments based on dividing the warehouse into twelve main regions and large numbers of randomly generated test problems are designed to validate the proposed heuristics’ performance. The computational results demonstrate the effectiveness and efficiency of the ascending+ heuristic compared to the performance of the previously published heuristics. The statistical analysis reveals the significant impact of the order region on the performance of the routing heuristics. Therefore, each order region is allocated to the best-performed heuristic.
    Keywords: order picking heuristics; warehouse; logistics.
    DOI: 10.1504/IJISE.2022.10049128
     
  • Assessing Process Time Estimation for Job Sequencing in Moving Mixed-Model Assembly Lines   Order a copy of this article
    by Faisal Alfaiz, David Kim, Hector Vergara 
    Abstract: Job sequencing optimisation in moving mixed-model assembly lines has been studied extensively, and many optimisation procedures require average job processing times as input. However, in practice estimating average job processing times can be difficult for multiple reasons. In this study, various factors related to job processing time estimation are investigated to provide insight into more efficient job processing time estimation to support sequencing optimisation. To this end job sequencing optimisation was performed using job processing times representing estimates, where specific differences from assumed true average processing times were controlled, and separately with the assumed true average processing times. Experiments were conducted to identify the characteristics of the estimated processing times having the greatest impact on job sequence performance (i.e., the performance differences between using estimated, and assumed true processing times in job sequencing optimisation). The results indicate that if the estimated processing times used for job sequencing optimisation replicate specific properties (e.g., the rank) of true processing times, which may be different for different assembly systems, then most benefits of job sequencing optimisation may be realised.
    Keywords: sequencing; job sequencing; assembly lines; assessing processing time; mixed-model assembly lines; MMAL; processing time; processing time estimation.
    DOI: 10.1504/IJISE.2022.10049208
     
  • NBSOC Framework for Team Structure to develop Blockchain-based Applications   Order a copy of this article
    by Nitish Joshi, Tejaswi Khanna, Vikram Bali, Shivani Bali 
    Abstract: For the development of blockchain applications, platforms have been implemented by corporates like IBM, Oracle, Amazon, etc. Blockchain comprises smart contract development, which gets deployed over a peer-to-peer network. Basic skills about blockchain still lack amongst the developer community and all the people involved in developing blockchain applications. This paper proposes an NBSOC framework for organising teams to build blockchain-based applications. This framework has been used to create a team structure for implementing a land record management system. The authors have addressed the implementation challenges, cost, roles and responsibilities of an individual in the blockchain development environment.
    Keywords: blockchain; team structure; smart contract; decentralised applications; software engineering.
    DOI: 10.1504/IJISE.2022.10049488
     
  • MACHINE LEARNING FOR OPTIMIZATION OF FLOW-RACK AS/RS PERFORMANCES   Order a copy of this article
    by Zakaria Amara, Latefa Ghomri, Ali Rimouche 
    Abstract: In this paper, we are interested in flow-rack automated storage/retrieval systems (AS/RS), which are compact AS/RS. For this configuration of AS/RS we propose a new storage method based on machine learning (ML), i.e., ML method that assigns to each incoming load a position in the rack, in such a way, that the retrieval time of this same load will be optimal. In other words, we tidy out the loads inside the rack, In order to facilitate access to each type of loads. Consequently, the total (average) retrieval time in the system is minimised. The choice of ML is mainly due to the fact that the output, which is the minimisation of the average retrieval time, cannot be expressed as a function of the input, which is the choice of the most appropriate cell, for the storage of each incoming load. We compared the proposed model results with other basic storage methods. The obtained results were very satisfactory.
    Keywords: flow rack AS/RS; retrieval time prediction; supervised machine learning; regression; classification.
    DOI: 10.1504/IJISE.2022.10049510
     
  • Active stabilization of seaports co-evolution system for port throughput with time delay   Order a copy of this article
    by Xiao Xu, Hwan-Seong Kim, Truong Ngoc Cuong, Sam-Sang You 
    Abstract: This paper aims to investigate co-evolution dynamics with decision making policy for seaport throughput subjected to the time-delayed interactions. To explore interaction relationships among seaports, dynamical behaviours of co-evolution system are demonstrated using Lotka-Volterra model. Due to the time delay of interactions, the co-evolution dynamics exhibits strong fluctuations and undesirable behaviours leading to system instabilities. Adaptive fractional order sliding mode control is implemented to achieve robust stabilisation of the nonlinear co-evolution system with time delay under disturbances. The numerical simulations are presented to validate the effectiveness of the proposed control algorithm. This study systematically explains how time delays in the supply chains affect seaport co-evolution behaviours for cargo throughput and how they can be actively managed by decision making strategy. The results reveal that the proposed methodology can provide a resilience strategy under market uncertainty. Finally, conclusions are made regarding the manageable side of the time-delay problems.
    Keywords: seaport co-evolution; port throughput; time-delay; Lotka-Volterra model; adaptive fractional order sliding mode.
    DOI: 10.1504/IJISE.2022.10049595
     
