Template-Type: ReDIF-Article 1.0
Author-Name: Admasu Tadesse
Author-X-Name-First: Admasu
Author-X-Name-Last: Tadesse
Author-Name: Srikumar Acharya
Author-X-Name-First: Srikumar
Author-X-Name-Last: Acharya
Author-Name: Manoranjan Sahoo
Author-X-Name-First: Manoranjan
Author-X-Name-Last: Sahoo
Title: Multi-objective fuzzy transportation problem with fuzzy decision variables - NSGA-II approach
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 398-415
Issue: 3
Volume: 45
Year: 2023
Keywords: multi-objective programming; triangular fuzzy numbers; fuzzy transportation problem; fuzzy decision variables; ranking function; non-dominated sorting genetic algorithm-II; NSGA-II.
File-URL: http://www.inderscience.com/link.php?id=134714
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Handle: RePEc:ids:ijisen:v:45:y:2023:i:3:p:398-415

Template-Type: ReDIF-Article 1.0
Author-Name: Pratima Verma
Author-X-Name-First: Pratima
Author-X-Name-Last: Verma
Author-Name: Sumanjeet Singh
Author-X-Name-First: Sumanjeet
Author-X-Name-Last: Singh
Author-Name: Vimal Kumar
Author-X-Name-First: Vimal
Author-X-Name-Last: Kumar
Author-Name: Minakshi Paliwal
Author-X-Name-First: Minakshi
Author-X-Name-Last: Paliwal
Author-Name: Preeti Sharma
Author-X-Name-First: Preeti
Author-X-Name-Last: Sharma
Author-Name: Sung Chi Hsu
Author-X-Name-First: Sung Chi
Author-X-Name-Last: Hsu
Title: Fear of COVID-19 outbreak, stress and anxiety among working employees: a multi-service sector study
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, and health and government officials.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 378-397
Issue: 3
Volume: 45
Year: 2023
Keywords: COVID-19; psychological stress; financial stress; anxiety; fear factors.
File-URL: http://www.inderscience.com/link.php?id=134715
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Handle: RePEc:ids:ijisen:v:45:y:2023:i:3:p:378-397

Template-Type: ReDIF-Article 1.0
Author-Name: Ayoub Ghaouta
Author-X-Name-First: Ayoub
Author-X-Name-Last: Ghaouta
Author-Name: Ahmed Ouiddad
Author-X-Name-First: Ahmed
Author-X-Name-Last: Ouiddad
Author-Name: Chafik Okar
Author-X-Name-First: Chafik
Author-X-Name-Last: Okar
Title: Measuring warehouse performance: a systematic literature review
Abstract:
Recently, there has been a huge amount of academic interest and publications in the area of warehouse performance (WP). This can be partly explained by the growing interest giving to 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 guidance to decision-makers considering the trade-off between different warehouse processes and performance measurement (PM). The findings disclose that PM in WM contexts is still a productive area of research.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 321-364
Issue: 3
Volume: 45
Year: 2023
Keywords: key performance indicators; logistics; systematic literature review; SLR; warehouse management.
File-URL: http://www.inderscience.com/link.php?id=134716
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Handle: RePEc:ids:ijisen:v:45:y:2023:i:3:p:321-364

Template-Type: ReDIF-Article 1.0
Author-Name: Sandeep Kumar Bhaskar
Author-X-Name-First: Sandeep Kumar
Author-X-Name-Last: Bhaskar
Author-Name: Manoj Kumar Sain
Author-X-Name-First: Manoj Kumar
Author-X-Name-Last: Sain
Author-Name: Manu Augustine
Author-X-Name-First: Manu
Author-X-Name-Last: Augustine
Author-Name: Praveen Saraswat
Author-X-Name-First: Praveen
Author-X-Name-Last: Saraswat
Author-Name: Brij Mohan Sharma
Author-X-Name-First: Brij Mohan
Author-X-Name-Last: Sharma
Title: Process improvement using Six Sigma DMAIC in the bearing component manufacturing industry: a case study
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, and 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 ±5 to ±3 and was well within target limits.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 271-290
Issue: 3
Volume: 45
Year: 2023
Keywords: process capability analysis; process capability indices; process improvement; quality improvement; Six Sigma DMAIC.
File-URL: http://www.inderscience.com/link.php?id=134717
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Handle: RePEc:ids:ijisen:v:45:y:2023:i:3:p:271-290

Template-Type: ReDIF-Article 1.0
Author-Name: Shahrzad DerakhshanHoreh
Author-X-Name-First: Shahrzad
Author-X-Name-Last: DerakhshanHoreh
Author-Name: Mehdi Bijari
Author-X-Name-First: Mehdi
Author-X-Name-Last: Bijari
Title: Integrated production and non-cyclical maintenance planning in flow-shop environment with limited buffer
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 291-320
Issue: 3
Volume: 45
Year: 2023
Keywords: scheduling; lot-sizing; non-cyclical preventive maintenance; limited buffer; fix and optimise algorithm.
File-URL: http://www.inderscience.com/link.php?id=134718
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Handle: RePEc:ids:ijisen:v:45:y:2023:i:3:p:291-320

Template-Type: ReDIF-Article 1.0
Author-Name: Shanyin Yao
Author-X-Name-First: Shanyin
Author-X-Name-Last: Yao
Author-Name: Yehui Dong
Author-X-Name-First: Yehui
Author-X-Name-Last: Dong
Author-Name: Jiawei Gao
Author-X-Name-First: Jiawei
Author-X-Name-Last: Gao
Author-Name: Minglei Song
Author-X-Name-First: Minglei
Author-X-Name-Last: Song
Title: Study on optimisation of supply chain inventory management based on particle swarm optimisation
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 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 PSO 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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 365-377
Issue: 3
Volume: 45
Year: 2023
Keywords: particle swarm optimisation; PSO; supply chain; inventory; management; model.
File-URL: http://www.inderscience.com/link.php?id=134719
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Handle: RePEc:ids:ijisen:v:45:y:2023:i:3:p:365-377

Template-Type: ReDIF-Article 1.0
Author-Name: Jaydeepsinh M. Ravalji
Author-X-Name-First: Jaydeepsinh M.
Author-X-Name-Last: Ravalji
Author-Name: Shruti J. Raval
Author-X-Name-First: Shruti J.
Author-X-Name-Last: Raval
Author-Name: Ghulamkhwaza Qureshi
Author-X-Name-First: Ghulamkhwaza
Author-X-Name-Last: Qureshi
Author-Name: Himadri Shukla
Author-X-Name-First: Himadri
Author-X-Name-Last: Shukla
Title: Insightful implementation of lean tools to cultivate lean culture in a small scale manufacturing organisation - a case study
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 52-74
Issue: 1
Volume: 44
Year: 2023
Keywords: lean manufacturing; 5S; value stream mapping; VSM; Kaizen.
File-URL: http://www.inderscience.com/link.php?id=130912
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:1:p:52-74

Template-Type: ReDIF-Article 1.0
Author-Name: Radhika Agarwal
Author-X-Name-First: Radhika
Author-X-Name-Last: Agarwal
Author-Name: Shweta Upadhyaya
Author-X-Name-First: Shweta
Author-X-Name-Last: Upadhyaya
Author-Name: Divya Agarwal
Author-X-Name-First: Divya
Author-X-Name-Last: Agarwal
Author-Name: Sumit Kumar
Author-X-Name-First: Sumit
Author-X-Name-Last: Kumar
Title: Cost optimality of an erratic <i>Geo<SUP align="right"><SMALL>X</SMALL></SUP></i>/<i>G</i>/1 retrial queue under J-vacation scheme using nature inspired algorithms
Abstract:
In this article, we have explored a &lt;i&gt;Geo&lt;SUP align="right"&gt;&lt;SMALL&gt;X&lt;/SMALL&gt;&lt;/SUP&gt;&lt;/i&gt;/&lt;i&gt;G&lt;/i&gt;/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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 1-33
Issue: 1
Volume: 44
Year: 2023
Keywords: discrete-time; starting failure; normal breakdown; J-vacation; Bernoulli feedback; cost optimisation; direct search; particle swarm optimisation; PSO; artificial bee colony; ABC; cuckoo search.
File-URL: http://www.inderscience.com/link.php?id=130913
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:1:p:1-33

