Template-Type: ReDIF-Article 1.0
Author-Name: Sourav Kumar Patra
Author-X-Name-First: Sourav Kumar
Author-X-Name-Last: Patra
Author-Name: Susanta Kumar Paikray
Author-X-Name-First: Susanta Kumar
Author-X-Name-Last: Paikray
Author-Name: Rudra Mohan Tripathy
Author-X-Name-First: Rudra Mohan
Author-X-Name-Last: Tripathy
Title: A retailer's inventory model for deteriorating items under power pattern demand with shortages partially backlogged in both crisp and fuzzy environments
Abstract:
An inventory predicament can be resolved with numerous techniques, starting from the trial-and-error manner of mathematical and simulation methods. Mathematical methods always serve as powerful tools for minimising total inventory costs. In this paper, we have considered a retailer's inventory problem in order to determine an optimal strategy that minimises the total inventory cost under various constraints. Here, the constraints include constant deterioration, power-pattern demand, permissible shortages, partial backlog, different inventory costs, and inherent imprecision of various expenses concerning the current scenario. Subsequently, we develop the mathematical model of the problem together with its solving policy in a crisp as well as fuzzy environments. Moreover, we provide several numerical illustrations to validate our findings. Finally, we present several managerial insights for inventory managers based on the sensitivity analysis of associated parameters.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 96-118
Issue: 1
Volume: 49
Year: 2025
Keywords: inventory optimisation; power demand; deterioration; partial backlogging; triangular fuzzy numbers; signed distance method.
File-URL: http://www.inderscience.com/link.php?id=144083
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Handle: RePEc:ids:ijisen:v:49:y:2025:i:1:p:96-118
Template-Type: ReDIF-Article 1.0
Author-Name: Marcos Vido
Author-X-Name-First: Marcos
Author-X-Name-Last: Vido
Author-Name: Athos Paulo Tadeu Pacchini
Author-X-Name-First: Athos Paulo Tadeu
Author-X-Name-Last: Pacchini
Title: A conceptual human safety system in an industrial shared workspace with a collaborative robot
Abstract:
By working side-by-side with humans in a production environment, collaborative robots (cobots) can be helpful and versatile and can efficiently support activities in modern factories. A review of the extant literature identified an opportunity to build user-friendly human-robot interfaces and confirmed the need to enhance the perceptions of human safety conditions and requirements during interactions with cobots when performing manufacturing tasks. Therefore, this study seeks to deepen the knowledge regarding the use of cobots, based on introducing novel safety system architecture for human-robot collaboration in a shared workspace. The degree of collaboration is investigated, focusing on the safety requirements when human operators perform tasks involving cooperation between humans and cobots in a combined workstation. As a result, this study extends the previous literature by proposing a conceptual safety system architecture that is especially useful for covering safety requirements during the design stage of a collaborative workstation so as to minimise safety risks to humans, resulting in a dynamic safety framework that allows for the use of advanced robotics in an Industry 4.0 environment.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 119-138
Issue: 1
Volume: 49
Year: 2025
Keywords: collaborative robot; safety; human-robot collaboration; HRC; cyber-physical systems; CPSs; Industry 4.0.
File-URL: http://www.inderscience.com/link.php?id=144084
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Handle: RePEc:ids:ijisen:v:49:y:2025:i:1:p:119-138
Template-Type: ReDIF-Article 1.0
Author-Name: Hanieh Shambayati
Author-X-Name-First: Hanieh
Author-X-Name-Last: Shambayati
Author-Name: Mohsen Shafiei Nikabadi
Author-X-Name-First: Mohsen Shafiei
Author-X-Name-Last: Nikabadi
Author-Name: Mohammad Rahmanimanesh
Author-X-Name-First: Mohammad
Author-X-Name-Last: Rahmanimanesh
Title: Customer satisfaction optimisation in a dynamic closed-loop supply chain under uncertainty
Abstract:
Optimising the management of the closed-loop supply chain (CLSC) has attracted considerable attention over the past few years. However, most researches in this area have only considered the cost and profit functions. In this research, the optimisation of multi-product CLSC considering customer satisfaction with dimensions such as quality, service level, lead time, and environmental pollution along with the profit function in different periods is considered. The uncertainty of demand in the form of grey numbers is considered. To optimise this NP-hard problem, a multi-objective meta-heuristic pareto-based enhanced firefly algorithm was used. The purpose of the proposed model is to determine the optimal production quantities of each product and finding the location of the warehouse at each stage and period in the CLSC. Finally, for the validity and analysis of the model, a numerical example has been considered.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 18-56
Issue: 1
Volume: 49
Year: 2025
Keywords: closed-loop supply chain; CLSC; customer satisfaction; optimisation; uncertainty; grey numbers; enhanced firefly algorithm.
File-URL: http://www.inderscience.com/link.php?id=144085
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Handle: RePEc:ids:ijisen:v:49:y:2025:i:1:p:18-56
Template-Type: ReDIF-Article 1.0
Author-Name: Bhanu Ganesh Lukka
Author-X-Name-First: Bhanu Ganesh
Author-X-Name-Last: Lukka
Author-Name: T. Rama Subba Reddy
Author-X-Name-First: T. Rama Subba
Author-X-Name-Last: Reddy
Author-Name: Mercy Rosalina Kotapuri
Author-X-Name-First: Mercy Rosalina
Author-X-Name-Last: Kotapuri
Title: UPQC with hybrid HBD-SWO optimisation for improving power quality in a grid-connected HRES system
Abstract:
In order to achieve the aim of supplying constant supply of power, renewable energy systems (RES), like solar, photovoltaic (PV), battery energy storage systems (BESS), and wind energy is researched. The main objective of this study is to provide a method for increasing power quality with hybrid access points to RES using optimal FOPID controller settings and UPQC. Non-linear system load and failure conditions seem to be the root of PQ issues with HRES. The UPQC uses series and shunt filtering methods to resolve the PQ issues with the aid of hybrid Honey Badger-salp swarm optimiser (HBD-SWO) method that inherits the qualities of SSA and HBA methods. The new technique involves fine-tuning the FOPID controllers' variables of the shunt and series devices of UPQC. The efficiency of the proposed method is compared with that of conventional methods to prove the efficacy of the proposed approach in PQ enhancement.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 57-95
Issue: 1
Volume: 49
Year: 2025
Keywords: renewable energy systems; RES; photovoltaics; battery energy management system; FOPID; UPQC.
File-URL: http://www.inderscience.com/link.php?id=144088
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Handle: RePEc:ids:ijisen:v:49:y:2025:i:1:p:57-95
Template-Type: ReDIF-Article 1.0
Author-Name: Ivan Gunawan
Author-X-Name-First: Ivan
Author-X-Name-Last: Gunawan
Author-Name: Lusia Permata Sari Hartanti
Author-X-Name-First: Lusia Permata Sari
Author-X-Name-Last: Hartanti
Author-Name: Bernadeth Theresia Novita Klau
Author-X-Name-First: Bernadeth Theresia Novita
Author-X-Name-Last: Klau
Author-Name: Nor Chofifah
Author-X-Name-First: Nor
Author-X-Name-Last: Chofifah
Title: Product mix optimisation model for the coconut oil industry
Abstract:
Coconut can produce numerous derivatives and by-products. A coconut oil industry with five production processes: expeller-pressing, refinery, extraction, hydrogenation, and pelletising can produce up to 11 products. A product mix problem often arises in the determination of the quantity of each product to be produced. As such, product mix decisions can significantly affect profit generation. This research aims to develop a mathematical model based on linear programming (LP) to maximise profits. The optimisation model developed in this study estimates that the industry can increase profits by 43.9% by applying the best product mix decision. A sensitivity analysis shows that changes in capacity affect the model. Three production flow scenarios were tested in the LP model. Scenario 1 (adding refinery 2, using it like refinery 1 plus using refinery 2 to produce refined bleached deodorised hydrogenised coconut oil super) can increase the industry's profit by 28%.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 1-17
Issue: 1
Volume: 49
Year: 2025
Keywords: coconut oil industry; linear programming; maximising profit; product mix.
File-URL: http://www.inderscience.com/link.php?id=144101
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Handle: RePEc:ids:ijisen:v:49:y:2025:i:1:p:1-17
Template-Type: ReDIF-Article 1.0
Author-Name: Mahesh M. Deshpande
Author-X-Name-First: Mahesh M.
Author-X-Name-Last: Deshpande
Author-Name: Vikas B. Ghute
Author-X-Name-First: Vikas B.
Author-X-Name-Last: Ghute
Title: Process capability indices Cp and Cpk under AR (2) process
Abstract:
Process capability indices are widely used by quality practitioners to quantify the capability of given manufacturing processes. The process capability indices <i>C<SUB align="right"><SMALL>p</SMALL></SUB></i> and <i>C<SUB align="right"><SMALL>pk</SMALL></SUB></i> are based on the assumptions of independence and normality of the process characteristic. Many authors have reported that ignoring the autocorrelation present in the process characteristics leads to wrong decisions. In this paper, the effect of the autocorrelation on the capability indices <i>C<SUB align="right"><SMALL>p</SMALL></SUB></i> and <i>C<SUB align="right"><SMALL>pk</SMALL></SUB></i> is discussed. The second order autoregressive process AR (2) is considered to model the data from an autocorrelated process. To reduce the effect of autocorrelation on the indices and the skip and mixed sampling techniques are implemented to form rational subgroups in the design of these indices. Results based on simulation study confirm that both the techniques improve estimates of capability indices <i>C<SUB align="right"><SMALL>p</SMALL></SUB></i> and <i>C<SUB align="right"><SMALL>pk</SMALL></SUB></i> significantly.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 158-173
Issue: 2
Volume: 49
Year: 2025
Keywords: process capability index; subgroup; autoregressive process; s-skip and mixed sampling.
File-URL: http://www.inderscience.com/link.php?id=144405
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Handle: RePEc:ids:ijisen:v:49:y:2025:i:2:p:158-173
Template-Type: ReDIF-Article 1.0
Author-Name: Aneta Jajou
Author-X-Name-First: Aneta
Author-X-Name-Last: Jajou
Author-Name: Ahmed Azab
Author-X-Name-First: Ahmed
Author-X-Name-Last: Azab
Author-Name: Sally Kassem
Author-X-Name-First: Sally
Author-X-Name-Last: Kassem
Title: Vehicle routing decision-support system development using integer programming and heuristics: a model-driven structured approach
Abstract:
In this article, a model-driven structured approach is adopted to develop a decision support system for the capacitated vehicle routing problem. A repository of artefacts is developed through system initiation, analysis, design, and implementation. Data about the problem is gathered, and existing procedures are analysed and improved using key stakeholders' knowledge to maintain continuous communication throughout the stages with involved parties. The DSS adopts mathematical programming and a heuristic to obtain exact and good solutions. The nearest neighbourhood heuristic is employed to solve large instances. IDEF0 and a problem statement are employed for system initiation. A cause-effect analysis is conducted for problem analysis. Use-case diagrams and narratives are used for requirements analysis. Logical and physical data flow diagrams are developed for system design. The system is implemented using Excel internal VBA language and the Application Programming Interfaces for Frontline Solver and Google Maps. Fico Xpress is used for exact solutions.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 226-251
Issue: 2
Volume: 49
Year: 2025
Keywords: model-driven software engineering; decision support system; DSS; vehicle routing problem; VRP; logical design; system construction.
File-URL: http://www.inderscience.com/link.php?id=144406
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Handle: RePEc:ids:ijisen:v:49:y:2025:i:2:p:226-251
Template-Type: ReDIF-Article 1.0
Author-Name: Yun-Xiang Han
Author-X-Name-First: Yun-Xiang
Author-X-Name-Last: Han
Title: Machine learning-based conflict-free trajectory generation
Abstract:
With the rapid development of the aviation industry, air traffic flow is showing a rapid growth trend, and the mutual influence and interference between aircraft in the airspace are also increasing. In order to ensure the safe and orderly operation of air traffic flow, it is urgent to propose efficient conflict-free trajectory generation methods. The development of artificial intelligence technology provides a new way for the design of conflict-free trajectory generation algorithms. As a consequence, machine learning can be applied to conflict-free trajectory generation. Intelligent agents learn autonomously in their interactions with the environment, thus possessing the ability to make autonomous decisions. Simulation experiments in different scenarios have shown that the algorithm proposed is effective.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 174-185
Issue: 2
Volume: 49
Year: 2025
Keywords: machine learning; air traffic control; conflict management; trajectory planning.
File-URL: http://www.inderscience.com/link.php?id=144407
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Handle: RePEc:ids:ijisen:v:49:y:2025:i:2:p:174-185
Template-Type: ReDIF-Article 1.0
Author-Name: Mahnaz Naghsh-Nilchi
Author-X-Name-First: Mahnaz
Author-X-Name-Last: Naghsh-Nilchi
Author-Name: Morteza Rasti-Barzoki
Author-X-Name-First: Morteza
Author-X-Name-Last: Rasti-Barzoki
Title: A game-theoretic approach for analysing a competition between electric and hydrogen-based vehicles in a supply chain to reduce carbon emission under government strategies
Abstract:
In recent decades, climate change and air pollution have become major global challenges due to population growth and increased fossil fuel use. Electric and hydrogen vehicles have emerged as sustainable alternatives, reducing greenhouse gas emissions and improving air quality. Both offer co-benefits in reducing air pollutants from common emission sources. However, the study shows that despite higher demand for electric cars, hydrogen car manufacturers still yield greater profits. The preference for consumers and governments is more towards electric cars due to higher demand and better environmental impact. Nevertheless, the hydrogen car market remains profitable for manufacturers. Governments may play a role through tax and subsidy policies to incentivise consumers towards more sustainable choices, contributing to environmental protection and public health preservation.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 252-266
Issue: 2
Volume: 49
Year: 2025
Keywords: electric car; hydrogen car; government policy; pollution pricing; sustainability; game theory.