  • Improving Forecast accuracy for Seasonal products in FMCG Industry: Integration of SARIMA and regression model   Order a copy of this article
    by Deepak Bartwal, Rohit Sindhwani, Omkarprasad S. Vaidya 
    Abstract: Increasing forecast accuracy of seasonal products is very critical as production; inventory and customer service depends on it. There has been introduction of new models, techniques and use of advance data analytics in forecasting, however, considering the complexity of the several causal variables and demand; it has been very difficult to get the consistent accuracy. This paper proposes integrated SARIMA (for non-seasonal component of demand) and regression (for seasonal component of demand) models for improving the forecasting accuracy. Further, we evaluate the performance of the proposed model with other known methods such as, SARIMA, ANN and SARIMAX. The performance is evaluated on various parameters of forecasting error. It is seen that for the empirical data, the proposed method outranks the other methods on all the performance metrics. Further, this paper brings into managerial insights, which can be replicated to various industries, indicating the wide scope of the proposed approach.
    Keywords: forecasting; insecticide; regression; SARIMA; seasonality.
    DOI: 10.1504/IJISE.2022.10049596
     
  • Seru scheduling problems with learning effect and job deterioration during an increasing adjustment period   Order a copy of this article
    by Ru Zhang, Zhe Zhang, Xiaoling Song, Xiaofang Zhong, Yong Yin 
    Abstract: This paper focuses on seru scheduling problems during an increasing adjustment period considering learning effects and job deteriorations, in which the job’s processing time is defined by a function of job position in the processing sequence, adjustment position and effects of learning and deterioration. Each seru has an increasing adjustment period, which means that the later the adjustment, the longer the duration. Moreover, the seru will return to its original state and the deterioration effect will restart from new position after adjustment, yet the learning effect keeps growing. The objectives are to minimise the total seru loads (TSL), the total completion times (TC) and the total absolute deviation in completion times (TADC), respectively. A general exact solution method is proposed and optimal solutions for seru scheduling problems are obtained. The comprehensive experimental analysis is conducted, and the results demonstrate that the proposed method is able to return high-quality solutions for seru scheduling problems.
    Keywords: seru scheduling; learning effect; job deterioration; increasing adjustment period; exact solution method.
    DOI: 10.1504/IJISE.2022.10049678
     
  • Analytical hierarchy process based Maintenance quality function deployment integrating Total quality management with Total productive maintenance and its application in dairy industry   Order a copy of this article
    by Jeffin Johnson, Pramod V. K, Pramod V.R. 
    Abstract: Quality enhancement of the products and services provided by manufacturing enterprises is gaining more and more attention from researchers. This research work leads to the development and implementation of AHP-based maintenance quality function deployment (MQFD) model in the dairy industry. It prioritises and identifies the prominent factors which are involved in the quality performance of the organisation. MQFD model is developed by combining TPM and TQM approaches. AHP was adopted for prioritising the decision alternatives on the basis of the main and sub-factors. Through the evaluation, the local sensitivity of critical factors such as increased profit and reliability of decisions were found to be 0.708 and 0.472, and global sensitivity of the factors such as quality of products and TQM tools were obtained as 0.351 and 0.252. The sensitivity analysis will help the organisation to find the optimum parameter in order to achieve its market goals.
    Keywords: analytical hierarchy process; AHP; quality function deployment; QFD; total productive maintenance; TPM; total quality management; TQM; maintenance quality function deployment; MQFD.
    DOI: 10.1504/IJISE.2022.10049797
     
  • Exploring the Manufacturing Flexibility Issues to Build a Framework to Implement the Manufacturing Flexibility of a Supply Chain: A Review   Order a copy of this article
    by Chowdhury Jony Moin, Mohammad Iqbal, A.B.M. Abdul Malek, Muhshin Aziz Khan 
    Abstract: Manufacturing flexibility is considered one of the most in-demand properties for manufacturing firms in the present highly competitive markets and uncertain business environment. Implementation of manufacturing flexibility is also difficult. This study aimed to minimise the difficulties in understanding the manufacturing flexibility issues through a review of highly cited scientific articles. The period of the selected articles was from the foundation of the topic (1980) to up-to-date (2021). This study explored and organised manufacturing flexibility components; manufacturing flexibility types, their interrelationships, drivers, sources, and relationship with various exogenous and endogenous issues. Finally, the study suggested a generalised framework for implementing and managing manufacturing flexibility for a homogeneous industry which would be an easy and systematic approach for decision-makers. The study concluded that to implement the manufacturing flexibility, researchers and practitioners should take a single firm or homogeneous industries of a specific supply chain as an entity rather than heterogeneous industries.
    Keywords: manufacturing flexibility; environmental uncertainty; homogeneous industries.
    DOI: 10.1504/IJISE.2022.10049929
     
  • Optimal Pricing Decisions in a Two echelon Green/non green Resilient Supply Chain for Substitute and Complementary Products Considering Disruption Risk   Order a copy of this article
    by Ashkan Mohsenzadeh Ledari, Alireza Arshadikhamseh 
    Abstract: In this paper, a pricing model is presented for substitute and complementary products, where the manufacturers 2 and 3 products are alternatives while manufacturer 1 produces a complimentary product for the others. The first manufacturer produces one green product that increases the tendency of customers for buying this product and its substitutes which brings more costs to the supply chain. Hence, the relationship between the manufacturers and the distributor is modelled by both cooperative and non-cooperative games. In the first model, the whole system works integrally, whereas, in the non-cooperative game, the model is analysed by the Stackelberg equilibrium where the manufacturers have disregarded leaders and the distributor is a follower. Moreover, potential disruption risks between the manufacturer and the distributor are considered in the current paper which means only a percentage of the distributor’s order quantity can be fulfilled by the manufacturer during disruption conditions. The optimal prices and the green degree for the products have been achieved parametrically using KKT conditions and finally, a numerical example is presented to describe the model.
    Keywords: green supply chain; GSC; pricing; green product; substitute product; complementary product; game theory; disruption risk.
    DOI: 10.1504/IJISE.2022.10049930
     