Template-Type: ReDIF-Article 1.0
Author-Name: Shikhar Saxena
Author-X-Name-First: Shikhar
Author-X-Name-Last: Saxena
Author-Name: Rajesh Piplani
Author-X-Name-First: Rajesh
Author-X-Name-Last: Piplani
Title: Integrated scheduling and vehicle routing at cross-dock distribution centre: a simulated annealing approach
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 2-3 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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 427-457
Issue: 4
Volume: 44
Year: 2023
Keywords: cross-docking; routing and scheduling; delivery window; meta-heuristic; product consolidation; simulated annealing.
File-URL: http://www.inderscience.com/link.php?id=132709
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:4:p:427-457

Template-Type: ReDIF-Article 1.0
Author-Name: Tareq N. Issa
Author-X-Name-First: Tareq N.
Author-X-Name-Last: Issa
Title: Implementing lean-kaizen for manufacturing operations improvement: a case-study in the plastics industry
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 &lt;i&gt;lean-kaizen&lt;/i&gt; 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%.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 118-139
Issue: 1
Volume: 44
Year: 2023
Keywords: lean-kaizen concept; kaizen event; cycle-time reduction; plastic bags industry; value stream map.
File-URL: http://www.inderscience.com/link.php?id=130917
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:1:p:118-139

Template-Type: ReDIF-Article 1.0
Author-Name: Dongwei Shi
Author-X-Name-First: Dongwei
Author-X-Name-Last: Shi
Title: New mechanism of credit risk control in order agriculture
Abstract:
The bilateral default rate of farmers and companies is usually high in contract farming. Inspired by the rule of 'mark-to-market' in futures market, this paper proposes a new 'mid-term mark-to-market' model of contract farming to avoid the bilateral default risk. We design of the contract farming coordination mechanism under the new model and give the explicit expressions of the optimal decision-making as well as the incomes of companies and farmers. Taking soybean production as an example, empirical study is conducted to compare the bilateral expected return and default probability of the new model compared to the traditional order model. The research results show that the new proposed model can increase the total expected return and reduce the bilateral default rate of farmers and companies. Among them, the inhibitory effect on default rates of the new model is particularly significant.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 499-514
Issue: 4
Volume: 44
Year: 2023
Keywords: contract farming; bilateral default risk; mark-to-market.
File-URL: http://www.inderscience.com/link.php?id=132710
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:4:p:499-514

Template-Type: ReDIF-Article 1.0
Author-Name: Tapan P. Bagchi
Author-X-Name-First: Tapan P.
Author-X-Name-Last: Bagchi
Author-Name: R.P. Mohanty
Author-X-Name-First: R.P.
Author-X-Name-Last: Mohanty
Author-Name: Surajit Sinha
Author-X-Name-First: Surajit
Author-X-Name-Last: Sinha
Title: A tutorial on optimisation involving the David Ricardo theory on comparative advantage
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 &#45; to gain from its own comparative advantage. Simplifications of this seminal theory exist. However, even in the simplest 2-2-1 case computations become exigent when manipulated by hand to explore different scenarios of production and trade. Hence, students frequently skip this effort. This paper presents an Excel&#174;-based computational framework to quickly locate optimal production in Ricardian trade.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 34-51
Issue: 1
Volume: 44
Year: 2023
Keywords: comparative advantage; factor of production; free trade; linear programming; international trade; optimisation; Ricardo's principle of trade.
File-URL: http://www.inderscience.com/link.php?id=130918
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:1:p:34-51

Template-Type: ReDIF-Article 1.0
Author-Name: André Luis Korzenowski
Author-X-Name-First: André Luis
Author-X-Name-Last: Korzenowski
Author-Name: Felipe Kirsch Hoerbe
Author-X-Name-First: Felipe Kirsch
Author-X-Name-Last: Hoerbe
Author-Name: Taciana Mareth
Author-X-Name-First: Taciana
Author-X-Name-Last: Mareth
Author-Name: Lucas Schmidt Goecks
Author-X-Name-First: Lucas Schmidt
Author-X-Name-Last: Goecks
Title: Use of heuristic methods for the optimisation of truck loading in a steel company
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 75-95
Issue: 1
Volume: 44
Year: 2023
Keywords: operational research; three-dimensional; container loading problem; CLP; steel industry.
File-URL: http://www.inderscience.com/link.php?id=130919
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:1:p:75-95

Template-Type: ReDIF-Article 1.0
Author-Name: S. Radha
Author-X-Name-First: S.
Author-X-Name-Last: Radha
Author-Name: S. Maragathasundari
Author-X-Name-First: S.
Author-X-Name-Last: Maragathasundari
Author-Name: P. Manikandan
Author-X-Name-First: P.
Author-X-Name-Last: Manikandan
Title: Asymptotic analysis of a Bernoulli vacation non-Markovian queuing system in air traffic control system
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 532-558
Issue: 4
Volume: 44
Year: 2023
Keywords: setup time; service interruption; repair process; restricted admissibility; Bernoulli schedule; reneging; supplementary variable technique.
File-URL: http://www.inderscience.com/link.php?id=132714
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:4:p:532-558

Template-Type: ReDIF-Article 1.0
Author-Name: Biswajit Mohapatra
Author-X-Name-First: Biswajit
Author-X-Name-Last: Mohapatra
Author-Name: Aneesh Kuruvilla
Author-X-Name-First: Aneesh
Author-X-Name-Last: Kuruvilla
Author-Name: Deepak Singhal
Author-X-Name-First: Deepak
Author-X-Name-Last: Singhal
Author-Name: Sushanta Tripathy
Author-X-Name-First: Sushanta
Author-X-Name-Last: Tripathy
Title: Sustainability in Indian manufacturing sector: an empirical study on challenges
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 281-300
Issue: 3
Volume: 43
Year: 2023
Keywords: sustainability; challenges; structural equation modelling; SEM; manufacturing.
File-URL: http://www.inderscience.com/link.php?id=129133
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:3:p:281-300

Template-Type: ReDIF-Article 1.0
Author-Name: Hui Zhang
Author-X-Name-First: Hui
Author-X-Name-Last: Zhang
Author-Name: Biao Yan
Author-X-Name-First: Biao
Author-X-Name-Last: Yan
Author-Name: Liling Xia
Author-X-Name-First: Liling
Author-X-Name-Last: Xia
Author-Name: Qiucheng Wang
Author-X-Name-First: Qiucheng
Author-X-Name-Last: Wang
Title: An assembly process simulation method in immersive virtual reality environment
Abstract:
In a virtual assembly process simulation, it 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. 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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 384-406
Issue: 3
Volume: 43
Year: 2023
Keywords: virtual assembly; virtual environment; force feedback; heuristic analysis method; constraint effect.
File-URL: http://www.inderscience.com/link.php?id=129134
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:3:p:384-406