File-URL: http://www.inderscience.com/link.php?id=144408
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Handle: RePEc:ids:ijisen:v:49:y:2025:i:2:p:252-266
Template-Type: ReDIF-Article 1.0
Author-Name: Seema Sharma
Author-X-Name-First: Seema
Author-X-Name-Last: Sharma
Author-Name: Mamta .
Author-X-Name-First: Mamta
Author-X-Name-Last: .
Title: Performance and reliability analysis of pulping system in a paper plant
Abstract:
This paper presents the performance and reliability analysis of the pulping system in a repairable paper plant utilising the fuzzy λ-τ method based on trapezoidal fuzzy numbers. The configuration of the pulping system has been modelled by the Petri net model. To deal with imprecision and vagueness in failure/repair data, trapezoidal fuzzy numbers are used to fuzzify the failure and repair data of each component of the pulping system. The fuzzy λ-τ method has been utilised to evaluate reliability factors of the pulping system including availability, reliability, failure rate, repair time, mean time between failures and expected number of failures at different spreads. The analysis is beneficial for plant managers to enhance the performance of the pulping system by developing and implementing appropriate maintenance strategies and policies.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 206-225
Issue: 2
Volume: 49
Year: 2025
Keywords: repairable systems; fuzzy λ-τ method; Petri net; trapezoidal fuzzy number; uncertain data.
File-URL: http://www.inderscience.com/link.php?id=144409
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Handle: RePEc:ids:ijisen:v:49:y:2025:i:2:p:206-225
Template-Type: ReDIF-Article 1.0
Author-Name: Dawei Zhang
Author-X-Name-First: Dawei
Author-X-Name-Last: Zhang
Author-Name: Shouli Gao
Author-X-Name-First: Shouli
Author-X-Name-Last: Gao
Author-Name: Rui Xia
Author-X-Name-First: Rui
Author-X-Name-Last: Xia
Author-Name: Dongya Zhao
Author-X-Name-First: Dongya
Author-X-Name-Last: Zhao
Title: Data-driven distributed control of input-coupled interconnected systems based on Nash optimality
Abstract:
This paper introduces a data-driven distributed controller for interconnected systems with input coupling of unknown models. The estimation of input coupling terms does not depend on historical data. The complex interconnected systems with input couplings are decomposed into individual subsystems. The proposed strategy not only alleviates computational load, but also optimises the interaction between subsystems, effectively addressing the output oscillations of the system during abrupt reactions of input couplings. The convergence of the control algorithm and the stability of the closed-loop system response are examined, and the efficacy of the proposed control method is validated by comparative simulations.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 186-205
Issue: 2
Volume: 49
Year: 2025
Keywords: input couplings; data-driven control; dynamic linearisation method; Nash optimality; distributed control.
File-URL: http://www.inderscience.com/link.php?id=144410
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Handle: RePEc:ids:ijisen:v:49:y:2025:i:2:p:186-205
Template-Type: ReDIF-Article 1.0
Author-Name: Abdessalem Jerbi
Author-X-Name-First: Abdessalem
Author-X-Name-Last: Jerbi
Author-Name: Mohamed Ali Elleuch
Author-X-Name-First: Mohamed Ali
Author-X-Name-Last: Elleuch
Title: PROMETHEE vs. OptQuest for simulation-based multi-objective optimisation approach in flexible manufacturing systems
Abstract:
Flexible manufacturing system design is a complex problem because of its stochastic nature, especially when there are multiple optimisation objectives to consider. For this reason, various studies have relied on discrete event simulation tools to create and evaluate the flexible manufacturing system's performance using multi-objective optimisation methods. However, the literature lacks comparative studies of these different methods in the flexible manufacturing systems optimisation context. This paper aims to compare the two optimisation methods, PROMETHEE and OptQuest, based on multi-objective efficiency. PROMETHEE is based on ranking simulation results, while OptQuest is an iterative method using a meta-heuristic. This comparison showed that OptQuest is the best-performing method.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 139-157
Issue: 2
Volume: 49
Year: 2025
Keywords: discrete event simulation; DES; multi-objective optimisation method; simulation-based; OptQuest; PROMETHEE; flexible manufacturing systems; FMS.
File-URL: http://www.inderscience.com/link.php?id=144411
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Handle: RePEc:ids:ijisen:v:49:y:2025:i:2:p:139-157
Template-Type: ReDIF-Article 1.0
Author-Name: Yi Guo
Author-X-Name-First: Yi
Author-X-Name-Last: Guo
Author-Name: Miao Zhou
Author-X-Name-First: Miao
Author-X-Name-Last: Zhou
Author-Name: Jun Xie
Author-X-Name-First: Jun
Author-X-Name-Last: Xie
Author-Name: Wei-Zhong Huang
Author-X-Name-First: Wei-Zhong
Author-X-Name-Last: Huang
Author-Name: Pan Geng
Author-X-Name-First: Pan
Author-X-Name-Last: Geng
Title: Clustering evaluation of energy efficiency in the inlet pump room based on BP-DEMATEL and improved CRITIC method
Abstract:
China would successively release implementation plans and supporting measures for major areas and industries to achieve 'carbon peak and carbon neutrality'. Accordingly, the sewage treatment industry has to push energy and industrial structure transformation and upgrading. Whether the inlet pump room can perform effectively, and energy-savingly, will directly impact the economic operation of the whole enterprise. This paper seeks to build a complete energy efficiency assessment model for the pump room. Firstly, the calculation and standard range of five relevant indicators are carried out. Secondly, the indicator weight algorithm of BP-DEMATEL and improved CRITIC technique is proposed, and the linear coupling weighting is adopted according to minimal discernment information. Alternatively, an OPTICS clustering approach based on Bayes optimisation is also presented to obtain the range for four operating conditions. Finally, empirical research is carried out on the case of the pump room in Shanghai. The researched model may greatly increase the assessment performance, giving the scientific reference value for the optimisation of the pump room renovation.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 267-292
Issue: 3
Volume: 49
Year: 2025
Keywords: BP-DEMATEL; improved CRITIC method; Bayesian optimisation; OPTICS clustering; energy efficiency assessment.
File-URL: http://www.inderscience.com/link.php?id=145057
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Handle: RePEc:ids:ijisen:v:49:y:2025:i:3:p:267-292
Template-Type: ReDIF-Article 1.0
Author-Name: Tarit Rattanamanee
Author-X-Name-First: Tarit
Author-X-Name-Last: Rattanamanee
Author-Name: Suebsak Nanthavanij
Author-X-Name-First: Suebsak
Author-X-Name-Last: Nanthavanij
Title: Multi-period and multi-workday workforce scheduling for manufacturing workstations with multiple workers
Abstract:
This paper discusses the complex workforce scheduling problem where a workday is divided into multiple periods and the planning horizon is extended to cover several workdays, or MPMW-WSP. Additionally, there can be multiple workers at individual manufacturing workstations. The MPMW-WSP focuses on the safe exposure of workers to a given ergonomic hazard that is dominantly present in the workplace. Dominant ergonomic hazard can be either a single-limit hazard or variable-limit hazard. A hybrid solution procedure is employed to solve the problem. It consists of a heuristic method to estimate an initial workforce size and an integer linear programming (ILP) model to determine a minimum number of workers to be rotated among different tasks so that their daily hazard exposures are within the permissible or recommended limit. Numerical examples and computation experiment are also presented.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 293-314
Issue: 3
Volume: 49
Year: 2025
Keywords: workforce scheduling; job rotation; ergonomic hazard; hazard exposure; optimisation.
File-URL: http://www.inderscience.com/link.php?id=145059
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Handle: RePEc:ids:ijisen:v:49:y:2025:i:3:p:293-314
Template-Type: ReDIF-Article 1.0
Author-Name: Mst. Nasima Bagum
Author-X-Name-First: Mst. Nasima
Author-X-Name-Last: Bagum
Author-Name: Choudhury Abul Anam Rashed
Author-X-Name-First: Choudhury Abul Anam
Author-X-Name-Last: Rashed
Author-Name: Ratul Barman
Author-X-Name-First: Ratul
Author-X-Name-Last: Barman
Author-Name: Md. Ariful Islam
Author-X-Name-First: Md. Ariful
Author-X-Name-Last: Islam
Author-Name: Md. Mehedi Hasan Kibria
Author-X-Name-First: Md. Mehedi Hasan
Author-X-Name-Last: Kibria
Title: Impact of interconnectivity and information sharing on cyber-physical system implementation
Abstract:
The study examines the correlation between implementing a cyber-physical system (CPS) and interconnectivity, information sharing and visibility (ISV). A conceptual model was developed based on an extensive literature review. The study was performed in a mixed mode based on the case study and survey. In the case study, ten public and private banks participated. The survey was conducted with responses from 54 banks using a semi-structured questionnaire. The conceptual model was validated, and the relationships within the model were tested using structural equation modelling (SEM). Additionally, the impact of CPS implementation on cost reduction, improved Performance, and enhanced resource utilisation was assessed. The data collected was analysed using SmartPLS 4. The findings indicated a positive influence of Interconnectivity and ISV on CPS implementation, leading to increased performance and resource utilisation. However, it is worth noting that the study did not find a positive effect of CPS implementation on overall cost.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 359-379
Issue: 3
Volume: 49
Year: 2025
Keywords: interconnectivity; information sharing and visibility; ISV; cyber-physical system; CPS; conceptual model; structural equation modelling; SEM.
File-URL: http://www.inderscience.com/link.php?id=145061
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Handle: RePEc:ids:ijisen:v:49:y:2025:i:3:p:359-379
Template-Type: ReDIF-Article 1.0
Author-Name: Junxiang Li
Author-X-Name-First: Junxiang
Author-X-Name-Last: Li
Author-Name: Xiaran Gao
Author-X-Name-First: Xiaran
Author-X-Name-Last: Gao
Author-Name: Chenglong Li
Author-X-Name-First: Chenglong
Author-X-Name-Last: Li
Author-Name: Xiaojia Ma
Author-X-Name-First: Xiaojia
Author-X-Name-Last: Ma
Title: Improving satisfaction of waiting customers by personalised service
Abstract:
Queuing problem is considerably important in a service field. The customers' waiting satisfaction in the process of queuing has a large impact on the whole service. A queuing model providing personalised service is constructed to improve the satisfaction of waiting customers. The enterprise's extra service cost, waiting satisfaction and the customer's actual utility after service are analysed to increase the proportion of satisfied customers by using arena, a simulation software. By comparing with other queuing systems, the results show that the proportion of customers seeking personalised service, their willingness to get extra service and their queuing position of providing extra service have an important impact on the proportion of satisfied customers. The research can offer an important reference for contact centres and other service fields.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 335-358
Issue: 3
Volume: 49
Year: 2025
Keywords: contact centre; personalised service; queuing theory; arena; waiting satisfaction.
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Handle: RePEc:ids:ijisen:v:49:y:2025:i:3:p:335-358
Template-Type: ReDIF-Article 1.0
Author-Name: Ashwani Kharola
Author-X-Name-First: Ashwani
Author-X-Name-Last: Kharola
Title: Simulation modelling and comparison of different training algorithms for multistep prediction
Abstract:
This study investigates nonlinear autoregressive neural network (NARNET) and nonlinear autoregressive neural network with exogenous input (NARXNET)-based artificial neural network (ANN) models for multistep prediction of specific enthalpy of steam. Real-time experimental data on specific enthalpy of steam has been collected and used for training of proposed models. The machine learning models have been trained using different training algorithms namely Levenberg-Marquardt (LM), Bayesian-regularisation (BR), scaled-conjugate gradient (SCG), one step secant (OSS) and resilient back-propagation (RB). The prediction performance of these algorithms has been analysed in terms of root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and bivariate correlation coefficient (COR) for a maximum step size of 30 multistep predictions. The results highlight superior performance of NARXNET model designed using BR-algorithm compared to prediction models designed using other training algorithms.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 315-334
Issue: 3
Volume: 49
Year: 2025
Keywords: multistep prediction; NARNET; NARXNET; process modelling; simulation; training algorithms.
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Handle: RePEc:ids:ijisen:v:49:y:2025:i:3:p:315-334
Template-Type: ReDIF-Article 1.0
Author-Name: Wujiu Pan
Author-X-Name-First: Wujiu
Author-X-Name-Last: Pan
Author-Name: Yinghao Sun
Author-X-Name-First: Yinghao
Author-X-Name-Last: Sun
Author-Name: Shuming Cao
Author-X-Name-First: Shuming
Author-X-Name-Last: Cao
Author-Name: Kuishan Kong
Author-X-Name-First: Kuishan
Author-X-Name-Last: Kong
Author-Name: Junyi Wang
Author-X-Name-First: Junyi
Author-X-Name-Last: Wang
Author-Name: Peng Nie
Author-X-Name-First: Peng
Author-X-Name-Last: Nie
Title: A bearing fault diagnosis and monitoring software system based on lightweight neural networks to resist coloured noise
Abstract:
In actual industrial sites, the application of bearings is becoming increasingly widespread. In order to better monitor the faults of bearings, this article combines the concept of deep learning and designs a bearing fault diagnosis and monitoring software system based on lightweight neural networks to resist coloured noise. This system is developed based on MATLAB App Designer. When testing the system, five different bearing datasets, namely MFPT, Paderborn, IMS, Ottawa, and CWRU, are applied. Considering that the data in actual scenarios contains complex noise, coloured noise signals are added. Compared to traditional fault diagnosis software that requires pre writing data into the program, this software can perform real-time processing on any single column vibration data file. By using lightweight neural network methods to preprocess the data collected by sensors, the SqueezeNet network has a faster speed to extract significant features of vibration. This software system can achieve time-frequency domain image output of signals, with multiple noise reduction methods. It can also calculate the frequency of faults based on bearing model data. Through envelope spectrum images, the location of faults can be monitored and email reminders can be sent to engineers.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 380-403
Issue: 3
Volume: 49
Year: 2025
Keywords: lightweight neural networks; anti-coloured noise; software engineering; fault detect; system health management.