  • A Quantitative Analysis of Simultaneous Supply and Demand Disruptions on a Multi-Echelon Supply Chain   Order a copy of this article
    by Austin R. Kost, Hector Vergara, David Porter 
    Abstract: This research aimed to uncover how different features of simultaneous supply and demand disruptions impact the performance of a multi-echelon supply chain. A discrete event simulation model was developed in ARENA and a full factorial designed experiment was conducted to understand how different disruption characteristics affect key supply chain performance metrics. Historical data was obtained for a four-echelon supply chain owned by a single company using the guaranteed service model inventory policy. Results showed that the severity of a demand disruption had considerable impact on performance during the disruption period. Furthermore, disruptions that occurred further upstream in the supply chain were more likely to translate into a decrease in overall performance in the post-disruption period when compared to disruptions located elsewhere. It was also found that additional inventory can be expected to accumulate at a disrupted node which, in turn, could translate into inventory reductions immediately upstream of the disrupted node.
    Keywords: discrete event simulation; guaranteed service model; GSM; supply chain disruption; SCD; mitigation strategies; multi-echelon supply chain.
    DOI: 10.1504/IJISE.2022.10050004
     
  • Median and Interquartile Range Control Charts Based on Quantiles of Marshall-Olkin Inverse Log-logistic Distribution   Order a copy of this article
    by Olubisi L. Aako, Johnson A. Adewara, Kayode Sam Adekeye 
    Abstract: The presence of outliers makes process data deviate from normality and reduces the sensitivity of control charting procedures. This paper proposed a robust method of determining the control limits of and R charts in the presence of outliers when the data deviates from normality. The quantile of Marshall-Olkin inverse log-logistic distribution (MOILLD) is derived. The quantiles of the distribution are then used to estimate the process location and dispersion for the construction of control limits of median and interquartile range control charts. Control limit interval, false alarm rate, and average run length were used to compare the performance of the proposed control charts with similar control charts in the literature. The results showed that the proposed method detects out-of-control faster than the classical Shewhart control chart and robust control charts whose control limits were based on raw data.
    Keywords: control charts; interquartile range; inverse log-logistic distribution; median; quantiles; Marshall-Olkin inverse log-logistic distribution; MOILLD.
    DOI: 10.1504/IJISE.2022.10050090
     
  • Development of a Face Shield Concept to Protect Against COVID-19 Infection using Integrated CAD and CAE Tools and Sustainable Design Techniques: Deployment of International Standards   Order a copy of this article
    by Nasser Ramsawak, Boppana V. Chowdary 
    Abstract: To this day, the COVID-19 pandemic has infected hundreds of millions of persons globally. Counter measures to combat this virus have been orchestrated by major health enterprises that have approved solutions including vaccines, social distancing and facial protection. As such, this paper focuses on the development of a COVID-19 preventative face shield concept using integrated computer-aided design and engineering (CAD and CAE or CAD/E) tools alongside sustainable design techniques to generate a virtual model in compliance with the safety standards as recommended by the major international health organisations. The study will employ an extensive review of literature, standard product development practices, CAD drawings, and CAE simulations and analysis to facilitate the concept’s evolution. This proposal can prove highly valuable to sanitation companies owing to the recently exorbitant market demands for face shields because of the pandemic, which can in turn provide substantial profit to both a business and daily consumer.
    Keywords: COVID-19; face shield concept; computer aided design; CAD; computer aided engineering; CAE; sustainable design techniques; safety standards; product development practices.
    DOI: 10.1504/IJISE.2022.10050343
     
  • A Multi-Objective Optimisation for Green Supply Chain Network Design Problem Considering Economic and Environmental Sustainability   Order a copy of this article
    by Sreyneath Chhun, Saowanit Lekhavat, Mohammad Alghababsheh 
    Abstract: The aim of this study is to develop a multi-objective optimisation for the green supply chain network design (GSCND) problem considering economic and environmental sustainability. The economic and environmental sustainability of different facilities (i.e., suppliers, plants and distribution centres) and allocation routes under five different scenarios of demand, capacity, distance, and area were evaluated. The economic sustainability was assessed in terms of four supply chain costs (i.e., establishment, transportation, production and holding costs). Environmental sustainability was measured using the ReCipe method
    Keywords: environmental sustainability; green supply chain; multi-commodity; multi-objective optimisation; particle swarm optimisation; supply chain network design problem.
    DOI: 10.1504/IJISE.2022.10050355
     