Template-Type: ReDIF-Article 1.0
Author-Name: Mohammadjavad Nasiri Jahroudi
Author-X-Name-First: Mohammadjavad Nasiri
Author-X-Name-Last: Jahroudi
Author-Name: Mehdi Nani
Author-X-Name-First: Mehdi
Author-X-Name-Last: Nani
Author-Name: Ebrahim Safa
Author-X-Name-First: Ebrahim
Author-X-Name-Last: Safa
Author-Name: Ehsan Sadeh
Author-X-Name-First: Ehsan
Author-X-Name-Last: Sadeh
Title: Identification and generalisability of key causes of challenges in the implementation of IPD contract in construction projects with the perspective of Iran road construction projects
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 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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 407-433
Issue: 3
Volume: 43
Year: 2023
Keywords: generalisability; correlation; causes of challenge; IPD principles; statistical tests.
File-URL: http://www.inderscience.com/link.php?id=129135
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:3:p:407-433

Template-Type: ReDIF-Article 1.0
Author-Name: Xiao Yu
Author-X-Name-First: Xiao
Author-X-Name-Last: Yu
Author-Name: Armagan Bayram
Author-X-Name-First: Armagan
Author-X-Name-Last: Bayram
Title: Optimising patient revisit intervals for virtual and office appointments in chronic care
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 363-383
Issue: 3
Volume: 43
Year: 2023
Keywords: virtual appointments; revisit intervals; chronic care; migration network model.
File-URL: http://www.inderscience.com/link.php?id=129136
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:3:p:363-383

Template-Type: ReDIF-Article 1.0
Author-Name: Angassu Girma Mullisa
Author-X-Name-First: Angassu Girma
Author-X-Name-Last: Mullisa
Author-Name: Walid Abdul-Kader
Author-X-Name-First: Walid
Author-X-Name-Last: Abdul-Kader
Title: Performance improvement: a lean manufacturing case of metal tools factory
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 475-498
Issue: 4
Volume: 44
Year: 2023
Keywords: value stream mapping; lean manufacturing; discrete event simulation; production performances.
File-URL: http://www.inderscience.com/link.php?id=132721
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:4:p:475-498

Template-Type: ReDIF-Article 1.0
Author-Name: Changhong Zhu
Author-X-Name-First: Changhong
Author-X-Name-Last: Zhu
Author-Name: Tianci Pan
Author-X-Name-First: Tianci
Author-X-Name-Last: Pan
Title: Research on the cross-platform information transmission method of industrial internet of things based on XML technology
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 317-330
Issue: 3
Volume: 43
Year: 2023
Keywords: XML technology; industrial internet; SUM function; cross-platform transmission; distribution probability.
File-URL: http://www.inderscience.com/link.php?id=129137
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:3:p:317-330

Template-Type: ReDIF-Article 1.0
Author-Name: Mohammad Yavari
Author-X-Name-First: Mohammad
Author-X-Name-Last: Yavari
Author-Name: Amir Hosein Akbari
Author-X-Name-First: Amir Hosein
Author-X-Name-Last: Akbari
Title: Service level and profit maximisation in order acceptance and scheduling problem with weighted tardiness
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 331-362
Issue: 3
Volume: 43
Year: 2023
Keywords: order acceptance and scheduling; OAS; service level; simulated annealing-based heuristic; mixed-integer linear programming; MILP; goal programming; bi-objective; lower bound.
File-URL: http://www.inderscience.com/link.php?id=129138
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:3:p:331-362

Template-Type: ReDIF-Article 1.0
Author-Name: Zhenhua Wei
Author-X-Name-First: Zhenhua
Author-X-Name-Last: Wei
Title: Automatic error calibration system for English semantic translation based on machine learning
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. Then, English semantic translation decision function is obtained by constructing semantic ontology model, while English semantic translation error automatic calibration algorithm is realised by machine learning algorithm. Finally, the overall architecture and network topology of the system is designed, and the design of automatic proofreading system of English semantic translation errors is completed. 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%.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 301-316
Issue: 3
Volume: 43
Year: 2023
Keywords: dimensionless treatment; calibration algorithm; high CPU utilisation; low translation accuracy; high calibration time-consuming; machine learning; translation decision function.
File-URL: http://www.inderscience.com/link.php?id=129141
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:3:p:301-316

Template-Type: ReDIF-Article 1.0
Author-Name: Reza Yazdani
Author-X-Name-First: Reza
Author-X-Name-Last: Yazdani
Author-Name: Mirpouya Mirmozaffari
Author-X-Name-First: Mirpouya
Author-X-Name-Last: Mirmozaffari
Author-Name: Elham Shadkam
Author-X-Name-First: Elham
Author-X-Name-Last: Shadkam
Author-Name: Seyed Mohammad Khalili
Author-X-Name-First: Seyed Mohammad
Author-X-Name-Last: Khalili
Title: A lion optimisation algorithm for a two-agent single-machine scheduling with periodic maintenance to minimise the sum of maximum earliness and tardiness
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 515-531
Issue: 4
Volume: 44
Year: 2023
Keywords: lion optimisation algorithm; LOA; multi-agent; maintenance; single machine; metaheuristic; grasshopper optimisation algorithm; GOA; sine cosine algorithm; SCA; Salp swarm algorithm; SSA.
File-URL: http://www.inderscience.com/link.php?id=132730
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:4:p:515-531

Template-Type: ReDIF-Article 1.0
Author-Name: Vipulesh Shardeo
Author-X-Name-First: Vipulesh
Author-X-Name-Last: Shardeo
Author-Name: Anchal Patil
Author-X-Name-First: Anchal
Author-X-Name-Last: Patil
Author-Name: Ashish Dwivedi
Author-X-Name-First: Ashish
Author-X-Name-Last: Dwivedi
Author-Name: Jitender Madaan
Author-X-Name-First: Jitender
Author-X-Name-Last: Madaan
Title: Modelling of critical success factors for blockchain technology adoption readiness in the context of agri-food supply chain
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 consumer's 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 study's findings will assist policymakers, managers, and practitioners in strategising the decision-making process while BCT dissemination.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 80-102
Issue: 1
Volume: 43
Year: 2023
Keywords: blockchain technology; agri-food supply chain; AFSC; fuzzy; best-worst method; BWM; trust.
File-URL: http://www.inderscience.com/link.php?id=128398
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:1:p:80-102

Template-Type: ReDIF-Article 1.0
Author-Name: Shahla Jahangiri
Author-X-Name-First: Shahla
Author-X-Name-Last: Jahangiri
Author-Name: Milad Abolghasemian
Author-X-Name-First: Milad
Author-X-Name-Last: Abolghasemian
Author-Name: Peiman Ghasemi
Author-X-Name-First: Peiman
Author-X-Name-Last: Ghasemi
Author-Name: Adel Pourghader Chobar
Author-X-Name-First: Adel Pourghader
Author-X-Name-Last: Chobar
Title: Simulation-based optimisation: analysis of the emergency department resources under COVID-19 conditions
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 1-19
Issue: 1
Volume: 43
Year: 2023
Keywords: emergency department; simulation-based optimisation; S-BO; meta-model; COVID-19.
File-URL: http://www.inderscience.com/link.php?id=128399
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:1:p:1-19

Template-Type: ReDIF-Article 1.0
Author-Name: Elham Shadkam
Author-X-Name-First: Elham
Author-X-Name-Last: Shadkam
Title: A new hybrid method for optimising multi-surface problems: DSM method (power plants of Iran)
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 115-136
Issue: 1
Volume: 43
Year: 2023
Keywords: data envelopment analysis; DEA; response surface method; RSM; efficiency; optimisation; power plant.
File-URL: http://www.inderscience.com/link.php?id=128400
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:1:p:115-136