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Handle: RePEc:ids:ijisen:v:49:y:2025:i:3:p:380-403
Template-Type: ReDIF-Article 1.0
Author-Name: S. Malik
Author-X-Name-First: S.
Author-X-Name-Last: Malik
Author-Name: S.C. Malik
Author-X-Name-First: S.C.
Author-X-Name-Last: Malik
Author-Name: N. Nandal
Author-X-Name-First: N.
Author-X-Name-Last: Nandal
Author-Name: A.D. Yadav
Author-X-Name-First: A.D.
Author-X-Name-Last: Yadav
Title: Reliability assessment of a NSP system under constant triangular fuzzy failure rates
Abstract:
Here, the reliability of a non-series-parallel system (NSP) has been examined considering fuzzy failure rates. There are seven non-identical components in the system, which are arranged into three structures. The two structures operate in parallel and each having three components connected in series; while the third structure has a single component connected with the extreme components of the parallel structures. The expression for reliability of the system is assessed using the path tracing method. The failure rate of the components is assumed as constant triangular fuzzy number and thus they follow the exponential distribution. The α-cut method is used to defuzzify these fuzzy numbers for determining reliability measures. The intervals for fuzzy reliability and MTSF of the system have been computed for both non-identical and identical components. An illustration of RLC system has been described to highlight the application part of the research work.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 405-420
Issue: 4
Volume: 49
Year: 2025
Keywords: fuzzy reliability measures; NSP system; exponential failure laws; α-cut approach; triangular membership function.
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Handle: RePEc:ids:ijisen:v:49:y:2025:i:4:p:405-420
Template-Type: ReDIF-Article 1.0
Author-Name: Mohammed Said Obeidat
Author-X-Name-First: Mohammed Said
Author-X-Name-Last: Obeidat
Author-Name: Hussam A. Alshraideh
Author-X-Name-First: Hussam A.
Author-X-Name-Last: Alshraideh
Author-Name: Abedallah A. Al Kader
Author-X-Name-First: Abedallah A. Al
Author-X-Name-Last: Kader
Author-Name: Rabah M. Al Abdi
Author-X-Name-First: Rabah M. Al
Author-X-Name-Last: Abdi
Author-Name: Morad Etier
Author-X-Name-First: Morad
Author-X-Name-Last: Etier
Author-Name: Mohammad Hamasha
Author-X-Name-First: Mohammad
Author-X-Name-Last: Hamasha
Title: Optimising multiple sclerosis detection: harnessing cutting-edge MRI image analysis for advanced industrial diagnosis
Abstract:
Human brain disorders are those abnormal changes that occur around or inside brain parts. These disorders include infections, tumours, trauma, degeneration, structural defects, stroke, and autoimmune disorders. The devastating consequences of brain disorders on the lives of humans could be reduced by early diagnosis. The diagnosis of brain disorders consumes higher time and effort by physicians compared to computerised diagnosis techniques. Several computerised diagnosis algorithms have been developed to improve and optimise the diagnostic capabilities of physicians. Magnetic resonance imaging (MRI) is an effective tool used for brain disorders diagnosis. MRI detection of multiple sclerosis (MS) is extremely complicated due to several reasons, including the anatomical variability between patients, lesion location, and the variability in lesion's shape. This paper reviews several computerised algorithms used in diagnosing brain disorders, to present the most efficient techniques that reduce the physicians' diagnosis time and effort of MRI images, hence, starting MS treatment at earlier stages.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 506-519
Issue: 4
Volume: 49
Year: 2025
Keywords: magnetic resonance imaging; MRI; brain disorders; industrial engineering algorithms; decision; multiple sclerosis.
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Handle: RePEc:ids:ijisen:v:49:y:2025:i:4:p:506-519
Template-Type: ReDIF-Article 1.0
Author-Name: Wen Zhu
Author-X-Name-First: Wen
Author-X-Name-Last: Zhu
Author-Name: Jingran Zhang
Author-X-Name-First: Jingran
Author-X-Name-Last: Zhang
Author-Name: Sanchoy Das
Author-X-Name-First: Sanchoy
Author-X-Name-Last: Das
Title: Optimising parcel count in e-commerce fulfilment with mixed-split order picking
Abstract:
E-commerce fulfilment warehouses (e-warehouses) store thousands of items and fulfil thousands of online customer orders every day. E-warehouses are operationally different from traditional warehouses. To accelerate fulfilment speed, an e-warehouse splits multi-line orders across multiple picklists. A key research question is how to manage the flow of picked items so that the number of shipped parcels is minimised. This research introduces the e-warehouse order consolidation (WOC) problem. Tote consolidation is a key link between order picking and parcel packing. We identify key modelling elements and formulate the associated constraints and objectives. The WOC mixed integer program is tested on a series of problems, and we illustrate the operational and business value of controlling the tote consolidation process. Order similarity between totes is used to develop two fast heuristics. Two controllable design parameters are investigated, the number of packing stations and the number of totes assigned simultaneously, on parcel packing efficiency.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 421-441
Issue: 4
Volume: 49
Year: 2025
Keywords: fulfilment speed; shipping costs; parcel packing.
File-URL: http://www.inderscience.com/link.php?id=146066
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Handle: RePEc:ids:ijisen:v:49:y:2025:i:4:p:421-441
Template-Type: ReDIF-Article 1.0
Author-Name: Utkarsh Mittal
Author-X-Name-First: Utkarsh
Author-X-Name-Last: Mittal
Author-Name: Dilbagh Panchal
Author-X-Name-First: Dilbagh
Author-X-Name-Last: Panchal
Title: Development of distributed LSTM framework to forecast transportation lead time
Abstract:
This study aimed to develop an AI-based system to evaluate delivery complexities and reduce system vulnerabilities more accurately. The approach of the study is empirical where dataset from different systems is used to develop ML and DL models to forecast more accurately transportation time and improve profitability. Various models, e.g., linear regression, deep learning, and distributed long short-term memory (DLSTM) networks are used. It is found that the DLSTM regression model shows superior performance in forecasting the delivery times compared to the other models, achieving an accuracy of around 90%, as the model has the ability to handle complex and nonlinear relationships among variables. The findings underscore the potential of machine learning (ML) and deep learning (DL) in improving predictability and profitability aimed increasing digitalisation in global transportation.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 520-544
Issue: 4
Volume: 49
Year: 2025
Keywords: machine learning; deep learning; delivery time forecasting; profitability optimisation; fuzzy C means clustering; supply chain risk management.
File-URL: http://www.inderscience.com/link.php?id=146067
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Handle: RePEc:ids:ijisen:v:49:y:2025:i:4:p:520-544
Template-Type: ReDIF-Article 1.0
Author-Name: Devbrat Gupta
Author-X-Name-First: Devbrat
Author-X-Name-Last: Gupta
Author-Name: Jitendra Kumar
Author-X-Name-First: Jitendra
Author-X-Name-Last: Kumar
Author-Name: Vishal Goyal
Author-X-Name-First: Vishal
Author-X-Name-Last: Goyal
Title: An enhanced fractional-order fuzzy controller design for an integrated power system using a counteractive control action
Abstract:
This research article reports an efficient control of the integrated power system (IPS) using a fractional-order fuzzy proportional and derivative (FOFPD) controller combined with a fractional-order integral and derivative (FOID) controller in order to overcome the sudden variation in microgrid frequency problem. The novelty of the anticipated control strategy lies in the use of FOID control action, which generates the counteractive action to improve the control performance. The controller's gains are optimised by an optimisation algorithm called spider-monkey optimisation (SMO). The objective function is considered as the sum of the integral of the squared deviation of the microgrid frequency (ISFD). The proposed controller's response is then compared with the integer-order counterparts to investigate the effectiveness of the suggested controller. The detailed simulation results demonstrate the robust behaviour of the proposed control scheme and establish its superiority over other investigated control structures.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 442-477
Issue: 4
Volume: 49
Year: 2025
Keywords: integrated power system; IPS; fractional-order; fuzzy PID controller; spider-monkey algorithm; micro-grid frequency.
File-URL: http://www.inderscience.com/link.php?id=146068
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Handle: RePEc:ids:ijisen:v:49:y:2025:i:4:p:442-477
Template-Type: ReDIF-Article 1.0
Author-Name: Vikram Singh
Author-X-Name-First: Vikram
Author-X-Name-Last: Singh
Author-Name: Somesh Kumar Sharma
Author-X-Name-First: Somesh Kumar
Author-X-Name-Last: Sharma
Author-Name: Prakhar Shukla
Author-X-Name-First: Prakhar
Author-X-Name-Last: Shukla
Title: Impact of multi-agent technology on the manufacturing organisations: a multi-criteria decision-making analysis
Abstract:
Quality is a major concern for manufacturers and can affect the performance of manufacturing system components and product quality. This study aims to improve the quality of manufacturing processes from material acquisition to the end of production using multi-agent technology (MAT). The literature review identified five factors and their 31 governing variables, and their impact is analysed through AHP, DEMATEL, and TOPSIS. AHP was used to study and establish priority orders. DEMATEL was used to develop inter-relationship and TOPSIS to validate the global ranking evolved through AHP. 'Manufacturing process' along with 'quality aspects' have evolved most significant factors for controlling quality. Their significance is increased since they were discovered to be the most influential in affecting other factors. The detailed research and discussions in this article may allow industrial organisations to raise quality standards, hence increasing customer support, lowering costs, and improving efficiency.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 478-505
Issue: 4
Volume: 49
Year: 2025
Keywords: analytic hierarchy process; AHP; DEMATEL; manufacturing organisational; multi-agent technology; MAT; TOPSIS.
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Handle: RePEc:ids:ijisen:v:49:y:2025:i:4:p:478-505
Template-Type: ReDIF-Article 1.0
Author-Name: Xia Zihan
Author-X-Name-First: Xia
Author-X-Name-Last: Zihan
Title: The impact of difficulty and expensive financing on energy industry conservation and emission reduction
Abstract:
This article separates the issues of financing difficulties and high financing costs, and studies the impact of financing difficulties and high financing costs on the energy-saving and emission reduction behaviour of enterprises. We find that when the problem of difficult financing for enterprises exists, the approved loan amount positively affects the level of energy conservation and emission reduction through production volume. The level of energy conservation and emission reduction is not related to the loan interest rate. The fixed cost investment in energy conservation and emission reduction is a major factor for enterprises to take energy conservation and emission reduction measures. Even with financing difficulties, because of the existence of carbon taxes and subsidies, companies tend to adopt energy-saving and emission reduction measures. The heterogeneity of enterprise scale only exists when financing difficulties exist. Once financing difficulties are resolved, there is no heterogeneity in the impact of enterprise scale on energy conservation and emission reduction levels. This means that the energy conservation and emission reduction levels of enterprises of different scales are ultimately the same.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 58-74
Issue: 1
Volume: 50
Year: 2025
Keywords: difficulties in financing; high cost of financing; energy conservation and emission reduction; carbon tax; subsidy.
File-URL: http://www.inderscience.com/link.php?id=146116
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Handle: RePEc:ids:ijisen:v:50:y:2025:i:1:p:58-74
Template-Type: ReDIF-Article 1.0
Author-Name: Vikram Singh
Author-X-Name-First: Vikram
Author-X-Name-Last: Singh
Author-Name: Somesh Kumar Sharma
Author-X-Name-First: Somesh Kumar
Author-X-Name-Last: Sharma
Title: Analysing the role of multi-agent technology on high-tech manufacturing using AHP, DEMATEL, and TOPSIS
Abstract:
High-tech product manufacturers operate in extremely sensitive environments and face challenges in meeting the quality standards of high-tech products. To address these challenges, this study aims analysing the impact of multi-agent technology (MAT) on the quality standards of high-tech manufacturing (HTM). The extensive literature was used to explore 8 factors of HTM and 45 variables of MAT. A hybrid multi-criteria decision-making technique was used to analyse the factors and variables. The HTM process is a highly prioritised and impactful factor. <i>Process monitoring, automatic customised test plans, adaptive agents, demand forecasting agents, and virtual manufacturing</i> are the top five globally ranked variables. The findings of this article provide ranking order and determine the relationship between factors and variables for the integration of MAT in HTM. This bridging can assist designers in improving the design quality, manufacturers in increasing process quality standards of products, and market experts in selecting the potential market.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 75-105
Issue: 1
Volume: 50
Year: 2025
Keywords: HTM; MAT; analytical hierarchy process; AHP; decision-making trail evaluation laboratory; DEMATEL; high-tech products; HTPs; technique for order preference by similarity to ideal solution; TOPSIS.
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Handle: RePEc:ids:ijisen:v:50:y:2025:i:1:p:75-105
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Author-Name: P. Leslie Dass
Author-X-Name-First: P. Leslie
Author-X-Name-Last: Dass
Author-Name: Sreerengan V.R. Nair
Author-X-Name-First: Sreerengan V.R.