  • Lean Manufacturing Implementation in the Food Industry in Jordan   Order a copy of this article
    by Lubna Baqlah, Hala Alsliti, Mohammed Obeidat, Samir Khrais 
    Abstract: Lean manufacturing philosophy aim to enhance operation efficiency by eliminating wastes, which are considered non-value added activities that increase costs and reduce profits in the competitive marketplace. In this study, the lean manufacturing concepts were used using the value stream mapping, to highlight areas of improvement and eliminate wastes in a thyme manufacturing line in a food factory in Jordan. The data were collected using motion and time study concepts from the factory, and both the current and future state value stream maps were constructed. The results showed that when joining packing and labelling operations in the thyme manufacturing line, the lead time was successfully reduced by 13.57%.
    Keywords: lean manufacturing; value stream mapping; VSM; thyme; food industry; Jordan.
    DOI: 10.1504/IJISE.2022.10050436
     
  • A framework for optimal patch release time using G-DEMATEL and Multi-Attribute Utility Theory   Order a copy of this article
    by Misbah Anjum, Amir H.S. Garmabaki, P.K. Kapur, Sunil Kumar Khatri, Vernika Agarwal 
    Abstract: The primary focus of the present work is to determine the optimal vulnerability patch release time using multi-attribute utility theory (MAUT) by considering two objectives that are cost minimisation and reliability maximisation. The novelty of the study lies in multi-phased research methodology for identifying the attributes affecting the software patch release time through a combination of literature review and the grey-Delphi approach for guiding the optimisation process. The literature has directly considered the weights of the attributes without emphasising their interrelationships, which is overcome by the use of the DEMATEL methodology under the grey environment in the current study for the evaluation of weights of selected attributes. The implications of the study will help in achieving the sustainable development goals pertaining to Innovation and Infrastructure. A numerical example is used to demonstrate the relevance of the optimisation problem.
    Keywords: vulnerabilities; patch release; multi-attribute utility theory; MAUT; reliability; cost; sustainable development goals; SDGs.
    DOI: 10.1504/IJISE.2022.10050488
     
  • A Revenue-based Decision-making Approach for Evaluating Modular Product Release Plans under Resource Constraints   Order a copy of this article
    by Adewole Adegbola, Venkat Allada 
    Abstract: This study introduces the module substitution concept to develop an approach for assessing different strategies for modular product release in a technology-receptive market. We consider a situation where product variants emerge from modules which have varying modular relationships, and each module is defined by specific attributes. The statistical program evaluation and review technique (statistical PERT) was then adopted to address the uncertainties associated with module attributes. A practical example involving the development of modules, product families and their product variants is used to demonstrate the applicability of the approach in which feasible strategies that satisfy the development resource constraint were identified. We then introduced a substitute module to yield a product variant and re-evaluated the strategies. The results obtained shows that the approach is instrumental in assessing various alternatives based on launch timings and revenue generation and can be adopted by managers in deciding on the appropriate product release plan.
    Keywords: product release; product variants; resource constraint; module substitution; statistical PERT.
    DOI: 10.1504/IJISE.2022.10050936
     
  • Ergonomics intervention with DMAIC methodology application   Order a copy of this article
    by Nur Nadia Nadirah Yusuf, Shaliza Azreen Mustafa, Rosmaini Ahmad 
    Abstract: This study aims to assess the level of ergonomics risk factors (ERFs) in production workstations using ergonomics assessment tools and provide an appropriate solution to improve the safety and health of the workers. A systematic approach using define-measure-analyse-improve-control (DMAIC) methodology was applied. Initial assessment found that awkward posture was the main ERF emerging in the company. Under the Measure and Analyse phases, the rapid upper limb assessment (RULA) and rapid entire body assessment (REBA) tools were applied to further assess of the identified ERFs. Results found that the filling task is the highest risk condition. Improve phase involved improvements action based on simple invention using a wooden step stool to provide a neutral working posture and the REBA has showed the signs of low risk comparatively. Related recommendations based on hazard identification, risk assessment and risk control (HIRARC) were then given in Control phase for future work planning.
    Keywords: ergonomics assessment; musculoskeletal disorders; MSD; DMAIC; RULA; REBA; food industry.
    DOI: 10.1504/IJISE.2022.10050938
     
  • Automatic error calibration system for English semantic translation based on machine learning   Order a copy of this article
    by Zhenhua Wei 
    Abstract: The traditional English semantic translation error calibration system can not determine the optimal translation solution, which has the problems of high CPU utilisation, low translation accuracy and high calibration time-consuming. Before English semantic translation, English semantic features are decomposed to realise fuzzy mapping selection of English semantic translation, English semantic translation decision function is obtained by constructing semantic ontology model, English semantic translation error automatic calibration algorithm is realised by machine learning algorithm, design the overall architecture and network topology of the system, and complete the design of automatic proofreading system of English semantic translation errors. The experimental results show that the running time of the proposed system is 1.5 s, the CPU occupancy rate of the designed system is only 0.9%, and the calibration accuracy is as high as 99%.
    Keywords: dimensionless treatment; calibration algorithm; high CPU utilisation; low translation accuracy; high calibration time-consuming; machine learning; translation decision function.
    DOI: 10.1504/IJISE.2021.10051045
     