Template-Type: ReDIF-Article 1.0
Author-Name: Shan Hu
Author-X-Name-First: Shan
Author-X-Name-Last: Hu
Author-Name: Qi Jia
Author-X-Name-First: Qi
Author-X-Name-Last: Jia
Author-Name: Yuqing Wang
Author-X-Name-First: Yuqing
Author-X-Name-Last: Wang
Author-Name: Kaijie Fu
Author-X-Name-First: Kaijie
Author-X-Name-Last: Fu
Author-Name: Liyan Zhang
Author-X-Name-First: Liyan
Author-X-Name-Last: Zhang
Author-Name: Min Guo
Author-X-Name-First: Min
Author-X-Name-Last: Guo
Author-Name: Weiqi Guo
Author-X-Name-First: Weiqi
Author-X-Name-Last: Guo
Title: A case study on the design and implementation of a new product for infants learning to walk
Abstract:
In order to solve the problem of poor user experience and low satisfaction of infants and parents caused by insufficient research into existing products for toddlers, a design is proposed. Based on the design and development process, this research takes pre-existing dual user research as its core and uses literature research, 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 in actively learning 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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 1-28
Issue: 1
Volume: 45
Year: 2023
Keywords: infant; toddler; product design; user research.
File-URL: http://www.inderscience.com/link.php?id=133522
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Handle: RePEc:ids:ijisen:v:45:y:2023:i:1:p:1-28

Template-Type: ReDIF-Article 1.0
Author-Name: Eduardo Pérez
Author-X-Name-First: Eduardo
Author-X-Name-Last: Pérez
Author-Name: Mahima Sajan Varghese
Author-X-Name-First: Mahima Sajan
Author-X-Name-Last: Varghese
Author-Name: Amy Louise Schwarz
Author-X-Name-First: Amy Louise
Author-X-Name-Last: Schwarz
Title: A decision support system for selecting augmentative and alternative communication devices
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 59-79
Issue: 1
Volume: 43
Year: 2023
Keywords: decision making; augmented and alternative communication; AAC; healthcare; medical devices.
File-URL: http://www.inderscience.com/link.php?id=128402
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:1:p:59-79

Template-Type: ReDIF-Article 1.0
Author-Name: Javad Gholami
Author-X-Name-First: Javad
Author-X-Name-Last: Gholami
Author-Name: Ahmad Razavi
Author-X-Name-First: Ahmad
Author-X-Name-Last: Razavi
Author-Name: Hadi Gholami
Author-X-Name-First: Hadi
Author-X-Name-Last: Gholami
Author-Name: Alireza Moini
Author-X-Name-First: Alireza
Author-X-Name-Last: Moini
Title: Facility maintenance scheduling for organisations with a multi-location structure: optimisation model and hybrid metaheuristic approach
Abstract:
In comparison to centralised organisations with a single location structure, multi-location organisations face more challenges in the management of maintenance scheduling. In this paper, we present a new mathematical model to solve the maintenance scheduling problem for a multi-location facility, then we develop a hybrid metaheuristic algorithm combining the genetic algorithm (GA) and particle swarm optimisations (PSO) mechanisms, called GA-PSO. Employing the introduced model and the proposed solution approach, any multi-location organisation may be able to determine the best or near to optimal maintenance scheduling. The proposed model considers different work skills required for the maintenance scheduling and also the possibility of outsourcing the maintenance tasks. To demonstrate the applicability of the proposed model and algorithm, numerical analysis is employed. Numerical experiments indicate the accuracy and computational efficiency of the proposed solution approach.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 96-117
Issue: 1
Volume: 44
Year: 2023
Keywords: facility management; maintenance scheduling; genetic algorithm; particle swarm optimisations; cost.
File-URL: http://www.inderscience.com/link.php?id=130962
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:1:p:96-117

Template-Type: ReDIF-Article 1.0
Author-Name: M. Mathirajan
Author-X-Name-First: M.
Author-X-Name-Last: Mathirajan
Author-Name: Reddy Sujan
Author-X-Name-First: Reddy
Author-X-Name-Last: Sujan
Author-Name: M. Vimala Rani
Author-X-Name-First: M. Vimala
Author-X-Name-Last: Rani
Author-Name: Pujara Dhaval
Author-X-Name-First: Pujara
Author-X-Name-Last: Dhaval
Title: A machine learning algorithm for scheduling a burn-in oven problem
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 20-58
Issue: 1
Volume: 43
Year: 2023
Keywords: dispatching rules; semiconductor manufacturing; greedy heuristic algorithm; GHA; artificial neural network; ANN; optimal solution; estimated optimal solution; dispatching rule-based greedy heuristic algorithm; DR-GHA; hybrid neural network; HNN.
File-URL: http://www.inderscience.com/link.php?id=128403
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Template-Type: ReDIF-Article 1.0
Author-Name: Fadoua Tamtam
Author-X-Name-First: Fadoua
Author-X-Name-Last: Tamtam
Author-Name: Amina Tourabi
Author-X-Name-First: Amina
Author-X-Name-Last: Tourabi
Title: An integrated fuzzy QFD approach to leagile supply chain assessment during the COVID-19 crisis
Abstract:
The COVID-19 crisis has severely disrupted Moroccan automotive production. This pandemic has weakened the 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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 29-39
Issue: 1
Volume: 45
Year: 2023
Keywords: supply chain leagility; automotive industry; fuzzy quality function deployment; FQFD; leagile drivers; leagile capabilities; leagile enablers.
File-URL: http://www.inderscience.com/link.php?id=133524
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Handle: RePEc:ids:ijisen:v:45:y:2023:i:1:p:29-39

Template-Type: ReDIF-Article 1.0
Author-Name: Huilin Liu
Author-X-Name-First: Huilin
Author-X-Name-Last: Liu
Author-Name: Yadi Duan
Author-X-Name-First: Yadi
Author-X-Name-Last: Duan
Title: Production and construction quality management system of prefabricated buildings based on BIM technology
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 103-114
Issue: 1
Volume: 43
Year: 2023
Keywords: BIM technology; prefabricated building; production and construction; quality management; big data; resource scheduling.
File-URL: http://www.inderscience.com/link.php?id=128404
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:1:p:103-114

Template-Type: ReDIF-Article 1.0
Author-Name: Glaubos Clímaco
Author-X-Name-First: Glaubos
Author-X-Name-Last: Clímaco
Author-Name: Luidi Simonetti
Author-X-Name-First: Luidi
Author-X-Name-Last: Simonetti
Author-Name: Isabel Rosseti
Author-X-Name-First: Isabel
Author-X-Name-Last: Rosseti
Author-Name: Pedro Henrique González
Author-X-Name-First: Pedro Henrique
Author-X-Name-Last: González
Title: New approaches for the prize-collecting covering tour problem
Abstract:
In this paper, we consider the prize-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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 101-134
Issue: 1
Volume: 45
Year: 2023
Keywords: prize-collecting covering tour problem; PCCTP; greedy randomised adaptive search procedure; GRASP; random variable neighbourhood descent; RVND; hybrid heuristic; reduction rules.
File-URL: http://www.inderscience.com/link.php?id=133526
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Handle: RePEc:ids:ijisen:v:45:y:2023:i:1:p:101-134