Author-X-Name-Last: Nair
Author-Name: Georgy P. Kurien
Author-X-Name-First: Georgy P.
Author-X-Name-Last: Kurien
Author-Name: S. Kumar Chandar
Author-X-Name-First: S. Kumar
Author-X-Name-Last: Chandar
Title: A systematic literature network analysis approach to assess the topology of modern-era supply chain risk management research
Abstract:
Over the past decade, there has been a significant increase in research on supply chain risk management (SCRM). This review uses a systematic literature network analysis to provide an overview of the SCRM research landscape, with emphasis on optimisation approaches, mathematical modelling tools, and the identification of seminal studies and relevant keywords used in SCRM research. However, there are few quantitative models that represent the relationship between supply chain surplus, sustainability, and resilience in SCRM literature. The study has limitations since it only sources from a single database, and more clarity is needed on the effectiveness of optimisation in SCRM, which can be further evaluated through case studies and empirical studies.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 106-145
Issue: 1
Volume: 50
Year: 2025
Keywords: supply chain; risk management; optimisation; linear programming; resilience; sustainability; surplus; profitability.
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Handle: RePEc:ids:ijisen:v:50:y:2025:i:1:p:106-145
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Author-Name: Ashraf Sayed Abdou
Author-X-Name-First: Ashraf Sayed
Author-X-Name-Last: Abdou
Author-Name: Basma E. El-Demerdash
Author-X-Name-First: Basma E.
Author-X-Name-Last: El-Demerdash
Author-Name: Sherif A. Mazen
Author-X-Name-First: Sherif A.
Author-X-Name-Last: Mazen
Author-Name: Nagy Ramadan Darwish
Author-X-Name-First: Nagy Ramadan
Author-X-Name-Last: Darwish
Title: Blockchain technology adoption in healthcare: a systematic review and conceptual framework
Abstract:
Recently, blockchain technology has attracted a lot of interest from different researchers and academics due to its unique properties like immutability, interoperability, and confidentiality. However, to date, their adoption in the healthcare sector is still very limited. Few studies applied a systematic literature review (SLR) for blockchain adoption in healthcare. In this research study, the first contribution is to identify the factors that influence the adoption of blockchain by applying the SLR approach, understand how these factors are interrelated, and discuss the main challenges of blockchain adoption. The findings demonstrated that, the unified theory of acceptance and use of technology (UTAUT), the technology acceptance model (TAM) and its extension were the most popular models used for blockchain adoption. Then, we identified the key research gaps and proposed a conceptual framework to address the identified gaps to be a reference and guide for organisations adopting blockchain in healthcare.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 1-57
Issue: 1
Volume: 50
Year: 2025
Keywords: blockchain technology; healthcare; blockchain adoption; systematic literature review; SLR; UTAUT; technology acceptance model; TAM; TOE.
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Handle: RePEc:ids:ijisen:v:50:y:2025:i:1:p:1-57
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Author-Name: Samer Abaddi
Author-X-Name-First: Samer
Author-X-Name-Last: Abaddi
Title: Jordan's future renewable energy stability and break-even analysis under various catalysts using system dynamics
Abstract:
The social acceptability of photovoltaic (PV) systems contributes not only to the amount of power generated but also to the CO<SUB align="right"><SMALL>2</SMALL></SUB> emissions reduction in Jordan. The effect of three catalysts; subsidy proportion, word of mouth (WOM) and advertising effectiveness is addressed in this piece of work, in addition to a forecast of the power generated and the CO<SUB align="right"><SMALL>2</SMALL></SUB> emissions reduction by 2080. System dynamics (SD) is the fundamental approach of this study. Qualitative interviews and energy reports assisted the data collection process and simulation was conducted between 2020 and 2080. Six scenarios are hypothesised to facilitate the comparison between the catalyst's effects with the help of break-even point analysis. Jordan is expected to generate 1.845 Terra Wh (TWh) and 995.9 TWh of energy by 2040 and 2080, respectively. The CO<SUB align="right"><SMALL>2</SMALL></SUB> emissions reduction is expected to cross 630 million tons by 2080. Advertising effectiveness was found to be the top catalyst that stimulates the power generated in Jordan followed by WOM. The quantitative models foster the policy makers towards investing in social acceptability dimensions toward achieving earlier equivalency of demand and supply. This is the first study in Jordan that develops break-even calculations at various levels of catalysts using SD.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 147-163
Issue: 2
Volume: 50
Year: 2025
Keywords: system dynamics; SD; power generated; word of mouth; WOM; subsidy proportion; advertising effectiveness; Jordan.
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Handle: RePEc:ids:ijisen:v:50:y:2025:i:2:p:147-163
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Author-Name: Ravi Kumar Mandava
Author-X-Name-First: Ravi Kumar
Author-X-Name-Last: Mandava
Title: Portable coconut tree climbing device and its analysis
Abstract:
The coconut tree is one of the useful plants among all other plants. Due to the lack of coconut tree climbers worldwide, many coconut palm growers are not interested in cultivating coconut farming. Based on the above problem, numerous researchers have developed various climbing mechanisms. To overcome this problem, a novel coconut tree climbing device (CTCD) was introduced which can climb the coconut tree up to the canopy. To check the deformation behaviour and generated stresses of various parts of the device in the present research work, the authors conducted dynamic analysis, such as modal, harmonic, and transient analysis in ANSYS 2021. Moreover, the dynamic properties of each component will also be tested under vibrational excitation. Therefore, one of the vibrational properties, that is, the natural frequency, is used to analyse the effect of transient loads and avoid the noise and vibration hazards in the components of the coconut tree climbing mechanism.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 191-210
Issue: 2
Volume: 50
Year: 2025
Keywords: coconut tree climbing device; dynamic analysis; finite element method; ANSYS.
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Handle: RePEc:ids:ijisen:v:50:y:2025:i:2:p:191-210
Template-Type: ReDIF-Article 1.0
Author-Name: Mei-Wei Huang
Author-X-Name-First: Mei-Wei
Author-X-Name-Last: Huang
Author-Name: Hao-Wei Yang
Author-X-Name-First: Hao-Wei
Author-X-Name-Last: Yang
Author-Name: Ming-Min Lo
Author-X-Name-First: Ming-Min
Author-X-Name-Last: Lo
Author-Name: Yung-Tai Tang
Author-X-Name-First: Yung-Tai
Author-X-Name-Last: Tang
Author-Name: Hsin-Hung Wu
Author-X-Name-First: Hsin-Hung
Author-X-Name-Last: Wu
Title: Customer behaviour analytics in a supermarket in Taiwan based on RFM model
Abstract:
Supermarkets need to use a data-driven approach to segment customers based on their purchase transactions to meet different customer needs in this highly competitive retail industry in Taiwan. This empirical study combines clustering techniques and RFM model to analyse member customers' transaction data from a database of a supermarket in Taiwan within a six-week period. The results showed that 5,410 member customers are grouped into loyal, new, and vulnerable customers. A one-way analysis of variance is performed to show these three groups of customers are statistically different. This research further explores the top 10 best-selling merchandise items in both purchase quantity and total money spent. Loyal customers need to focus on five merchandise items. New customers have eight out of ten best-selling merchandise items appeared in both purchase quantity and total money spent. Supermarket management need to pay more attention to these eight items for new customers in this supermarket.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 220-233
Issue: 2
Volume: 50
Year: 2025
Keywords: customer behaviour; supermarket; RFM model; data-driven approach; loyal customer; new customer; vulnerable customer; best-selling merchandise items; Taiwan.
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Handle: RePEc:ids:ijisen:v:50:y:2025:i:2:p:220-233
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Author-Name: Yun-Xiang Han
Author-X-Name-First: Yun-Xiang
Author-X-Name-Last: Han
Title: Trajectory prediction using inference model
Abstract:
With the rapid increase in air traffic, more accurate aircraft trajectory prediction is the focus of integrated airspace operations for both manned and unmanned civil aviation. The development of machine learning technology is expected to bring new solutions to this problem. This paper processes and analyses aircraft trajectory data, and models aircraft trajectory prediction based on hidden Markov models, providing an efficient and accurate solution for aircraft trajectory prediction. Firstly, the trajectory data was pre-processed to provide effective support for the subsequent model formulation. Secondly, a trajectory prediction model was designed using the trajectory data and hidden Markov model. Finally, the performance of different models was compared and analysed through experiments.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 211-219
Issue: 2
Volume: 50
Year: 2025
Keywords: trajectory prediction; air traffic management; system modelling; simulation.
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Handle: RePEc:ids:ijisen:v:50:y:2025:i:2:p:211-219
Template-Type: ReDIF-Article 1.0
Author-Name: Roland Mader
Author-X-Name-First: Roland
Author-X-Name-Last: Mader
Title: Variant-rich new energy vehicle powertrain functional safety engineering
Abstract:
New energy vehicles (NEVs) are a success story that has led to the continuous introduction of manifold vehicle models and variants. Due to the fact that NEV powertrains are controlled by electrical and/or electronic (E/E) systems, faults and failures of these systems can lead to hazards. In order to prevent such hazards, functional safety engineering aims at avoiding or mitigating safety-critical E/E system faults and failures on the system, hardware and software level. Accordingly, numerous functional safety activities need to be executed and many workproducts are required. Variability of NEVs, high requirements as to achieve functional safety, short development cycles and resource constraints impose challenges for automotive companies. Motivated by an industrial case study we identify variation points of NEV powertrains and analyse their dependencies on the functional safety lifecycle. Based on that, we identify organisational and technical measures which support variant-rich new energy vehicle powertrain functional safety engineering.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 253-280
Issue: 2
Volume: 50
Year: 2025
Keywords: functional safety; new energy vehicle; NEV; battery electric vehicle; BEV; hybrid electric vehicle; HEV; powertrain; E/E system; product line; variability.
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Handle: RePEc:ids:ijisen:v:50:y:2025:i:2:p:253-280
Template-Type: ReDIF-Article 1.0
Author-Name: Nitin Goel
Author-X-Name-First: Nitin
Author-X-Name-Last: Goel
Author-Name: Naresh Kumar Yadav
Author-X-Name-First: Naresh Kumar
Author-X-Name-Last: Yadav
Title: Hybrid optimisation strategy-based economic emission dispatch for microgrid
Abstract:
CEED solution is the procedure of dividing the required demand of power among the possible producing units while taking into account low fuel costs, decreased emissions, and minimal transmission loss. The multiple objective functions are formulated to single CEED constraint to solve using an efficient algorithm. By combining the peculiar preying characteristics of Harris Hawk and the intellectual food storage characteristics of crow, a novel MIHHO Algorithm is designed to handle the CEED constraint. The efficiency of the optimisation strategy is evaluated with six test cases. The minimised results of transmission loss, economic cost and emission cost for the DG system by MIHHO technique is evaluated over the traditional strategies, such as GA, GWO, WOA, CSA and HHOA. From the outcomes, it is evident that the proposed MIHHO algorithm provides better solution as compared over the existing methods.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 164-190
Issue: 2
Volume: 50
Year: 2025
Keywords: wind; solar; microgrids; CEED; optimisation.
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Handle: RePEc:ids:ijisen:v:50:y:2025:i:2:p:164-190
Template-Type: ReDIF-Article 1.0
Author-Name: Sharmila Patil-Karpe
Author-X-Name-First: Sharmila
Author-X-Name-Last: Patil-Karpe
Author-Name: S.H. Brahmananda
Author-X-Name-First: S.H.
Author-X-Name-Last: Brahmananda
Title: Resource allocation strategy in fog computing
Abstract:
The idea of fog computing enables the delivery of computational services and resources closer to the endpoints and users, at the network's edge. Due to the large number of devices, determining the best resource allocation in this situation is challenging. Accordingly, a unique resource allocation strategy for fog computing is suggested in this work. The resource allocation of fog computing is made possible by the modelling of a nonlinear functionality under the objective function comprising metrics like service response rate, execution time, make span, resource consumption, and reboot rate. The proposed approach also takes consideration for the allocation of resources in urgent scenarios that allow for quick resource distribution. Considering this as the optimisation problem, a new optimisation model termed as hybrid coati insisted beluga whale optimisation (HCIBWO) is introduced in this work. The performance of proposed work is evaluated over the conventional models in terms of different measures.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 234-252
Issue: 2
Volume: 50
Year: 2025
Keywords: resource allocation fog computing; makespan; execution time; HCIBWO model.
File-URL: http://www.inderscience.com/link.php?id=146609
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Handle: RePEc:ids:ijisen:v:50:y:2025:i:2:p:234-252
Template-Type: ReDIF-Article 1.0
Author-Name: Hafsa El-Kaime
Author-X-Name-First: Hafsa
Author-X-Name-Last: El-Kaime
Author-Name: Saad Lissane Elhaq
Author-X-Name-First: Saad Lissane
Author-X-Name-Last: Elhaq
Title: SDAPI: a systematic approach to integrating Industry 4.0 and lean manufacturing for SME improvement
Abstract:
Many businesses, particularly small and medium-sized enterprises (SMEs), seek to improve productivity and reduce resource usage. Lean manufacturing (LM) is a popular method for optimising processes by eliminating non-value-added activities and improving efficiency and flexibility. However, in today's rapidly changing technological and market environment, companies must also adopt innovative production management approaches to stay competitive. The Fourth Industrial Revolution and related technologies offer the opportunity to take current manufacturing systems to the next level. While previous research has explored the concept of 'Lean 4.0', which combines Industry 4.0 and LM, there has been less focus on the relationship between methodological approaches and technological concepts. This research aims to fill this gap by presenting a methodological-technological framework for implementing Industry 4.0 technologies in SMEs in order to achieve the objectives of LM. The proposed methodology, called SDAPI, is developed through a literature reviews, it consists of five steps: specify, detect, analyse, propose, and implement.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 281-302
Issue: 3
Volume: 50
Year: 2025
Keywords: framework; Industry 4.0; lean manufacturing; LM; Lean 4.0; small and medium-sized enterprises; SMEs.