  • Implementation of Internet of Things (IoT) in Micro, Small and Medium Enterprises: A Case Study   Order a copy of this article
    by Parikshit Sarulkar, Kumar Srinivasan, Anish Kumar, Vineet Kumar Yadav 
    Abstract: Micro, small, and medium enterprises (MSMEs) play a vital role in India’s economic growth. MSMEs operating in the scrap management sector encounter two main concerns about the transportation cost and scheduling of vehicles. To solve these issues, MSMEs are trying to adopt emerging technologies such as automatic scrap storage, inventory control, and retrieval systems. However, MSMEs are reluctant to implement these technologies due to their pre-assumption of high adoption costs and expected benefits. The present study focused on the effective IoT implementation in vehicle loading to reduce transportation costs and trips in MSMEs. The case study of the scrap managing company has been considered to show the benefits of IoT implementation in MSMEs. The simulation was performed using FlexSim, and the results have confirmed that the IoT implementation can improve vehicle loading by 38% and reduce transportation costs by 38.6%. The outcomes highlight the benefits of IoT deployment in MSMEs.
    Keywords: micro; small; and medium enterprises; MSMEs; scrap management; IoT implementation; transportation; FlexSim simulation.
    DOI: 10.1504/IJISE.2022.10051062
     
  • Dynamic Futures Margin Setting Method under State Dependence   Order a copy of this article
    by Wang Hong, Kun Wen, Shouqian Kang 
    Abstract: Margin is not only a basic risk control system for futures trading, but also an important part of the cost of futures trading, and its fundamental position is very important. This paper presents a dynamic margin setting method for futures based on market state, which considers extreme risk control and opportunity cost. In different market conditions, we choose different margin levels to better balance spillover probability and opportunity cost. Using machine learning, we sample the sugar futures traded on the Dalian Commodity Exchange between January 6, 2006, and May 29, 2020. The market is divided into three categories by the hidden Markov model: highly volatile, volatile, and stable. We compare margin level under VaR, CVaR, MMVaR, EWMA and improved EWMA risk standards. Comparative analysis and retrospective test show that the current fixed margin ratio is unreasonable, and the margin level under the single risk criterion cannot balance risk control and opportunity cost well. We recommend that market regulators dynamically adjust margin setting levels according to different market states, thereby luring more investors to invest and boosting the liquidity of the futures market.
    Keywords: dynamic margin level; risk criteria; machine learning; market status.
    DOI: 10.1504/IJISE.2022.10051100
     
  • Modified Ant Colony Algorithm for Job Shop Scheduling Problem   Order a copy of this article
    by Ye Li, Ning Wang, Kun Xu 
    Abstract: In this work, we proposed a modified ant colony algorithm (ACA) for job shop scheduling problem (JSSP) with make-span, and constraints such as machine selection, time lags, and holding times, process, and sequence are taken into account. The two-stage setup of the pheromone update mechanism allows for a combination of local and global pheromone updates. In the first stage, the pheromone is updated locally for each completed process, and after the set iteration conditions have been met, the second stage is entered. To overcome the initial reliance on pheromones in the ACA, the pheromones are initialised using a genetic algorithm (GA). The optimal convergence ratio is obtained through the design of a genetic operator based on the procedure principle to accelerate the convergence effect of the whole algorithm and improve the global searching ability of ACA. Taking an engine company as an example, several simulation experiments are carried out for GA, ACA, and modified ant colony algorithm (MACA) based on the standard dataset to verify the effectiveness of proposed algorithms.
    Keywords: job shop scheduling problem; JSSP; ant colony algorithm; ACA; genetic algorithm; modified ant colony algorithm; MACA; optimal convergence ratio.
    DOI: 10.1504/IJISE.2022.10051301
     
  • Efficient Bayesian optimization of bounded general loss function for robust parameter design   Order a copy of this article
    by YING CHEN, Mei Han 
    Abstract: Robust parameter design (RPD) has been generally employed to minimise the system quality loss caused by noise perturbation via setting control factors in engineering design. Bayesian optimisation algorithms have received increasing attention for RPD, which includes establishing the Kriging model and developing acquisition functions (AFs). In RPD, the quality loss function method is a common method to calculate the response deviation from a target value. The existing literature mainly focuses on setting the loss function as a quadratic function for easier calculation, while it is not always reasonable due to its unboundedness. In this paper, we propose three efficient Bayesian algorithms for bounded general loss functions for finding the optimal design of control factors based on a Kriging model. We develop a Monte Carlo sampling method to approximate the proposed AFs. Three numerical examples and a rocket injector case are used to demonstrate the effectiveness of the proposed algorithms.
    Keywords: Bayesian optimisation; robust parameter design; RPD; bounded general loss function; acquisition function; Gaussian process model.
    DOI: 10.1504/IJISE.2022.10051366
     
  • Development of a Prescription Framework for Supply Chain Risk Management: Cases of Asian MNCs   Order a copy of this article
    by Jae-Yong Yang, Geun-wan Park, Kwangtae Park, Rajesh Piplani 
    Abstract: We use the level of impact and duration of risk to classify types of supply chain risks and their effective prescriptions using case studies of multi-national companies. The classification of supply chain risks and countermeasures for each risk type are presented as a risk diagnosis and prescription matrix. The companies adopt a risk acceptance strategy when the impact is low and the duration short. When impact is high and the duration short, substitute raw materials (or production sites) are considered under risk avoidance strategy. New suppliers and technologies are developed for complete replacement for risk mitigation when the duration of risk is long but the impact low. For risk-sharing, new demand sources are developed, and diversification of suppliers and production sites pursued when the risk duration is long and the impact high. Novelty of our study is in considering risk duration as an additional variable in risk management strategy.
    Keywords: supply chain risk; prescription matrix; Asian MNC.
    DOI: 10.1504/IJISE.2022.10051409
     