Template-Type: ReDIF-Article 1.0
Author-Name: Mohammad Zakaraia
Author-X-Name-First: Mohammad
Author-X-Name-Last: Zakaraia
Author-Name: Hegazy Zaher
Author-X-Name-First: Hegazy
Author-X-Name-Last: Zaher
Author-Name: Naglaa Ragaa
Author-X-Name-First: Naglaa
Author-X-Name-Last: Ragaa
Title: An artificial immune system algorithm for solving the stochastic multi-manned assembly line balancing problem
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 68-88
Issue: 1
Volume: 45
Year: 2023
Keywords: MALBP; chance-constrained programming; artificial immune system; AIS; Taguchi orthogonal arrays; analysis of variance; ANOVA; Tukey's HSD test.
File-URL: http://www.inderscience.com/link.php?id=133527
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Handle: RePEc:ids:ijisen:v:45:y:2023:i:1:p:68-88

Template-Type: ReDIF-Article 1.0
Author-Name: Enas Ahmed Zaky
Author-X-Name-First: Enas Ahmed
Author-X-Name-Last: Zaky
Author-Name: Tamer F. Abdelmaguid
Author-X-Name-First: Tamer F.
Author-X-Name-Last: Abdelmaguid
Author-Name: Tamer A. Mohamed
Author-X-Name-First: Tamer A.
Author-X-Name-Last: Mohamed
Author-Name: Sayed Tahaa Mohamed
Author-X-Name-First: Sayed Tahaa
Author-X-Name-Last: Mohamed
Title: Lot streaming of hybrid flowshops with variable lot sizes and eligible machines
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 analysed 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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 238-264
Issue: 2
Volume: 43
Year: 2023
Keywords: hybrid flowshop; HFS; sublots; make-span; mixed-integer nonlinear programming; eligible machines.
File-URL: http://www.inderscience.com/link.php?id=128663
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:2:p:238-264

Template-Type: ReDIF-Article 1.0
Author-Name: Yuxiang Yang
Author-X-Name-First: Yuxiang
Author-X-Name-Last: Yang
Author-Name: Ying Xie
Author-X-Name-First: Ying
Author-X-Name-Last: Xie
Title: An evolutionary game model for low-carbon technology adoption by rival manufacturers
Abstract:
Manufacturers' decisions on adopting low carbon technology are influenced by many factors, including the consumers' awareness of low-carbon technology and the 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, authorities should enact the carbon tax within appropriate range in order to reduce carbon emissions.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 40-67
Issue: 1
Volume: 45
Year: 2023
Keywords: low carbon technology; evolutionary game; low carbon awareness; carbon tax.
File-URL: http://www.inderscience.com/link.php?id=133528
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Handle: RePEc:ids:ijisen:v:45:y:2023:i:1:p:40-67

Template-Type: ReDIF-Article 1.0
Author-Name: Chuan Chen
Author-X-Name-First: Chuan
Author-X-Name-Last: Chen
Author-Name: Wujiu Pan
Author-X-Name-First: Wujiu
Author-X-Name-Last: Pan
Author-Name: Hanbing Zhang
Author-X-Name-First: Hanbing
Author-X-Name-Last: Zhang
Title: Effect of mesh phasing on dynamic response of rotate vector reducer
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 190-209
Issue: 2
Volume: 43
Year: 2023
Keywords: RV reducer; dynamic response; mesh phasing; influence factor.
File-URL: http://www.inderscience.com/link.php?id=128664
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:2:p:190-209

Template-Type: ReDIF-Article 1.0
Author-Name: Simin Tohidnia
Author-X-Name-First: Simin
Author-X-Name-Last: Tohidnia
Author-Name: Ghasem Tohidi
Author-X-Name-First: Ghasem
Author-X-Name-Last: Tohidi
Title: A prospect secondary goal model for ranking DMUs in DEA-R
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 153-167
Issue: 2
Volume: 43
Year: 2023
Keywords: data envelopment analysis; DEA; DEA-R; secondary goal model; prospect theory; cross-efficiency.
File-URL: http://www.inderscience.com/link.php?id=128665
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:2:p:153-167

Template-Type: ReDIF-Article 1.0
Author-Name: Asmaa Motrani
Author-X-Name-First: Asmaa
Author-X-Name-Last: Motrani
Author-Name: Rachid Noureddine
Author-X-Name-First: Rachid
Author-X-Name-Last: Noureddine
Title: Data-driven prognostic framework for remaining useful life prediction
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 210-221
Issue: 2
Volume: 43
Year: 2023
Keywords: prognostic and health management; PHM; data-driven prognostic; sparse Bayesian learning; SBL; relevance vector machine; RVM; sparse Bayesian interpolation; SBI; remaining useful life; RUL.
File-URL: http://www.inderscience.com/link.php?id=128666
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:2:p:210-221

Template-Type: ReDIF-Article 1.0
Author-Name: Qian Xu
Author-X-Name-First: Qian
Author-X-Name-Last: Xu
Author-Name: Jun-ting Lin
Author-X-Name-First: Jun-ting
Author-X-Name-Last: Lin
Title: Safety requirement verification of train-centric CBTC by integrating STPA with coloured Petri net
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 168-189
Issue: 2
Volume: 43
Year: 2023
Keywords: train-centric CBTC; system-theoretic process analysis; STPA; coloured Petri net; CPN; safety requirements verification; unsafe control actions.
File-URL: http://www.inderscience.com/link.php?id=128667
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:2:p:168-189

Template-Type: ReDIF-Article 1.0
Author-Name: Wenyuan Chen
Author-X-Name-First: Wenyuan
Author-X-Name-Last: Chen
Title: An enterprise financial data risk prediction model based on entropy weight method
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. The enterprise risk financial data prediction index system is built and the prediction index is obtained. The entropy weight method is used to calculate the weight of prediction index and to 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%.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 89-100
Issue: 1
Volume: 45
Year: 2023
Keywords: entropy method; enterprise financial risk; index system; weight; predictive model.
File-URL: http://www.inderscience.com/link.php?id=133533
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Handle: RePEc:ids:ijisen:v:45:y:2023:i:1:p:89-100

Template-Type: ReDIF-Article 1.0
Author-Name: Leena Ghrayeb
Author-X-Name-First: Leena
Author-X-Name-Last: Ghrayeb
Author-Name: Purushothaman Damodaran
Author-X-Name-First: Purushothaman
Author-X-Name-Last: Damodaran
Title: Minimising makespan of a batch processing machine with unequal job ready times using simulated annealing
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 222-237
Issue: 2
Volume: 43
Year: 2023
Keywords: scheduling; batch processing machine; BPM; makespan; simulated annealing.
File-URL: http://www.inderscience.com/link.php?id=128670
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:2:p:222-237

Template-Type: ReDIF-Article 1.0
Author-Name: Rong Tang
Author-X-Name-First: Rong
Author-X-Name-Last: Tang
Author-Name: Guoxiong Zhang
Author-X-Name-First: Guoxiong
Author-X-Name-Last: Zhang
Author-Name: Yunxia Li
Author-X-Name-First: Yunxia
Author-X-Name-Last: Li
Title: Prediction of uncertainty risk factors in engineering management system based on improved decision tree
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 285-301
Issue: 3
Volume: 44
Year: 2023
Keywords: engineering management system; uncertainty; risk factors; improved decision tree; fuzzy clustering; prediction.
File-URL: http://www.inderscience.com/link.php?id=132259
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:3:p:285-301

Template-Type: ReDIF-Article 1.0
Author-Name: Xiaohong Zhu
Author-X-Name-First: Xiaohong
Author-X-Name-Last: Zhu
Title: Study on regional digital teaching resource sharing platform based on internet of things and big data
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. The least square algorithm to construct the operation and maintenance elastic model is introduced, and the dual residual and the original residual of the model output data are calculated. 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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 458-474
Issue: 4
Volume: 44
Year: 2023
Keywords: internet of things; big data; ADMM algorithm; operation and maintenance elasticity; dual function; Lagrange function.
File-URL: http://www.inderscience.com/link.php?id=132771
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:4:p:458-474