File-URL: http://www.inderscience.com/link.php?id=147677
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Handle: RePEc:ids:ijisen:v:50:y:2025:i:3:p:281-302
Template-Type: ReDIF-Article 1.0
Author-Name: Rajdeep Singh
Author-X-Name-First: Rajdeep
Author-X-Name-Last: Singh
Author-Name: Chandan Deep Singh
Author-X-Name-First: Chandan Deep
Author-X-Name-Last: Singh
Title: Ranking of factors affecting performance of manufacturing industry using fuzzy MAUT technique
Abstract:
With the rise of creative engineering, India's manufacturing industry is expanding quickly. Because of this, the market is more cutthroat for businesses, especially those that are indigenous. Core functional competences are essential for survival in the age of globalisation since they can positively or negatively impact a variety of organisational performance factors. This paper deals with the prioritisation or ranking of the factors, which affect core functional competencies and further affect the performance of the Indian manufacturing industry. For the ranking of the attributes, the fuzzy MAUT method has been used in the study.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 303-321
Issue: 3
Volume: 50
Year: 2025
Keywords: fuzzy MAUT; core functional competencies; competitiveness; globalisation.
File-URL: http://www.inderscience.com/link.php?id=147678
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Handle: RePEc:ids:ijisen:v:50:y:2025:i:3:p:303-321
Template-Type: ReDIF-Article 1.0
Author-Name: Himani Pant
Author-X-Name-First: Himani
Author-X-Name-Last: Pant
Author-Name: S.B. Singh
Author-X-Name-First: S.B.
Author-X-Name-Last: Singh
Title: Particle swarm optimisation strategy for design optimisation of a series-parallel system incorporating failure dependencies and multiple repair teams
Abstract:
A series-parallel system with multiple repair teams and failure dependence is investigated in this article. An optimal design problem is being scrutinised and worked upon in the current paper. This work is conducted with reference to prior study conducted by Hu et al. (2012). They used a genetic algorithm (GA) to find the optimal design of the series-parallel configuration consequently minimising its cost. The particle swarm optimisation (PSO) technique is being proposed in this article to further refine their results. The solution entails identifying the vector comprising of system components and repair teams, (<i>n</i><SUB align="right"><SMALL>1</SMALL></SUB>, <i>n</i><SUB align="right"><SMALL>2</SMALL></SUB>, ..., <i>n<SUB align="right"><SMALL>N</SMALL></SUB></i>, <i>r</i><SUB align="right"><SMALL>1</SMALL></SUB>, <i>r</i><SUB align="right"><SMALL>2</SMALL></SUB>, ..., <i>r<SUB align="right"><SMALL>N</SMALL></SUB></i>). These computations were carried out using the computer software Python. As a consequence, extremely intriguing results were achieved.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 371-391
Issue: 3
Volume: 50
Year: 2025
Keywords: particle swarm optimisation; PSO; design optimisation; series-parallel configuration; failure dependencies.
File-URL: http://www.inderscience.com/link.php?id=147679
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Handle: RePEc:ids:ijisen:v:50:y:2025:i:3:p:371-391
Template-Type: ReDIF-Article 1.0
Author-Name: Sandeep Sharda
Author-X-Name-First: Sandeep
Author-X-Name-Last: Sharda
Author-Name: Sanjeev Mishra
Author-X-Name-First: Sanjeev
Author-X-Name-Last: Mishra
Author-Name: Dheeraj Nimawat
Author-X-Name-First: Dheeraj
Author-X-Name-Last: Nimawat
Title: Sustainable spare parts inventory stock control management at macro level, using linear programming: perspective to petroleum and fertiliser industries
Abstract:
The goal of the study is to manage the problem in the petroleum and fertiliser sectors by optimising the overall spare parts inventory. To solve the issue, the proposed framework employs the linear programming model (LPM) and TORA software to optimise the entire spare parts inventory. This research offers petroleum and fertiliser industries a clear and straightforward way for the spare parts management. Results show improved cost and stock management that promotes sustainability with optimised data set of total spare parts inventory as 40,000 numbers and US$65.5 million. Additionally, it eliminates the excessive stock due to exaggerated risk with traditional practices and reduces deterioration by lowering long-stay of items in the warehouse. Validation of model is done using classified data sets (as HML and FSN) that are based on previous factual six years' cumulative consumption and acquired from an Indian fertiliser industry.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 322-342
Issue: 3
Volume: 50
Year: 2025
Keywords: high, medium and low; HML; sustainability; spare parts macro inventory; linear programming; LP; TORA; fast, slow and non-moving; FSN.
File-URL: http://www.inderscience.com/link.php?id=147680
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Handle: RePEc:ids:ijisen:v:50:y:2025:i:3:p:322-342
Template-Type: ReDIF-Article 1.0
Author-Name: Kamal Deep
Author-X-Name-First: Kamal
Author-X-Name-Last: Deep
Title: A comprehensive approach to UA facility layout design using genetic algorithm
Abstract:
Facility layout planning is a quantum leap for the production industry to realise the low entropy, widely applied to the unequal area facility layout problems (UA-FLPs). This paper aims at the optimisation of UA-facility layout in the flexible bays structure (FBS) to maximise the adjacency requirements of facility types for the production layout. The FBS is a most commonly used structure flexible to allocate the facilities in the bays of unequal areas permitting empty space in the total area of the layout. The proposed mixed integer programming model has been formulated to ensure; minimum side length, confined aspect ratio of facility types, and optimal space utilisation in the total area of facility layout. The genetic algorithm based heuristic has been used to search the discrete solution space in a feasible time span. The optimal results obtained are mapped with the best-known numerical instances reported in the literature to approve the efficacy of proposed solution approach.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 392-412
Issue: 3
Volume: 50
Year: 2025
Keywords: unequal area facility layout; flexible-shape facilities; genetic algorithm-based optimisation algorithm; flexible bays structure; FBS.
File-URL: http://www.inderscience.com/link.php?id=147681
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Handle: RePEc:ids:ijisen:v:50:y:2025:i:3:p:392-412
Template-Type: ReDIF-Article 1.0
Author-Name: Cong Chi Tran
Author-X-Name-First: Cong Chi
Author-X-Name-Last: Tran
Author-Name: Thi Tham Nguyen
Author-X-Name-First: Thi Tham
Author-X-Name-Last: Nguyen
Author-Name: Van Tuu Nguyen
Author-X-Name-First: Van Tuu
Author-X-Name-Last: Nguyen
Title: Multi-objective optimisation in turning AISI 304 stainless steel: an integration of the Taguchi method, response surface methodology, and NSGA-II
Abstract:
This study examined the impact of machining parameters [depth of cut (d), feed rate (f), and spindle speed (s)] on surface roughness and material removal rate in the turning process of AISI 304 stainless steel. Three optimisation methods were used: the Taguchi method, the response surface methodology (RSM), and the non-dominated sorting genetic algorithm II (NSGA-II). The Taguchi method identified the most influential parameter for surface roughness (f > d > s) and for material removal rate (d > f > s). RSM regression models achieved high R<SUP align="right"><SMALL>2</SMALL></SUP> values of 0.9896 for roughness and 0.9997 for material removal rate. NSGA-II multi-objective optimisation produced 35 Pareto solutions within ranges of cutting parameters, resulting in surface roughness values from 0.239 to 3.301 μm and material removal rates from 151.53 to 594.99 mm<SUP align="right"><SMALL>3</SMALL></SUP>/s. Confirmation experiments validated the optimal values, with deviations within 10%, confirming the accuracy of the research method for solving the optimisation problem.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 413-432
Issue: 3
Volume: 50
Year: 2025
Keywords: multi-objective optimisation; 304 stainless steel; Taguchi method; response surface methodology; RSM; NSGA-II.
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Handle: RePEc:ids:ijisen:v:50:y:2025:i:3:p:413-432
Template-Type: ReDIF-Article 1.0
Author-Name: Sakir Sakir
Author-X-Name-First: Sakir
Author-X-Name-Last: Sakir
Author-Name: Bambang Dwi Argo
Author-X-Name-First: Bambang Dwi
Author-X-Name-Last: Argo
Author-Name: Yusuf Hendrawan
Author-X-Name-First: Yusuf
Author-X-Name-Last: Hendrawan
Author-Name: Sugiono Sugiono
Author-X-Name-First: Sugiono
Author-X-Name-Last: Sugiono
Title: Integration of Kansei engineering and artificial neural network toward the implementation of intelligent food packaging design based on consumer preferences
Abstract:
Packaging design innovation is one of the crucial strategies for consumer-oriented product development. Therefore, this research aimed to design intelligent food packaging (IFP) for beef products using an integrated approach of Kansei engineering (KE) and artificial neural network (ANN) based on consumer preferences. The results showed 37 valid and reliable Kansei words based on Kaiser-Meyer-Olkin measure (KMO), Bartlett's test of sphericity, and measure of sampling adequacy (MSA) using SPSS 26 software. Based on the results, the best ANN structure was achieved with the Traingd learning algorithm which had 418 inputs, 20 nodes in the hidden layer, and eight outputs with a training mean square error (MSE) of 0.0099991, a validation MSE of 0.0321, a training regression (R) of 0.99287, and a validation R of 0.98928. Therefore, the best IFP design for beef products based on consumer preferences could be achieved by integrating KE and ANN methods.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 343-370
Issue: 3
Volume: 50
Year: 2025
Keywords: Kansei engineering; artificial neural network; intelligent food packaging design; consumer preferences.
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Handle: RePEc:ids:ijisen:v:50:y:2025:i:3:p:343-370
Template-Type: ReDIF-Article 1.0
Author-Name: Seema Sharma
Author-X-Name-First: Seema
Author-X-Name-Last: Sharma
Author-Name: Mamta
Author-X-Name-First:
Author-X-Name-Last: Mamta
Title: Reliability analysis of bleaching system in a paper industry
Abstract:
This paper presents a fuzzy technique to examine the reliability of bleaching system in a paper industry using uncertain data. The uncertainties in failure/repair data of every subsystem/component of the bleaching system are quantified using two types of fuzzy numbers, trapezoidal and triangular fuzzy numbers. The basic arrangement of components/subsystems of bleaching system is represented using Petri net model. The fuzzy values of various reliability metrics of bleaching system for different uncertainty levels have been evaluated employing fuzzy <i>λ</i>-<i>τ</i> technique. Subsequently, to analyse the failure behaviour of bleaching system and to plan for suitable maintenance policies, these fuzzy values have been defuzzified using centre of area method. The analysis is useful for plant managers to improve the performance of bleaching system by establishing and implementing appropriate maintenance strategies and policies.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 512-530
Issue: 4
Volume: 50
Year: 2025
Keywords: reliability analysis; uncertain data; Petri net; fuzzy methodology; trapezoidal fuzzy number.
File-URL: http://www.inderscience.com/link.php?id=147714
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Handle: RePEc:ids:ijisen:v:50:y:2025:i:4:p:512-530
Template-Type: ReDIF-Article 1.0
Author-Name: Yongzhong Wu
Author-X-Name-First: Yongzhong
Author-X-Name-Last: Wu
Author-Name: Minqi Xu
Author-X-Name-First: Minqi
Author-X-Name-Last: Xu
Author-Name: Mianmian Huang
Author-X-Name-First: Mianmian
Author-X-Name-Last: Huang
Title: A hybrid optimisation strategy for large-scale vehicle routing problems with time windows using solution initialisation
Abstract:
This paper investigates a novel hybrid optimisation strategy that integrates a machine learning algorithm with a meta-heuristics to tackle large-scale vehicle routing problems with time windows (VRPTW). Specifically, the K-means clustering algorithm is employed to generate initial routing solutions, subsequently optimised by an artificial bee colony (ABC) algorithm. The new approach is tested on large-scale real-life cases. The computational results show that the new algorithm outperforms a well-established ABC algorithm in terms of both objective value and computation time. In addition, the experiments highlight the importance of considering both the distance between customers and customer time windows in the clustering process to ensure good computational results.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 492-511
Issue: 4
Volume: 50
Year: 2025
Keywords: vehicle routing problem with time windows; clustering; artificial bee colony algorithm.
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Handle: RePEc:ids:ijisen:v:50:y:2025:i:4:p:492-511
Template-Type: ReDIF-Article 1.0
Author-Name: Dong Zhang
Author-X-Name-First: Dong
Author-X-Name-Last: Zhang
Author-Name: Yazhen Lan
Author-X-Name-First: Yazhen
Author-X-Name-Last: Lan
Author-Name: Shan Hu
Author-X-Name-First: Shan
Author-X-Name-Last: Hu
Title: Designing and assessing cognitive training application for seniors with MCI: comprehensive evaluation methodology
Abstract:
This study addresses the absence of design standards for cognitive training apps catering to seniors with mild cognitive impairment (MCI). Integrating qualitative and quantitative methods, it employs grounded theory (GT) for synthesising user interview data and iteratively refines design criteria through theoretical coding. The fuzzy analytic hierarchy process (FAHP) and criteria importance through intercriteria correlation (CRITIC) objectively establish weights for design evaluation criteria and finalise the weighting values using the combined ideal point assignment method. The VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) is used to evaluate and select design solutions. This comprehensive approach minimises subjectivity and bias in criteria determination and weighting, enhancing the Objectivity and accuracy of cognitive training application evaluations. Usability questionnaires and user testing validate that the integrated approach improves design decisions' objectivity and scientificity, making the application more responsive to user needs.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 433-464
Issue: 4
Volume: 50
Year: 2025
Keywords: healthy ageing; cognitive training; mild cognitive impairment; MCI; grounded theory; evaluation methodology.