  • Design of intelligent system for indoor illumination adjustment based on deep learning   Order a copy of this article
    by ChenQun Wu 
    Abstract: In order to overcome the low adjustment accuracy and efficiency of the traditional regulation system, this paper designed an indoor lighting intensity intelligent regulation system based on deep learning. The hardware part of the system is designed by deep learning. Then, based on the analysis of sensor data and historical data, the corresponding intelligent adjustment table is formed. After the convolution and pooling operation, the training samples are combined with restricted Boltzmann machine. At the same time, the natural illumination model is built based on the time cycle variation characteristics of sunlight, and the indoor and outdoor illumination is calculated with the deep learning results, so as to obtain the brightness level of dimming, so as to realise intelligent regulation. The experimental results show that the intelligent adjustment accuracy of the system is between 95.0% and 98.5%, and the adjustment efficiency is always above 95%.
    Keywords: deep learning; indoor illumination; illumination adjustment; illumination model.
    DOI: 10.1504/IJISE.2021.10051759
     
  • Cross-domain management system of real estate sales information based on blockchain   Order a copy of this article
    by Shu Xue, Simin Wei 
    Abstract: In the existing real estate sales information management system, the efficiency of information cross domain management is low, and the information security is poor. The whole architecture of real estate sales information system includes sales information collection module, intelligent contract execution module and real estate information encryption module; the discrete wavelet transform method is used to fuse similar data, and the intelligent contract is designed according to the data fusion results, and all sales information is encrypted; then the trust model of blockchain certificate authorisation centre is designed, and the final result is verified Real estate sales information access cross domain authentication, real estate sales information cross domain management system design. The experimental results show that the safety factor of the system data designed in this paper can reach 0.99, and the system response delay is about 0.5 s.
    Keywords: Blockchain technology; real estate sales; information cross-domain; management system.
    DOI: 10.1504/IJISE.2021.10051909
     
  • A fast encryption method of large enterprise financial data based on adversarial neural network   Order a copy of this article
    by Youwei Chu  
    Abstract: In order to overcome the high time cost of encrypting, decrypting and revocation attribute calculation existing in traditional encryption methods of financial data of large enterprise, this paper proposes a fast encryption method of financial data of large enterprise based on adversarial neural network. Adversarial neural network is used to build the financial data reorganisation model of large enterprise, and obtain the sparse and local characteristics of the reorganised financial data of large enterprise, so as to generate the encrypted initial key and sub-key, and complete the fast encryption of the financial data of large enterprise by combining matrix transformation. The simulation results show that the average time cost of encryption is 0.115 s, the average time cost of decryption is 0.05 s, and the average time cost of undo calculation is 0.616 s, which can realise the fast encryption of financial data of large enterprise.
    Keywords: adversarial neural network; data encryption; enterprise financial data.
    DOI: 10.1504/IJISE.2021.10052415
     
  • An Enterprise Financial Data Risk Prediction Model Based on Entropy Weight Method   Order a copy of this article
    by Wenyuan Chen 
    Abstract: The traditional financial risk prediction model has some problems, such as inaccurate prediction results due to the poor selection of risk index system. This paper proposes to build an enterprise financial data risk prediction model based on entropy weight method. Build the enterprise risk financial data prediction index system and obtain the prediction index; The entropy weight method is used to calculate the weight of prediction index and obtain the weight coefficient; The data with higher risk index weight is input into the neural network as the initial vector of prediction, the weight of risk data nodes at different levels of the network is calculated, the risk prediction model is constructed, and the error of the output solution of the model is corrected by the incentive function to realise the risk prediction. The experimental results show that the prediction accuracy of the model is always about 98%.
    Keywords: entropy method; enterprise financial risk; index system; weight; predictive model.
    DOI: 10.1504/IJISE.2021.10052416
     
  • Judgment Method of Enterprise Financial Data Abnormality Based on High-Order Dynamic Bayesian Network   Order a copy of this article
    by Lili Wang  
    Abstract: This paper proposes a judgement method of enterprise financial data anomaly based on high-order dynamic Bayesian network. Firstly, the enterprise financial data is divided into normal data and abnormal data, and the original training samples are classified to obtain the data classification results. Input the classification results into the enterprise financial data management platform based on cloud computing to improve the efficiency of data anomaly judgement. The high-order dynamic Bayesian network is used to initialise and modify the network, and the chromosome coding method is used to realise the abnormal judgement of enterprise financial data. The experimental results show that the method has higher accuracy rate of anomaly judgement, lower miss rate and error rate.
    Keywords: high-order dynamic Bayesian network; financial data; network modification; chromosome coding; data classification.