Template-Type: ReDIF-Article 1.0
Author-Name: Chen Qun Wu
Author-X-Name-First: Chen Qun
Author-X-Name-Last: Wu
Title: Design of intelligent system for indoor illumination adjustment based on deep learning
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 and 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%.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 137-152
Issue: 2
Volume: 43
Year: 2023
Keywords: deep learning; indoor illumination; illumination adjustment; illumination model.
File-URL: http://www.inderscience.com/link.php?id=128676
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:2:p:137-152

Template-Type: ReDIF-Article 1.0
Author-Name: Arash Ashjaee
Author-X-Name-First: Arash
Author-X-Name-Last: Ashjaee
Author-Name: Mohammadali Pirayesh
Author-X-Name-First: Mohammadali
Author-X-Name-Last: Pirayesh
Author-Name: Farzad Dehghanian
Author-X-Name-First: Farzad
Author-X-Name-Last: Dehghanian
Title: Inventory management of manufacturers with yield uncertainty and lateral transshipment
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 351-368
Issue: 3
Volume: 44
Year: 2023
Keywords: inventory management; yield uncertainty; lateral transshipment.
File-URL: http://www.inderscience.com/link.php?id=132261
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:3:p:351-368

Template-Type: ReDIF-Article 1.0
Author-Name: Shu Xue
Author-X-Name-First: Shu
Author-X-Name-Last: Xue
Author-Name: Simin Wei
Author-X-Name-First: Simin
Author-X-Name-Last: Wei
Title: Cross-domain management system of real estate sales information based on blockchain
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 with real estate sales information access cross-domain authentication and 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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 265-280
Issue: 2
Volume: 43
Year: 2023
Keywords: blockchain technology; real estate sales; information cross-domain; management system.
File-URL: http://www.inderscience.com/link.php?id=128677
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:2:p:265-280

Template-Type: ReDIF-Article 1.0
Author-Name: Wenyuan Chen
Author-X-Name-First: Wenyuan
Author-X-Name-Last: Chen
Title: Risk warning method of computerised accounting information distortion based on deep integration model
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 391-403
Issue: 3
Volume: 44
Year: 2023
Keywords: computerised accounting information; index quantification; distortion risk identification; risk warning; deep integration model.
File-URL: http://www.inderscience.com/link.php?id=132263
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:3:p:391-403

Template-Type: ReDIF-Article 1.0
Author-Name: Jiaxuan Chen
Author-X-Name-First: Jiaxuan
Author-X-Name-Last: Chen
Title: Copper futures hedging based on Markov switching approach
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 316-335
Issue: 3
Volume: 44
Year: 2023
Keywords: dynamic futures hedging; Markov regime-switching model; DCC-GARCH.
File-URL: http://www.inderscience.com/link.php?id=132264
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:3:p:316-335

Template-Type: ReDIF-Article 1.0
Author-Name: Samson Akindele
Author-X-Name-First: Samson
Author-X-Name-Last: Akindele
Author-Name: Olusegun Akanbi
Author-X-Name-First: Olusegun
Author-X-Name-Last: Akanbi
Author-Name: Feyisayo Akinwande
Author-X-Name-First: Feyisayo
Author-X-Name-Last: Akinwande
Author-Name: Joshua Ade-Omowaye
Author-X-Name-First: Joshua
Author-X-Name-Last: Ade-Omowaye
Title: A study on work-related musculoskeletal complaints and associated risk factors among steel industrial workers
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 404-426
Issue: 3
Volume: 44
Year: 2023
Keywords: posture; casting; productivity; rapid upper limb assessment; RULA; musculoskeletal complaints; discomfort; safety; steel industry.
File-URL: http://www.inderscience.com/link.php?id=132266
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:3:p:404-426

Template-Type: ReDIF-Article 1.0
Author-Name: Youwei Chu
Author-X-Name-First: Youwei
Author-X-Name-Last: Chu
Title: A fast encryption method of large enterprise financial data based on adversarial neural network
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 enterprises, this paper proposes a fast encryption method of financial data of large enterprises based on adversarial neural network. Adversarial neural network is used to build the financial data reorganisation model of large enterprises, and obtain the sparse and local characteristics of the reorganised financial data of large enterprises, so as to generate the encrypted initial key and sub-key, and complete the fast encryption of the financial data of large enterprises 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 enterprises.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 302-315
Issue: 3
Volume: 44
Year: 2023
Keywords: adversarial neural network; data encryption; enterprise financial data.
File-URL: http://www.inderscience.com/link.php?id=132269
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:3:p:302-315

Template-Type: ReDIF-Article 1.0
Author-Name: Lili Wang
Author-X-Name-First: Lili
Author-X-Name-Last: Wang
Title: Judgement method of enterprise financial data abnormality based on high-order dynamic Bayesian network
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 a higher accuracy rate of anomaly judgement, and a lower miss rate and error rate.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 369-379
Issue: 3
Volume: 44
Year: 2023
Keywords: high-order dynamic Bayesian network; financial data; network modification; chromosome coding; data classification.
File-URL: http://www.inderscience.com/link.php?id=132270
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:3:p:369-379

Template-Type: ReDIF-Article 1.0
Author-Name: Linlin Zhou
Author-X-Name-First: Linlin
Author-X-Name-Last: Zhou
Title: A clustering method of marketing effective data based on relation matrix fusion
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 380-390
Issue: 3
Volume: 44
Year: 2023
Keywords: marketing data; valid data; relation matrix fusion; EMD distance; data clustering; Earth mover's distance.
File-URL: http://www.inderscience.com/link.php?id=132271
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:3:p:380-390

Template-Type: ReDIF-Article 1.0
Author-Name: Mahmoud A. El-Sharief
Author-X-Name-First: Mahmoud A.
Author-X-Name-Last: El-Sharief
Author-Name: Omar Salah
Author-X-Name-First: Omar
Author-X-Name-Last: Salah
Author-Name: Mahmoud Heshmat
Author-X-Name-First: Mahmoud
Author-X-Name-Last: Heshmat
Title: ANFIS and regression-based ANOVA for attribute and variable prediction: a case of quality characteristics in the cement bags industry
Abstract:
Efficient models are significant to manufacturing systems for the purpose of prediction and performance evaluation. Traditionally, regression models have been widely held for this purpose; recently, soft computing models are widely used. Efficiency of soft computing models depends on the size of the problem dataset. In this paper, we conduct a regression-based ANOVA study and ANFIS for cement bags production. Quality characteristics of bag dimensions are considered. The results show that ANFIS can predict attributes and variables of production lines more than regression-based ANOVA.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 336-350
Issue: 3
Volume: 44
Year: 2023
Keywords: ANFIS; ANOVA; regression; manufacturing systems.
File-URL: http://www.inderscience.com/link.php?id=132283
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:3:p:336-350

Template-Type: ReDIF-Article 1.0
Author-Name: Sebastian Cáceres-Gelvez
Author-X-Name-First: Sebastian
Author-X-Name-Last: Cáceres-Gelvez
Author-Name: Martín Darío Arango-Serna
Author-X-Name-First: Martín Darío
Author-X-Name-Last: Arango-Serna
Author-Name: Julián Andrés Zapata-Cortés
Author-X-Name-First: Julián Andrés
Author-X-Name-Last: Zapata-Cortés
Title: Integrated optimisation of the unequal-area facility layout and the flowshop group scheduling problems for a case of the garment industry
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 148-172
Issue: 2
Volume: 45
Year: 2023
Keywords: unequal-area facility layout; flowshop group scheduling; genetic algorithm; garment industry; integrated optimisation; case study.
File-URL: http://www.inderscience.com/link.php?id=134352
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Handle: RePEc:ids:ijisen:v:45:y:2023:i:2:p:148-172