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Handle: RePEc:ids:ijisen:v:50:y:2025:i:4:p:433-464
Template-Type: ReDIF-Article 1.0
Author-Name: Leena Hamdan
Author-X-Name-First: Leena
Author-X-Name-Last: Hamdan
Author-Name: Abdulrahman R. Alenezi
Author-X-Name-First: Abdulrahman R.
Author-X-Name-Last: Alenezi
Title: Reliable location models with transportation mode selection
Abstract:
In this study, we examined a three-echelon supply chain network consisting of candidate facilities, hubs, and customers. Products are delivered from facilities to customers directly or via hubs, utilising different transportation modes. Full truckload shipments are employed for delivering products from facilities to customers or hubs, while less than truckload shipments are utilised for products from hubs to customers. Considering the susceptibility of facilities to failure, customers are allocated to either a primary facility exclusively or both primary and secondary facilities, with the secondary facility serving customers only during the failure period. The problem is mathematically formulated as a linear integer programming model and subsequently solved using the Lagrange relaxation procedure. The solution was obtained with an average computational time of 96.6 seconds, demonstrating a gap between upper and lower bounds averaging 0.158%.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 465-491
Issue: 4
Volume: 50
Year: 2025
Keywords: supply chain management; SCM; reliability; transportation mode; Lagrange relaxation; facility location models.
File-URL: http://www.inderscience.com/link.php?id=147717
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Handle: RePEc:ids:ijisen:v:50:y:2025:i:4:p:465-491
Template-Type: ReDIF-Article 1.0
Author-Name: Ayedh Almutairi
Author-X-Name-First: Ayedh
Author-X-Name-Last: Almutairi
Author-Name: Fatmah Alfaqeeh
Author-X-Name-First: Fatmah
Author-X-Name-Last: Alfaqeeh
Author-Name: Zachary A. Collier
Author-X-Name-First: Zachary A.
Author-X-Name-Last: Collier
Author-Name: James H. Lambert
Author-X-Name-First: James H.
Author-X-Name-Last: Lambert
Title: Quantifying the influence of future disruptive scenarios to priorities of energy supply chains systems of liquified petroleum gas
Abstract:
The availability of liquified petroleum gas (LPG) is especially critical for commercial and residential users. A risk assessment framework has been established to track risk scenarios and to address the level of disruptions on the priority orders of initiatives under the influences of scenarios. It demonstrated in an LPG facility in the State of Kuwait with 17 emergent conditions, 3 scenarios, 15 initiatives, and 4 evaluation criteria. The shutting down of one centre and the shutting down of two centres were the most disruptive scenarios. The highest ranked initiatives are: Increasing the number of workers for inspection, having random weekly inspections, and having monthly maintenance, respectively. However, these initiatives are the least robust to disruptive scenarios' impact. The initiative, raising customers' awareness of how to safely use LPG cylinders, has the least priority ranking order but is the most robust initiative to the influence of scenarios.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 555-578
Issue: 4
Volume: 50
Year: 2025
Keywords: energy supply; risk analysis; emergent conditions; scenario-based preference model; liquified petroleum gas system.
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Handle: RePEc:ids:ijisen:v:50:y:2025:i:4:p:555-578
Template-Type: ReDIF-Article 1.0
Author-Name: Kapil Netaji Vhatkar
Author-X-Name-First: Kapil Netaji
Author-X-Name-Last: Vhatkar
Title: Integrated squid game with coati optimisation algorithm for resource allocation system for NOMA system in industrial internet of things
Abstract:
The development of IIoT is the scarcity of spectrum resources. It consumes a significant amount of energy while increases the system's spectrum effectiveness. This paper shows the resource distribution in non-orthogonal multiple access (NOMA) models for IIoT applications from the view of power efficiency. In this paper, the hybrid optimisation is used for reducing the energy consumption of power resources and channel resources. An integrated squid game with coati optimisation algorithm (ISG-COA) is developed by integrating squid game optimiser (SGO) and coati optimisation algorithm (COA) for resource allocation in IIoT scenarios. The limitation of user service quality criteria is also added to the existing optimisation problem in order to prevent the situation where the data transmission quality is substantially impaired as a result of the system's energy-saving measures. The algorithm's average system energy efficiency is higher according to the strategy performance simulation experiment when compared to traditional resource allocation algorithms.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 531-554
Issue: 4
Volume: 50
Year: 2025
Keywords: energy-efficient resource allocation system; integrated squid game with coati optimisation algorithm; industrial internet of things; non-orthogonal multiple access; NOMA; squid game optimiser; SGO; coati optimisation algorithm; COA.
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Handle: RePEc:ids:ijisen:v:50:y:2025:i:4:p:531-554
Template-Type: ReDIF-Article 1.0
Author-Name: Junxiang Li
Author-X-Name-First: Junxiang
Author-X-Name-Last: Li
Author-Name: Chenmin Gong
Author-X-Name-First: Chenmin
Author-X-Name-Last: Gong
Author-Name: Deqiang Qu
Author-X-Name-First: Deqiang
Author-X-Name-Last: Qu
Author-Name: Xi Wang
Author-X-Name-First: Xi
Author-X-Name-Last: Wang
Title: Optimal operation of microgrid systems considering user energy storage behavior
Abstract:
This paper establishes a microgrid system optimisation model based on carbon capture and shared energy storage to promote new energy consumption and better reduce carbon emissions. Considering the user's psychology and demand response, the energy storage behaviour of users is analysed to maximise the benefit of energy storage and achieve a win-win situation for both load aggregators and shared energy storage providers. The pricing and energy supply strategies of microgrid operators are optimised based on carbon capture technology. A case study is conducted on a microgrid system located in a business park in southern China. Through numerical simulation and comparative analysis of multiple scenes, it is verified that carbon capture devices and shared energy storage can significantly reduce the microgrid's carbon emissions and the uncertainty of the system operation and improve users' demand response capability, which is beneficial to the long-term development of the microgrid system.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 1-32
Issue: 1
Volume: 51
Year: 2025
Keywords: carbon capture; shared energy storage; demand response; user psychology; energy storage behaviour.
File-URL: http://www.inderscience.com/link.php?id=148382
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Handle: RePEc:ids:ijisen:v:51:y:2025:i:1:p:1-32
Template-Type: ReDIF-Article 1.0
Author-Name: S.M. Senthil
Author-X-Name-First: S.M.
Author-X-Name-Last: Senthil
Author-Name: M. Bhuvanesh Kumar
Author-X-Name-First: M. Bhuvanesh
Author-X-Name-Last: Kumar
Author-Name: L. Rajeshkumar
Author-X-Name-First: L.
Author-X-Name-Last: Rajeshkumar
Author-Name: Sampada Viraj Dravid
Author-X-Name-First: Sampada Viraj
Author-X-Name-Last: Dravid
Title: Effects of building parameters on mechanical and surface properties of 3D printed bioplastic (PLA) using TOPSIS: an experimental study
Abstract:
Additive manufacturing is becoming an emerging technology in manufacturing three-dimensional (3D) components in a layer-by-layer printing fashion. The technology enables wide variety of materials to be printed for different applications starting from automotive, aerospace, marine and to the biomedical fields. 3D printing processes are majorly used to print polymeric materials compared to metallic materials. Polylactic acid (PLA) is the most commonly used material by the fused deposition modelling technique, which accounts for multiple applications. The present study investigates the effect of printing parameters such as infill density, wall thickness, printing speed and ironing to identify optimum process parameter combination for better mechanical performance. Based on the design of experiments, 40 samples were printed and measured for mechanical characteristics. Upon the analysis using TOPSIS, at the parameter combination of infill density (99%), wall thickness (3 mm), and printing speed (150 mm/hr), the printed specimens showed higher tensile strength of 10.20 MPa and comparatively good surface finish. Hence, the parameter optimisation showed a positive influence on enhancing the mechanical properties of printed components.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 104-124
Issue: 1
Volume: 51
Year: 2025
Keywords: 3D printing; additive manufacturing; polylactic acid; PLA; parameter optimisation; TOPSIS.
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Handle: RePEc:ids:ijisen:v:51:y:2025:i:1:p:104-124
Template-Type: ReDIF-Article 1.0
Author-Name: Jun Wang
Author-X-Name-First: Jun
Author-X-Name-Last: Wang
Author-Name: Yazhen Lan
Author-X-Name-First: Yazhen
Author-X-Name-Last: Lan
Author-Name: Dong Zhang
Author-X-Name-First: Dong
Author-X-Name-Last: Zhang
Author-Name: Mengqing Liu
Author-X-Name-First: Mengqing
Author-X-Name-Last: Liu
Title: A study on the application of emotional factors in medical products for paediatric asthma
Abstract:
Emotional factors play a pivotal role in enhancing the user experience of medical products for paediatric asthma, mitigating children's negative emotions, and improving treatment adherence. However, a comprehensive framework and assessment criteria for integrating emotional factors into the design of such medical products are lacking. To standardise these criteria, this study integrates emotional design theory, grounded theory, and the fuzzy analytic hierarchy process (FAHP). Firstly, based on the three-level theory of emotional design, an interview outline was constructed to conduct semi-structured interviews with the target users, and the interview content was coded and analysed using the grounded theory to refine the emotional factor design indicators. Subsequently, FAHP assigned weights to these indicators, constructing a comprehensive emotional factor application model. PSSUQ validated product usability, revealing that the proposed model effectively meets users' emotional needs, thereby standardising emotional factors application criteria and offering theoretical references for designing medical products for paediatric asthma.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 33-58
Issue: 1
Volume: 51
Year: 2025
Keywords: emotional factors; emotional design theory; grounded theory; fuzzy analytic hierarchy process; FAHP; paediatric asthma medical products.
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Handle: RePEc:ids:ijisen:v:51:y:2025:i:1:p:33-58
Template-Type: ReDIF-Article 1.0
Author-Name: Abror Hoshimov
Author-X-Name-First: Abror
Author-X-Name-Last: Hoshimov
Author-Name: Anna Corinna Cagliano
Author-X-Name-First: Anna Corinna
Author-X-Name-Last: Cagliano
Author-Name: Jamshid Inoyatkhodjaev
Author-X-Name-First: Jamshid
Author-X-Name-Last: Inoyatkhodjaev
Author-Name: Antonio Carlin
Author-X-Name-First: Antonio
Author-X-Name-Last: Carlin
Title: Lean manufacturing applied in developing countries: a case study in metal industry
Abstract:
This paper proposes a structured approach that integrates key lean manufacturing tools to improve the operational performance of companies in developing countries, particularly in Central Asia. A case study approach is applied to a manufacturing company in Uzbekistan. Four steps are carried out: selection of a case company; formation of a working team and definition of the current process mapping; selection of relevant key performance indicators and lean tools; implementing lean tools and assessing improvements. The total daily production rate of the case company increased by about 28% after lean application. Developing countries need special efforts to overcome the barriers related to the cultural background of companies and the mentality of their employees, in order to support the diffusion of lean manufacturing. This case study can stimulate academics to focus on further research on the application of lean tools in developing countries and the key contextual factors for its successful implementation.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 125-147
Issue: 1
Volume: 51
Year: 2025
Keywords: lean manufacturing; value stream mapping; VSM; 5S; developing countries; case study; Uzbekistan.
File-URL: http://www.inderscience.com/link.php?id=148385
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Handle: RePEc:ids:ijisen:v:51:y:2025:i:1:p:125-147
Template-Type: ReDIF-Article 1.0
Author-Name: Mahlogonolo Russell Molokoane
Author-X-Name-First: Mahlogonolo Russell
Author-X-Name-Last: Molokoane
Author-Name: Olasumbo Ayodeji Makinde
Author-X-Name-First: Olasumbo Ayodeji
Author-X-Name-Last: Makinde
Author-Name: Kemlall Ramsaroop Ramdass
Author-X-Name-First: Kemlall Ramsaroop
Author-X-Name-Last: Ramdass
Title: Investigation of strategies to generate value from excess obsolete and non-use inventories held at a locomotive maintenance service organisation
Abstract:
Locomotive maintenance organisations play a key role towards ensuring effective repair, overhaul and preservation of locomotives used in a rail car. The locomotive maintenance organisation considered in this study has over the years hold excess obsolete and non-use inventories used for locomotive maintenance owing to poor inventory management practice. Hence, in order to remedy this dilemma, this study investigates strategies that could be deployed to generate value from the excess inventories held in the organisation. Experts' opinion sourced from inventory planners and supplier chain managers, and literature information were used to unveil suitable strategies that could be used to generate value from the excess inventories held in the organisation. The result of this research exercise revealed that lateral transshipment, auctioning, sales to external organisations, repurposing and supplier buy-back are the suitable strategies that could be used to generate value from the excess inventories held in the locomotive maintenance organisation.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 91-103
Issue: 1
Volume: 51
Year: 2025
Keywords: locomotive; maintenance; excess inventories; strategies; framework.