  • Study on regional digital teaching resource sharing platform based on Internet of things and big data   Order a copy of this article
    by Xiaohong Zhu 
    Abstract: In order to overcome the problems of low upload rate and poor data integrity of traditional teaching resource sharing platforms, the paper proposes a regional digital teaching resource sharing platform based on the internet of things and big data. Introduce the least square algorithm to construct the operation and maintenance elastic model, and calculate the dual residual and the original residual of the model output data. The platform adopts the WebAPI framework, including the design of user login service, teacher resource information service, teaching information service, and online recommendation service for sharing teaching information. The experimental results show that the platform designed in this paper has a higher transmission rate, which has been maintained above 4G/s with the increase of time. In the state of network interruption, the platform’s return matrix data status detection shows that the storage data of the platform in this paper does not appear abnormal.
    Keywords: internet of things; big data; ADMM algorithm; operation and maintenance elasticity; dual function; lagrange function.

  • Abnormal Recognition of Corporate Financial Data Based on Deep Belief Network   Order a copy of this article
    by Xi Lun, Xiangyang Zhang, Yining Wang, Tian Wang 
    Abstract: In view of the traditional enterprise financial data exception recognition methods such as low recognising precision, long, belief network is put forward based on the depth of the enterprise’s financial data anomaly identification method, adopts the distributed data collection method, selection of enterprise financial data mining, and correlation analysis, according to the financial data of sample information entropy, to divide the financial data flow, According to the extraction results, use the deep belief network to build a financial data anomaly recognition model. The financial data of enterprises are input into the abnormal identification model of financial data to identify the status of financial data. Experimental results show that this method has higher recognition accuracy and shorter recognition time.
    Keywords: deep belief network; corporate financial data; information entropy; data stream fragment.
    DOI: 10.1504/IJISE.2021.10052450
     
  • A clustering method of marketing effective data based on relation matrix fusion   Order a copy of this article
    by LinLin Zhou  
    Abstract: In order to overcome the problems of traditional clustering methods, such as low recall rate, low clustering accuracy and poor clustering efficiency, an effective marketing data clustering method based on relation matrix fusion is proposed. The relationship matrix fusion process is designed, and the effective data in the marketing data is selected according to the fusion results. Then, the feature units of effective marketing data are extracted, and the data clustering problem is transformed into a linear programming problem by calculating the EMD distance between the data. Finally, data clustering is completed according to the results of data integration. The experimental results show that the recall rate of effective marketing data is between 94.5% and 98.3%, the clustering accuracy is between 95.1% and 98.7%, and the maximum number of iterations is 900, which proves that the method achieves the design expectation.
    Keywords: marketing data; valid data; relation matrix fusion; EMD distance; data clustering; Earth mover’s distance.
    DOI: 10.1504/IJISE.2021.10052451
     
  • Construction of Prediction Model for Individual Investors’ Psychology and Behavior Based on Cognitive Neuroscience   Order a copy of this article
    by Guangdong Liu, Sang Fu, Shiyong Liu 
    Abstract: Traditional forecasting models cannot extract the trend information of retail investors' multi-scale psychological and behavioural data, and the predictions are not accurate. To solve this problem, a Markov-based individual investor psychology and behaviour prediction model is proposed. Using the wavelet multi-scale analysis method , the multi-scale data of individual investor's psychology and behaviour are extracted. A long-term-memory analysis is performed on multi-scale data of individual investors’ psychology and behaviour using the correlation analysis method, and the trend information is extracted. On this basis, a Markov prediction model is established, and a modified investment preference model is introduced to improve the accuracy of the prediction. Using the individual similarity degree, the nearest neighbour set of the target individual is established, and a multi-order predictive Markov fusion model for multiple individuals is formed to achieve accurate prediction. The experimental results show that the proposed model achieves better nonlinear fitting and higher prediction accuracy.
    Keywords: individual investors; psychology and behaviour; prediction model; Markov.
    DOI: 10.1504/IJISE.2022.10046762
     
  • Productivity enhancement in caravan manufacturing: an organisational resource centric approach   Order a copy of this article
    by Ngwenya Andries Rakobela, Michael Kweneojo O. Ayomoh, Thinandahva Thomas Munyai, Kgashane Stephen Nyakala 
    Abstract: This paper has identified organisational factors and resources that contribute to low productivity and poor quality in caravan manufacturing. Eight productivity-enhancing factors directly linked to caravan manufacturing process were identified and a framework to enhance productivity of caravan manufacturing was proposed. The dataset utilised in this research was obtained from a qualitative data gathering process premised on system observation. The supplier input process output customer (SIPOC) and value stream mapping (VSM) were both utilised to assess the current 'as-is' productivity level of the case-study system. The same tools were deployed for identification of waste generating processes in the system, conduct of analysis for reduction of work in progress inventory and lead times associated with non-value adding activities. The analysis conducted herein was carried out through content and comparative analysis methods using MS Excel 2013 software while the causes and effect matrix was used for data measurement on a prescribed rating scale.
    Keywords: caravan manufacturing; organisational resources; productivity; quality enhancement.
    DOI: 10.1504/IJISE.2021.10039311
     