Template-Type: ReDIF-Article 1.0
Author-Name: Soumyanath Chatterjee
Author-X-Name-First: Soumyanath
Author-X-Name-Last: Chatterjee
Author-Name: R.P. Mohanty
Author-X-Name-First: R.P.
Author-X-Name-Last: Mohanty
Title: A bibliographic study of sustainability research: exploring multidimensionality
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 173-213
Issue: 2
Volume: 45
Year: 2023
Keywords: sustainability; systematic literature survey; text analytics; latent Dirichlet allocation; LDA; topic model; bibliographic analysis.
File-URL: http://www.inderscience.com/link.php?id=134353
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Handle: RePEc:ids:ijisen:v:45:y:2023:i:2:p:173-213

Template-Type: ReDIF-Article 1.0
Author-Name: Hong-Da Dou
Author-X-Name-First: Hong-Da
Author-X-Name-Last: Dou
Author-Name: Feng Wang
Author-X-Name-First: Feng
Author-X-Name-Last: Wang
Author-Name: He Pan
Author-X-Name-First: He
Author-X-Name-Last: Pan
Author-Name: Yi-Fan Wang
Author-X-Name-First: Yi-Fan
Author-X-Name-Last: Wang
Author-Name: Tsui-Ping Chung
Author-X-Name-First: Tsui-Ping
Author-X-Name-Last: Chung
Title: An aircraft position updating based algorithm for single runway scheduling with normal and alternate aircrafts
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 205-219
Issue: 2
Volume: 44
Year: 2023
Keywords: normal landing aircrafts; alternate landing aircrafts; single runway; fixed time window; safety interval; landing completion times.
File-URL: http://www.inderscience.com/link.php?id=131539
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:2:p:205-219

Template-Type: ReDIF-Article 1.0
Author-Name: Mudita Dixit
Author-X-Name-First: Mudita
Author-X-Name-Last: Dixit
Author-Name: Gopakumaran Thampi
Author-X-Name-First: Gopakumaran
Author-X-Name-Last: Thampi
Title: Investigating the challenges faced by Indian automotive industry for adopting technology organically
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&#36; 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 AI's 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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 258-284
Issue: 2
Volume: 44
Year: 2023
Keywords: advanced manufacturing technology; R&D; Indian automotive sector; latest technology adoption; original equipment manufacturer; OEM.
File-URL: http://www.inderscience.com/link.php?id=131540
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:2:p:258-284

Template-Type: ReDIF-Article 1.0
Author-Name: Forough Enayaty-Ahangar
Author-X-Name-First: Forough
Author-X-Name-Last: Enayaty-Ahangar
Author-Name: Behrooz Karimi
Author-X-Name-First: Behrooz
Author-X-Name-Last: Karimi
Author-Name: Negin Enayaty Ahangar
Author-X-Name-First: Negin Enayaty
Author-X-Name-Last: Ahangar
Author-Name: Alireza Sheikh Zadeh
Author-X-Name-First: Alireza Sheikh
Author-X-Name-Last: Zadeh
Title: An optimisation approach for multi-floor facility layout design using flexible bays
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 244-270
Issue: 2
Volume: 45
Year: 2023
Keywords: facility layout; optimisation; mixed-integer linear programming; metaheuristics; genetic algorithm.
File-URL: http://www.inderscience.com/link.php?id=134356
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Handle: RePEc:ids:ijisen:v:45:y:2023:i:2:p:244-270

Template-Type: ReDIF-Article 1.0
Author-Name: Andrew N. Forde
Author-X-Name-First: Andrew N.
Author-X-Name-Last: Forde
Author-Name: Mark S. Fox
Author-X-Name-First: Mark S.
Author-X-Name-Last: Fox
Title: An innovation ontology for idea forecasting and measurement
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 141-185
Issue: 2
Volume: 44
Year: 2023
Keywords: innovation management; ontology; semantic web; open innovation; radicalness; incrementalness; innovation properties; innovation categories; knightian uncertainty; classification; utility.
File-URL: http://www.inderscience.com/link.php?id=131541
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:2:p:141-185

Template-Type: ReDIF-Article 1.0
Author-Name: Awais Sayeed Kazi
Author-X-Name-First: Awais Sayeed
Author-X-Name-Last: Kazi
Author-Name: Nikhil R. Shinde
Author-X-Name-First: Nikhil R.
Author-X-Name-Last: Shinde
Author-Name: Sumeet S. Mujumdar
Author-X-Name-First: Sumeet S.
Author-X-Name-Last: Mujumdar
Author-Name: Tejas Gajanan Kulkarni
Author-X-Name-First: Tejas Gajanan
Author-X-Name-Last: Kulkarni
Author-Name: Prathamesh R. Potdar
Author-X-Name-First: Prathamesh R.
Author-X-Name-Last: Potdar
Title: IoT enabled smart window for controlling brightness: a perspective of heat transfer rate
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 29-30&#176;C and results shows saving in electricity by 11 watts/hour. This study concluded that low variation is observed in the indoor lumen and temperature conditions using the PDLC film. The movements of the PDLC crystals were controlled using mobile-based technology to make the film's operation feasible and accurate. A mobile application for managing the film is found highly viable and reliable to operate.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 220-257
Issue: 2
Volume: 44
Year: 2023
Keywords: polymer dispersed liquid crystal; PDLC; internet of things; IoT; smart window; heating; ventilation; and air conditioning; HVAC.
File-URL: http://www.inderscience.com/link.php?id=131543
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:2:p:220-257

Template-Type: ReDIF-Article 1.0
Author-Name: Virupaxi Bagodi
Author-X-Name-First: Virupaxi
Author-X-Name-Last: Bagodi
Author-Name: Biswajit Mahanty
Author-X-Name-First: Biswajit
Author-X-Name-Last: Mahanty
Title: Two-wheeler authorised service centre: a system dynamics study of 'limits to growth' archetype
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 464-490
Issue: 4
Volume: 43
Year: 2023
Keywords: limit to growth; service centre; two-wheelers; decision-making; India.
File-URL: http://www.inderscience.com/link.php?id=129751
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:4:p:464-490

Template-Type: ReDIF-Article 1.0
Author-Name: Thinandahva Thomas Munyai
Author-X-Name-First: Thinandahva Thomas
Author-X-Name-Last: Munyai
Author-Name: Michael Kweneojo O. Ayomoh
Author-X-Name-First: Michael Kweneojo O.
Author-X-Name-Last: Ayomoh
Author-Name: Olasumbo Ayodeji Makinde
Author-X-Name-First: Olasumbo Ayodeji
Author-X-Name-Last: Makinde
Author-Name: A. Edgar Nesamvuni
Author-X-Name-First: A. Edgar
Author-X-Name-Last: Nesamvuni
Author-Name: Boitumelo I. Ramatsetse
Author-X-Name-First: Boitumelo I.
Author-X-Name-Last: Ramatsetse
Title: Manufacturing management of productivity in the steel industry using system dynamics modelling and statistical evaluation
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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 491-528
Issue: 4
Volume: 43
Year: 2023
Keywords: productivity; system dynamics; steel manufacturing; manufacturing management; multiple regression analysis; MRA.
File-URL: http://www.inderscience.com/link.php?id=129752
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:4:p:491-528