File-URL: http://www.inderscience.com/link.php?id=148386
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Handle: RePEc:ids:ijisen:v:51:y:2025:i:1:p:91-103
Template-Type: ReDIF-Article 1.0
Author-Name: Mehari Bezuneh
Author-X-Name-First: Mehari
Author-X-Name-Last: Bezuneh
Author-Name: Assefa Tsegaw
Author-X-Name-First: Assefa
Author-X-Name-Last: Tsegaw
Author-Name: Bereket Haile
Author-X-Name-First: Bereket
Author-X-Name-Last: Haile
Author-Name: Teshome Bogale
Author-X-Name-First: Teshome
Author-X-Name-Last: Bogale
Author-Name: Matthias Brossog
Author-X-Name-First: Matthias
Author-X-Name-Last: Brossog
Author-Name: Jörg Franke
Author-X-Name-First: Jörg
Author-X-Name-Last: Franke
Title: Modularity-based mass customisation for the competitiveness of the manufacturing industry
Abstract:
The manufacturing industry is undergoing a significant transformation into mass customisation (MC) to achieve sustainable competitiveness. The effectiveness of MC strategy pivots on a firm's ability to achieve product variety with high volume, low costs, superior quality, and fast delivery. Modularity-based manufacturing approach (MBMA) is utilised as one strategy for the effectiveness of MC capabilities. However, the impact of MBMA on each MC capabilities is not adequately addressed. Hence, this study examines how MBMA impacts each MC capabilities, thereby enhancing competitiveness of the manufacturing industry. Hypotheses were developed following a thorough review of the literature on manufacturing capabilities and modularity-based manufacturing. Expert opinions were collected using structured data-collection tools, and analysis was conducted using the algorithms of the fuzzy Delphi method. The research findings indicate that applying an MBMA in MC strategy enhances MC capabilities and ultimately contributes to increasing the competitiveness of the manufacturing industry.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 59-90
Issue: 1
Volume: 51
Year: 2025
Keywords: mass customisation capabilities; modularity based manufacturing; manufacturing competitiveness; fuzzy Delphi method.
File-URL: http://www.inderscience.com/link.php?id=148387
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Handle: RePEc:ids:ijisen:v:51:y:2025:i:1:p:59-90
Template-Type: ReDIF-Article 1.0
Author-Name: Prateek Khublani
Author-X-Name-First: Prateek
Author-X-Name-Last: Khublani
Author-Name: Anil K. Bhat
Author-X-Name-First: Anil K.
Author-X-Name-Last: Bhat
Author-Name: Jyoti Tikoria
Author-X-Name-First: Jyoti
Author-X-Name-Last: Tikoria
Title: Challenges and issues faced by pharmaceutical companies from supply chain management perspective: a systematic literature review
Abstract:
The aim of this study is to examine issues and challenges faced by pharmaceutical companies from a supply chain management perspective. The study employs a systematic literature review approach, complemented by the strategic utilisation of the PRISMA framework, to curate and analyse research papers spanning the years 2013 to 2024. This research sheds light on the prevailing obstacles and evolving dynamics within the sector. The research paper discusses and analyses ten themes related to the selected research topic, considering their connection with identified issues and challenges. The themes derived from this comprehensive analysis, highlight the challenges faced by these pharmaceutical companies. Furthermore, the findings of this research contribute to documenting best practices, enriches the academic discourse and offer a valuable resource for researchers and practitioners seeking to navigate the intricate landscape of pharmaceutical supply chain management.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 149-179
Issue: 2
Volume: 51
Year: 2025
Keywords: supply chain management; SCM; supply chain effectiveness; supply chain efficiency; pharmaceutical industry; pharmaceutical supply chain.
File-URL: http://www.inderscience.com/link.php?id=148890
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Handle: RePEc:ids:ijisen:v:51:y:2025:i:2:p:149-179
Template-Type: ReDIF-Article 1.0
Author-Name: Ammar Al-Bazi
Author-X-Name-First: Ammar
Author-X-Name-Last: Al-Bazi
Author-Name: Mahmood Ahmad
Author-X-Name-First: Mahmood
Author-X-Name-Last: Ahmad
Author-Name: Mohammad A. Shbool
Author-X-Name-First: Mohammad A.
Author-X-Name-Last: Shbool
Author-Name: Anees Abu-Monshar
Author-X-Name-First: Anees
Author-X-Name-Last: Abu-Monshar
Author-Name: Rami Hikmat Al-Hadeethi
Author-X-Name-First: Rami Hikmat
Author-X-Name-Last: Al-Hadeethi
Author-Name: AbdulSattar Al-Alusi
Author-X-Name-First: AbdulSattar
Author-X-Name-Last: Al-Alusi
Title: Lot streaming optimisation of scheduling problems in open-shop manufacturing environments
Abstract:
Scheduling manufacturing operations is vital for companies to thrive under high competition in various manufacturing industries. The production scheduling process allocates resources such as time for each specific operation, detects possible conflicts of allocated resources, controls job release timings on the shop floor, ensures delivery due dates, and thus increases the productivity and efficiency of the workforce. In this paper, a method usually exploited to reduce the production duration, dubbed 'lot streaming', is adapted and applied to solve scheduling problems in open shop environments. A new integer linear programming (ILP) model is developed to outline the integration of lot streaming scheduling and constraints of partial functionality machines in an open shop environment to minimise the makespan. In such an environment, there are no restrictions on the order in which the machines perform the job's operations. The developed model is applied and tested on five different hypothetical problems. The experimental results are presented, and the efficiency of the proposed ILP is discussed. It is concluded that considerable reductions in the makespan can be achieved with the inclusion of lot streaming in an open shop production environment.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 180-205
Issue: 2
Volume: 51
Year: 2025
Keywords: open shop scheduling; lot streaming technique; mathematical optimisation; partial processing functionality machines.
File-URL: http://www.inderscience.com/link.php?id=148891
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Handle: RePEc:ids:ijisen:v:51:y:2025:i:2:p:180-205
Template-Type: ReDIF-Article 1.0
Author-Name: Boppana V. Chowdary
Author-X-Name-First: Boppana V.
Author-X-Name-Last: Chowdary
Author-Name: Fahraz Ali
Author-X-Name-First: Fahraz
Author-X-Name-Last: Ali
Title: Optimisation of surface roughness of FDM fabricated parts: application of definitive screening design and genetic algorithm techniques
Abstract:
This study presents an experimental investigation on the impact of variations in various fused deposition modelling (FDM) process parameters such as layer thickness, build orientation, raster angle, part raster width, raster to raster air gap, number of contours, contour width and part shrinkage factors on the top surface roughness of FDM printed poly-carbonate parts. To meet the study objective, definitive screening design (DSD) and ANOVA techniques were used to develop a predictive model for establishment of a functional relationship between the selected process parameters and part surface roughness. Thereafter, the predictive model was validated and optimised using genetic algorithm (GA) technique. The comparison of optimal and default process parameter settings showed an improvement in surface roughness of 60.9%. The proposed combined DSD-GA approach can assist practitioners in fabrication of various industrial products to uplift the additive manufacturing (AM) sector.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 206-235
Issue: 2
Volume: 51
Year: 2025
Keywords: fused deposition modelling; FDM; surface roughness; poly-carbonate; definitive screening design; DSD; genetic algorithm; GA.
File-URL: http://www.inderscience.com/link.php?id=148892
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Handle: RePEc:ids:ijisen:v:51:y:2025:i:2:p:206-235
Template-Type: ReDIF-Article 1.0
Author-Name: Daniel Tendai Chitima
Author-X-Name-First: Daniel Tendai
Author-X-Name-Last: Chitima
Author-Name: Olasumbo Ayodeji Makinde
Author-X-Name-First: Olasumbo Ayodeji
Author-X-Name-Last: Makinde
Author-Name: Kemlall Ramsaroop Ramdass
Author-X-Name-First: Kemlall Ramsaroop
Author-X-Name-Last: Ramdass
Title: Performance assessment of a potential maintenance strategy for legacy avionic systems
Abstract:
This study presents an approach that could be used to appraise the performance of a potential maintenance strategy tailored to maintain legacy avionic systems. A potential maintenance strategy for legacy avionic systems with the appropriate metrics to ascertain its performance, supportability and the required life cycle cost associated with the usage of this maintenance strategy was presented. Avionic subsystems operational and failure data for a period of ten years, literature information and experts' opinions on the lifecycle cost and supportability requirements for the potential avionic systems maintenance strategy were analysed to ascertain the veracity of deploying this maintenance solution. This study revealed that the potential maintenance strategy earmarked for avionic system maintenance, is expected to have a mean time between failure, operational availability, mean time to repair, lifecycle cost and logistical supportability index of 53.4 hours, 0.92, 1.06 hours, $1,219,029.55 and 59 respectively.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 236-250
Issue: 2
Volume: 51
Year: 2025
Keywords: legacy avionic system; maintenance; reliability; maintainability; life cycle cost.
File-URL: http://www.inderscience.com/link.php?id=148893
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Handle: RePEc:ids:ijisen:v:51:y:2025:i:2:p:236-250
Template-Type: ReDIF-Article 1.0
Author-Name: Mehari Bezuneh
Author-X-Name-First: Mehari
Author-X-Name-Last: Bezuneh
Author-Name: Bereket Haile
Author-X-Name-First: Bereket
Author-X-Name-Last: Haile
Author-Name: Assefa Tsegaw
Author-X-Name-First: Assefa
Author-X-Name-Last: Tsegaw
Author-Name: Teshome Bogale
Author-X-Name-First: Teshome
Author-X-Name-Last: Bogale
Author-Name: Matthias Brossog
Author-X-Name-First: Matthias
Author-X-Name-Last: Brossog
Author-Name: Jörg Franke
Author-X-Name-First: Jörg
Author-X-Name-Last: Franke
Title: Improving the competitiveness of the manufacturing industry using mass customisation
Abstract:
Globalisation, market uncertainty, changing customer interests, and shorter product life cycles pose computational challenges to the manufacturing industry. Mass customisation (MC) has emerged as a solution to tackle these challenges by offering customised products while maintaining product cost, quality, volume, variety, and delivery time, which are called competitive factors in the manufacturing industry. However, the effectiveness of the MC strategy depends on how effectively the industry applies different manufacturing systems. Therefore, the main objectives of this research were to identify and determine how the manufacturing system enhances MC capabilities and contributes to the competitiveness of the manufacturing industry. The process involved formulating hypotheses after reviewing existing literature and gathering expert opinions and analyses using the algorithms of the fuzzy Delphi method. Ultimately, this study identified the basic manufacturing systems that can increase MC capabilities, which contributes to improving the competitiveness of the manufacturing industry.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 251-282
Issue: 2
Volume: 51
Year: 2025
Keywords: mass customisation; customisation capabilities; sustainable competitiveness; manufacturing systems; enabling factors; fuzzy Delphi method.
File-URL: http://www.inderscience.com/link.php?id=148894
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Handle: RePEc:ids:ijisen:v:51:y:2025:i:2:p:251-282
Template-Type: ReDIF-Article 1.0
Author-Name: Xiao Ye
Author-X-Name-First: Xiao
Author-X-Name-Last: Ye
Author-Name: Jing Tan
Author-X-Name-First: Jing
Author-X-Name-Last: Tan
Author-Name: Bichun Du
Author-X-Name-First: Bichun
Author-X-Name-Last: Du
Title: Research on immersive experience of packaging design based on virtual reality and semantic segmentation algorithm
Abstract:
The rapid advancement of digital technology is revolutionising packaging design through the integration of virtual reality (VR) and semantic segmentation. Traditional two-dimensional design methods are inadequate for accurately conveying three-dimensional structures, textures, and product intricacies, This study presents an immersive packaging design system that leverages VR and deep learning-based semantic segmentation to address these limitations. The system was developed through a structured approach involving framework analysis, extensive data preparation, model training, and the creation of interactive VR environments. A user study with 50 participants demonstrated significant improvements in comprehension (average score: 4.2 vs. 3.0), satisfaction (4.0 vs. 2.8), engagement (4.1 vs. 2.5), and task efficiency (15 minutes to 10 minutes). An empirical case with a beverage brand further validated its effectiveness, showing increased consumer satisfaction, understanding, engagement, purchase intent. These results underscore the system's potential to enable intelligent, personalised, and immersive packaging design experiences.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 1-18
Issue: 5
Volume: 51
Year: 2025
Keywords: virtual reality; VR; semantic segmentation algorithms; package design; immersive experiences.
File-URL: http://www.inderscience.com/link.php?id=149319
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File-Restriction: Open Access
Handle: RePEc:ids:ijisen:v:51:y:2025:i:5:p:1-18
Template-Type: ReDIF-Article 1.0
Author-Name: Mohammad Reza Gharib
Author-X-Name-First: Mohammad Reza
Author-X-Name-Last: Gharib
Author-Name: Najmeh Jamali
Author-X-Name-First: Najmeh
Author-X-Name-Last: Jamali
Author-Name: Behzad Omidi Koma
Author-X-Name-First: Behzad Omidi
Author-X-Name-Last: Koma
Author-Name: Farzaneh Ghasemi Esfehsalari
Author-X-Name-First: Farzaneh Ghasemi
Author-X-Name-Last: Esfehsalari
Title: Smart urban metamorphosis: revolutionising through synergised lean supply chains and IoT integration: a case study
Abstract:
This study addresses challenges in traditional supply chains by advocating a shift towards intelligent, resilient systems. It emphasises integrating the internet of things (IoT) into supply chain management, proposing a secure infrastructure connecting data, goods, and all supply chain activities. In smart cities, aligning with urban modernisation goals, these efforts optimise business practices. The research explores agile technological methods for developing IoT solutions in sustainable urban environments, aiming for a platform that supports rapid expansion and addresses economic, social, cultural, and transportation challenges. Using a descriptive-analytical approach, the study anticipates transformative changes in smart cities due to rapid urbanisation. It investigates the impact of lean supply chains (LSC) on smart cities, presenting model-based solutions. Isfahan serves as a case study, revealing the benefits of integrating LSC within the smart city framework. This research contributes to innovative urban solutions, emphasising the convergence of LSC and IoT for sustainable, resilient cities.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 365-384
Issue: 3
Volume: 51
Year: 2025
Keywords: internet of things; IoT; lean supply chain; LSC; smart city; manufacturing; transportation; tourism.