  • A forward modelling approach to optimise the portfolio of projects among oil companies under uncertainty: a reactive two-stage stochastic model   Order a copy of this article
    by Mohsen Fayyazi, Siamak Haji Yakhchali, Mir Saman Pishvaee, Fariborz Jolai 
    Abstract: Because of high volatility in oil price, oil companies should change their strategies along with changing oil prices. Thus, dynamic portfolio management is strongly recommended to increase the rate of oil production and determine resource allocation for projects in each period of the planning horizon. To achieving the objective, a two-stage stochastic mathematical model is developed to optimise the portfolio of oil projects. To make the model more realistic, splitting the projects and their resumption are permitted. To solve the model, a robust optimisation approach is designed, and the results of the robust and two-stage stochastic designs are compared. These comparisons are based on a realisation algorithm developed by this study. To illustrate the capability and power of the stochastic model in handling the uncertainty, a case study on an oil company is presented.
    Keywords: portfolio management; resource assignment; project scheduling; stochastic programming; robust optimisation.
    DOI: 10.1504/IJISE.2021.10038570
     
  • A system dynamic to reforming of the healthcare sector in the Indonesian National Health Insurance System Program   Order a copy of this article
    by Diva Kurnianingtyas, Budi Santosa, Nurhadi Siswanto 
    Abstract: National Health Insurance System (NHIS) was established by the Indonesian Government to ensure the health needs of its people. However, the programme encountered many obstacles due to inefficiencies caused by changes in people's behaviour. The aim is to identify key factors, evaluate and plan further policies using Indonesian data from 2014 to 2018. The system's dynamics approach is used to build a model for determining policy alternatives that only focuses on referral reform and limiting health service coverage. The proposed model was proven correct and then implemented in 2019 to plan a policy solution. The result was limiting healthcare coverage as a short-term strategy, whereas changing tiered referrals to combined referrals could be considered a long-term strategy. However, the success of this strategy will only occur if there is good collaboration between health services and regulations. In addition, it is necessary to improve the structure of healthcare.
    Keywords: system dynamics; simulation; National Health Insurance System; NHIS; patient referral mechanism; financial strategy.
    DOI: 10.1504/IJISE.2021.10039542
     
  • A model-based decision framework for the multi-depot multi-travelling salesman problem with split and delivery demand considering different key performance indicators   Order a copy of this article
    by Daniela Contreras, Rodrigo Linfati, John Willmer Escobar 
    Abstract: This paper introduces the multi-depot multi-travelling salesman problem with split and delivery demand (MmTSP-SD). The problem has been formulated as a flexible optimisation model that considers four key performance indicators (KPIs): the minimisation of the route distance, the minimum daily demand to satisfy similar demand between crews, and the equivalent kilometres travelled between crews. The efficiency of the proposed approach has been tested in three types of instances adapted from a green area maintenance company dedicated to the management of any vegetation, cutting grass or weeds and/or collecting leaves, watering, or fertilising, among many other services. The results confirm the efficiency of the proposed approach and the positive impact in determining the different performance measures that are considered.
    Keywords: multi-travelling salesman problem; m-TSP; balance of travellers; key performance indicator; KPI; MmTSP-SD; visit planning; mixed-integer linear programming.
    DOI: 10.1504/IJISE.2021.10038690
     
  • Goal programming approach for agile sustainable pharmaceutical supply chain   Order a copy of this article
    by Meghdad Haji Mohammad Ali Jahromi, Ali Nazeri, Ehsan Ghorbani 
    Abstract: In this paper, a pharmaceutical supply chain network with four levels including suppliers, major distributors, retailers and customers was considered and in order to have agility and sustainability benefits simultaneously, goal programming approach has been used. In fact, an optimum structure regarding sustainable aspects of supply chain in light of economic, social, environmental and political aspects (i.e., as important aspects in the current situation) were designed. Also, for this purpose, a digraph corresponded to a feasible structure under real situation of pharmaceutical supply chain was considered, and then with help of goal programming approach, an optimum configuration, which is a sub-digraph from the main, will be achieved. Results show that the model has high capability to configure pharmaceutical chain according to expectations of the managers and experts of the chain.
    Keywords: sustainable supply chain; goal programming; pharmaceutical supply chain.
    DOI: 10.1504/IJISE.2021.10038796
     
  • PMP approach for solving the binary static multi-objective generalised cell formation problem   Order a copy of this article
    by Youkyung Won 
    Abstract: The p-median problem (PMP) approach has been used as an effective alternative for solving small-to-medium-sized single-objective cell formation (SOCF) problems. Cell load balancing is an important consideration in multi-objective cell formation (MOCF) problems for reflecting realistic manufacturing factors. However, few cell formation (CF) studies using the conventional PMP approach with the binary machine-part incidence matrix (MPIM) alone have considered multiple objectives including cell load balancing because the conventional binary MPIM can only indicate whether parts are processed on particular machines. In this study, we emphasise the importance of cell load balancing even in binary MPIM-based multi-objective generalised cell formation (MOGCF) problems with alternative process plans for parts and demonstrate that the binary MPIM-based CF without consideration of cell load balancing can lead to inferior solutions. This study shows that the PMP approach can effectively solve large-sized MOGCF problems by considering the minimisation of cell load imbalance and inter-cellular part moves, which result in inefficient cells. Our PMP approach first solves the SOCF problem and then attempts to satisfy conflicting multiple objectives ex post facto with a subsequent heuristic procedure. The computational results show that the proposed PMP approach is very effective for large-sized MOGCF problems.
    Keywords: PMP approach; generalised multi-objective cell formation; cell load balancing.
    DOI: 10.1504/IJISE.2021.10038798