Template-Type: ReDIF-Article 1.0
Author-Name: Mohammad Ebrahimi
Author-X-Name-First: Mohammad
Author-X-Name-Last: Ebrahimi
Author-Name: Arezoo Atighehchian
Author-X-Name-First: Arezoo
Author-X-Name-Last: Atighehchian
Title: Design of a mathematical model and a simulation-optimisation approach for master surgical scheduling considering uncertainty in length of stay, demands and duration of surgery
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%.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 435-463
Issue: 4
Volume: 43
Year: 2023
Keywords: master surgical scheduling; MSS; simulation-optimisation approach; mixed integer programming; uncertainty; robust optimisation.
File-URL: http://www.inderscience.com/link.php?id=129753
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:4:p:435-463

Template-Type: ReDIF-Article 1.0
Author-Name: Mohammad Hossein Vaghefzadeh
Author-X-Name-First: Mohammad Hossein
Author-X-Name-Last: Vaghefzadeh
Author-Name: Behrooz Karimi
Author-X-Name-First: Behrooz
Author-X-Name-Last: Karimi
Author-Name: Abbas Ahmadi
Author-X-Name-First: Abbas
Author-X-Name-Last: Ahmadi
Title: Modelling customer demand for mobile value-added services: non-stationary time series models or neural networks time series analysis?
Abstract:
The present research applies two different modelling 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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 555-581
Issue: 4
Volume: 43
Year: 2023
Keywords: time series; analysis; non-stationary; artificial neural network; mobile value-added; seasonal effect; demand; forecasting.
File-URL: http://www.inderscience.com/link.php?id=129754
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:4:p:555-581

Template-Type: ReDIF-Article 1.0
Author-Name: Padinharakam Lasin
Author-X-Name-First: Padinharakam
Author-X-Name-Last: Lasin
Author-Name: Vinay V. Panicker
Author-X-Name-First: Vinay V.
Author-X-Name-Last: Panicker
Author-Name: Francis J. Emmatty
Author-X-Name-First: Francis J.
Author-X-Name-Last: Emmatty
Title: Assessment of mental workload in a sorting task: a game-based approach
Abstract:
Human factors are ergonomics practise of designing tools and techniques for people within their physical and cognitive capabilities and limitations. As technology has improved during the last few decades, more research has been done on how to maximise the efficiency of human-machine interaction. The mental workload is one of the major psychological factors that affect the productivity of the worker. Mental workload describes the amount of mental effort needed to invest in executing a task. Most of the research work in modelling mental workload has mainly produced theory-driven models. This study aims to assess the influence of the factors on mental workload in a sorting task using a game-based approach. A simulation game-based approach is applied to a subjective assessment of mental workload in a sorting task. With the results obtained, analyses have been carried out based on age group, time window, gender, subject group, and colour.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 529-554
Issue: 4
Volume: 43
Year: 2023
Keywords: mental workload; MWL; subjective evaluation; game-based approach; sorting task.
File-URL: http://www.inderscience.com/link.php?id=129755
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Handle: RePEc:ids:ijisen:v:43:y:2023:i:4:p:529-554

Template-Type: ReDIF-Article 1.0
Author-Name: Xi Lun
Author-X-Name-First: Xi
Author-X-Name-Last: Lun
Author-Name: Xiangyang Zhang
Author-X-Name-First: Xiangyang
Author-X-Name-Last: Zhang
Author-Name: Yining Wang
Author-X-Name-First: Yining
Author-X-Name-Last: Wang
Author-Name: Tian Wang
Author-X-Name-First: Tian
Author-X-Name-Last: Wang
Title: Abnormal recognition of corporate financial data based on deep belief network
Abstract:
In view of the traditional enterprise financial data exception recognition methods, such as low recognition precision and long recognition time, a deep belief network is put forward. Based on the depth of the enterprise's financial data anomaly identification method, the distributed data collection method, selection of enterprise financial data mining, and correlation analysis are adopted, according to the financial data 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.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 135-147
Issue: 2
Volume: 45
Year: 2023
Keywords: deep belief network; corporate financial data; information entropy; data stream fragment.
File-URL: http://www.inderscience.com/link.php?id=134371
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Handle: RePEc:ids:ijisen:v:45:y:2023:i:2:p:135-147

Template-Type: ReDIF-Article 1.0
Author-Name: Dinesh Kumar Kushwaha
Author-X-Name-First: Dinesh Kumar
Author-X-Name-Last: Kushwaha
Author-Name: Dilbagh Panchal
Author-X-Name-First: Dilbagh
Author-X-Name-Last: Panchal
Author-Name: Anish Sachdeva
Author-X-Name-First: Anish
Author-X-Name-Last: Sachdeva
Title: An integrated framework based on intuitionistic fuzzy FMEA, COPRAS and TOPSIS for risk assessment in process industry
Abstract:
In this work, a novel intuitionistic fuzzy (IF) modelling-based failure mode and effect analysis (IF-FMEA) has been proposed for studying and analysing failure risk of sugarcane milling unit (SMU). The proposed novel IF-FMEA approach overcomes various disadvantages associated with already available FMEA approaches. IF hybrid weighted euclidean distance (IFHWED) score has been computed to rank all listed failure causes under three risk factors O, S and D. Failure causes namely unloader (UL2), main cane carrier (MC7), cane chopper and leveller (CC10), fibrizer (FB18), rake elevator (RE20), mill (MH22), juice pump and water spray system (JP32) with their corresponding IFHWED scores 1.1646, 1.0243, 0.7896, 1.0378, 1.0573, 1.0668 and 1.1060 were identified as the most critical failure causes resulting in sudden failure in plant operation. The performance of proposed novel IF-FMEA is evaluated by implementing IF-based COPRAS and TOPSIS. Sensitivity analysis has also been conducted to check stability of ranking results.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 214-243
Issue: 2
Volume: 45
Year: 2023
Keywords: IF-FMEA; IFWA operator; risk assessment; COPRAS; TOPSIS; sugar mill industry.
File-URL: http://www.inderscience.com/link.php?id=134376
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Handle: RePEc:ids:ijisen:v:45:y:2023:i:2:p:214-243

Template-Type: ReDIF-Article 1.0
Author-Name: Elvis Chiboyiwa
Author-X-Name-First: Elvis
Author-X-Name-Last: Chiboyiwa
Author-Name: France Ncube
Author-X-Name-First: France
Author-X-Name-Last: Ncube
Author-Name: Patience Erick
Author-X-Name-First: Patience
Author-X-Name-Last: Erick
Title: Implementation and evaluation of an ergonomic training program and stretch exercises among welders in the informal sector in three urban centres in Zimbabwe
Abstract:
This study assessed the effects of ergonomic training on postural risk and the effects of combined ergonomic training and stretch exercises on pain severity reported by welders in the informal sector of Zimbabwe. Supervised training and exercise sessions were conducted for a period of 11 weeks. Out of a total of 260 welders that were purposively selected and randomly assigned to four groups, 189 completed the intervention program. There was significant reduction of risk in the shoulder/arm, hand/wrist and neck (p &#61; 0.001) after the administration of ergonomic training. Non-significant reduction of risk was observed in the back (p &#61; 0.061). In the combined ergonomic training and stretch exercise group, there was a significant reduction in the severity of the reported pain in most body regions (p &#61; 0.001). There is need to implement a combination of intervention measures in order to substantially reduce the severity of pain among welders.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 186-204
Issue: 2
Volume: 44
Year: 2023
Keywords: administration; ergonomic; informal sector; intervention; pain severity; postural risk; program; training; stretch exercises; welders; Zimbabwe.
File-URL: http://www.inderscience.com/link.php?id=131574
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Handle: RePEc:ids:ijisen:v:44:y:2023:i:2:p:186-204