File-URL: http://www.inderscience.com/link.php?id=149943
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Handle: RePEc:ids:ijisen:v:51:y:2025:i:3:p:365-384
Template-Type: ReDIF-Article 1.0
Author-Name: Meena Chavan
Author-X-Name-First: Meena
Author-X-Name-Last: Chavan
Author-Name: B. Bhuvaneswari
Author-X-Name-First: B.
Author-X-Name-Last: Bhuvaneswari
Author-Name: J.V.N. Ramesh
Author-X-Name-First: J.V.N.
Author-X-Name-Last: Ramesh
Title: Arithmetic adopted chimp optimisation algorithm for optimal MPA design
Abstract:
Presently, MPAs are often used in a number of appliances due to their properties like lightweight, compatibility, reduced volume, low cost, and ease of installation on hard surfaces. Optimal antenna design ensures better results in almost all applications. Hence, this paper aims to introduce a novel Microstrip patch antenna design optimisation that ensures enhanced antenna performance with the optimal design parameters like substrate thickness, width, height, and length, under the satisfaction of multi-objectives like gain, bandwidth, antenna efficiency, return loss, and TARC. To solve the given optimisation problem, this work implements an arithmetic adopted chimp optimisation algorithm (AAChOA) scheme that merges the strategy of the chimp optimisation algorithm (ChOA) and arithmetic optimisation algorithm (AOA) to obtain higher antenna performance. Finally, the proposed technique was evaluated over other extant models based on different parameters like antenna gain, efficiency, total active reflection coefficient (TARC), return loss, and bandwidth.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 283-308
Issue: 3
Volume: 51
Year: 2025
Keywords: microstrip patch antenna; MPA; antenna efficiency; return loss; gain; optimisation.
File-URL: http://www.inderscience.com/link.php?id=149944
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Handle: RePEc:ids:ijisen:v:51:y:2025:i:3:p:283-308
Template-Type: ReDIF-Article 1.0
Author-Name: Vijay Omprakash Rathi
Author-X-Name-First: Vijay Omprakash
Author-X-Name-Last: Rathi
Author-Name: Raj Thaneeghaivel
Author-X-Name-First: Raj
Author-X-Name-Last: Thaneeghaivel
Title: Chaotic functions influenced the spider monkey optimisation algorithm for optimal routing and channel assignment
Abstract:
This paper intends to introduce a novel routing and channel assignment in multi-channel MANET. Here, the optimal routing is performed by selecting the cluster head under certain constraints like delay, distance, QoS, RSSI, and security. For this, chaotic functions influenced spider monkey optimisation (CFISMO) algorithm is used. The assignment of channels as the scheduling policy is introduced through senders while it has packets to transmit. In this work, the channel assignment will be initiated via a machine learning model that predicts the availability of the channels, which is based on the paths (channels) generated under the selected cluster head. Here, an optimised neural network (NN) will be used. Thus, the final output shows the paths (channels) to be assigned for data transmission. In the end, the performance of the adopted routing approach is evaluated over other traditional schemes based on various metrics like distance, PDR, delay, energy, alive nodes, QoS, security, and trust, respectively.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 309-341
Issue: 3
Volume: 51
Year: 2025
Keywords: MANET; optimal routing; quality of service; neural network; optimisation.
File-URL: http://www.inderscience.com/link.php?id=149956
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Handle: RePEc:ids:ijisen:v:51:y:2025:i:3:p:309-341
Template-Type: ReDIF-Article 1.0
Author-Name: A.B. Bhavya
Author-X-Name-First: A.B.
Author-X-Name-Last: Bhavya
Author-Name: S.B. Vinay Kumar
Author-X-Name-First: S.B. Vinay
Author-X-Name-Last: Kumar
Title: Self-adaptive meta heuristic model for floor planning in very large-scale integration
Abstract:
The process of designing very large scale integrated (VLSI) circuits includes a stage known as floor planning. Floor planning is done to ascertain the relative location of the various modules inside each sub-circuit after the complex circuit is divided into smaller sub-circuits during the partitioning stage. The objectives of this process are to minimise the total chip area covered by the circuit, the amount of dead space in the layout, and the interlinking wire length (WL) among modules. Estimating the placements and forms of the modules is what it is all about. The integrated circuit (IC), which has small feature sizes, a high clock frequency, and high packing density, can dissipate a lot of heat. This work proposes a self-adaptive cat swarm optimisation (SA-CSO) to resolve the floor plan issues. The non-slicing floorplans are regarded by the algorithm as having hard modules with continuous outline restraint. Thus, the area of layout gets reduced.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 342-364
Issue: 3
Volume: 51
Year: 2025
Keywords: very large scale integrated; VLSI; floorplan; non-slicing plan; dead space; area; SA-CSO algorithm.
File-URL: http://www.inderscience.com/link.php?id=149957
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Handle: RePEc:ids:ijisen:v:51:y:2025:i:3:p:342-364
Template-Type: ReDIF-Article 1.0
Author-Name: Sukhada Bhingarkar
Author-X-Name-First: Sukhada
Author-X-Name-Last: Bhingarkar
Title: Optimisation-driven model for breast cancer classification model using histopathological image
Abstract:
This paper provides a novel optimised deep model for classifying breast cancer. The simulation of IoT is the first step carried out, where the nodes collect the breast cancer histopathological image of patients. The routing is established with child circle inspired drawing optimisation (CCIDO). The fitness function is considered for choosing the best route using energy, trust distance, and delay. Then, the multi-grade breast cancer is executed at the base station. Here, a median filter is utilised for abandoning the noise. Unified extraction of features is provided for acquiring the features. The classification of breast cancer is done with the LeNet and trained using CCIDO. The assessment was performed to reveal the importance of the proposed model. The CCIDO-LeNet outperformed with the highest accuracy of 94.9%, NPV of 93.4%, PPV of 93.3%, TNR of 93.9% and TPR of 94.8%. In future, other datasets can be engaged to validate model flexibility.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 385-412
Issue: 3
Volume: 51
Year: 2025
Keywords: breast cancer detection; internet of things; median filter; SegNet; LeNet.
File-URL: http://www.inderscience.com/link.php?id=149969
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Handle: RePEc:ids:ijisen:v:51:y:2025:i:3:p:385-412
Template-Type: ReDIF-Article 1.0
Author-Name: Khedekar Vilas Baburao
Author-X-Name-First: Khedekar Vilas
Author-X-Name-Last: Baburao
Author-Name: Dharmendra Singh Rajput
Author-X-Name-First: Dharmendra Singh
Author-X-Name-Last: Rajput
Title: A multimedia-based patterns retrieval from database patterns and storing
Abstract:
In this work, a novel multimedia Pattern retrieval system is introduced that encapsulates three major phases: 1) feature extraction; 2) pattern generation; 3) pattern matching. The SURF features have been extracted from the audio input and text input. In addition, the video input is converted into RGB to greyscale format, and then the SURF features are extracted from it. The pattern generation phase includes three stages: 1) scaling of features; 2) rules generation with Association rule mining algorithm; 3) optimised rule generation. Initially, the extracted feature is scaled within limits 1 to 20, and the rules are generated for the video, audio, and text signals separately using the Association rule mining algorithm. Moreover, the optimised rules are generated from the extracted rules using the improved GOA model. Then, using the map-reduce framework, the correlation between them is validated.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 435-468
Issue: 4
Volume: 51
Year: 2025
Keywords: multi-media; pattern generation; pattern retrieval; apriori algorithm; IGWO.
File-URL: http://www.inderscience.com/link.php?id=150222
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Handle: RePEc:ids:ijisen:v:51:y:2025:i:4:p:435-468
Template-Type: ReDIF-Article 1.0
Author-Name: Abhijit S. Mali
Author-X-Name-First: Abhijit S.
Author-X-Name-Last: Mali
Author-Name: Manoj M. Dongre
Author-X-Name-First: Manoj M.
Author-X-Name-Last: Dongre
Title: Analysis of various image-based steganography techniques using different images
Abstract:
A detailed survey is elaborated in this paper for classification of optimisation algorithms utilised for image steganography. The reviews are gathered from 50 research papers and methodologies are classified depending on algorithms like cryptography, deep model, LSB, transform, edge detector, sparse, patch and quantum-based algorithms. The analysis is performed using the classification algorithms, evaluation metrics, tool, dataset used, and publication year. From analysis, it is proven that LSB is the category of algorithm is the widely used algorithm for image steganography. Similarly, MATLAB is the most frequently used implementation tool in most of the research papers, and the evaluation metrics, like PSNR, SSIM, and MSE are widely employed in classification algorithms. The research papers that are mostly taken for this survey are in 2020.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 516-539
Issue: 4
Volume: 51
Year: 2025
Keywords: wireless communication; steganography; cryptography; image security; authentication.
File-URL: http://www.inderscience.com/link.php?id=150223
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Handle: RePEc:ids:ijisen:v:51:y:2025:i:4:p:516-539
Template-Type: ReDIF-Article 1.0
Author-Name: Basant Kumar
Author-X-Name-First: Basant
Author-X-Name-Last: Kumar
Title: Blockchain-based authentication model for education data storage
Abstract:
In this work, a blockchain-based data-sharing model with secured data storage in educational institutions (BDS with SDSE) is presented that integrates storage servers, blockchain, and cryptography approaches to make a secure and reliable environment. Here, blockchain technology is utilised to ensure the reliability and security of data storage. The proposed model comprises four entities, namely education institutions, blockchain, certificate authority, and data centres. The proposed model combines the storage and sharing of educational records among institutions by using blockchain and a data centre. The blockchain ensures the security and auditability of the data, while the data centre is employed to establish record permissions. Finally, the experimentation analysis is performed for proposed model, and it presented enhanced performance with a memory usage of 0.418 MB, detection rate of 0.8 and computation time of 16.913 s.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 498-515
Issue: 4
Volume: 51
Year: 2025
Keywords: blockchain; authentication; education; data storage; key generation.
File-URL: http://www.inderscience.com/link.php?id=150224
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Handle: RePEc:ids:ijisen:v:51:y:2025:i:4:p:498-515
Template-Type: ReDIF-Article 1.0
Author-Name: Abdulnasser El-Gaddar
Author-X-Name-First: Abdulnasser
Author-X-Name-Last: El-Gaddar
Author-Name: Ahmed Azab
Author-X-Name-First: Ahmed
Author-X-Name-Last: Azab
Author-Name: Mohammed Fazle Baki
Author-X-Name-First: Mohammed Fazle
Author-X-Name-Last: Baki
Title: A part-mix batch-sizing and machinability data system for milling operations: an optimal sustainable cost of quality approach
Abstract:
With increased global competition and higher demand for sustainability in emerging markets, manufacturers are actively exploring new avenues to reduce production costs without compromising product quality. To address this challenge, a novel mixed integer nonlinear model is formulated by incorporating internal quality costs, environmental impact considerations, and the impact of buffer size to solve the micro-computer aided process planning problem. The scope covered is limited to milling operations for a part mix involving different materials being machined. Surface roughness is used to evaluate the desired quality level of finish. The internal quality failure cost model, including scrap and rework, is developed based on Taguchi's quadratic loss function. Mathematical programming is employed to validate the results of genetic algorithms (GAs). Because of the nonlinear nature of the model, GAs has been used. Considering strict quality cost measures, the model minimises internal quality-related costs while minimising the environmental impact.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 469-497
Issue: 4
Volume: 51
Year: 2025
Keywords: micro-computer aided process planning; machining parameters; internal failure cost; buffer size; genetic algorithms; mathematical programming.
File-URL: http://www.inderscience.com/link.php?id=150225
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Handle: RePEc:ids:ijisen:v:51:y:2025:i:4:p:469-497
Template-Type: ReDIF-Article 1.0
Author-Name: Nitin Goel
Author-X-Name-First: Nitin
Author-X-Name-Last: Goel
Author-Name: Naresh Kumar Yadav
Author-X-Name-First: Naresh Kumar
Author-X-Name-Last: Yadav
Title: Hybrid optimisation multi-energy demand response prediction model for economic emission dispatch solution-based hybrid optimisation
Abstract:
In this paper, a multi-energy demand response prediction model using an artificial neural network (ANN) and an economic emission dispatch (EDD) solution using a novel optimisation algorithm has been introduced. The trending problem relies on the demand prediction of RES, such as wind, solar, and the IEEE-30 bus system, which is assessed using the ANN classifier. The evaluated values are fed as input to the proposed optimisation algorithm known as the BE-Cro optimisation algorithm. Here, the optimisation variables are controlled to achieve the solution for the EED problem, to reduce the entire cost. The performance of the BE-Cro method is evaluated based on cost of economics, cost of emission, power loss, and total cost. The result depicts that the BE-Cro method is superior in performance when compared to other traditional methods. In future, the analysis will be carried out in IEEE-33 and IEEE-69 bus systems.
Journal: Int. J. of Industrial and Systems Engineering
Pages: 413-434
Issue: 4
Volume: 51
Year: 2025
Keywords: economic emission dispatch; EDD; renewable energy sources; energy demand; IEEE bus; optimisation.
File-URL: http://www.inderscience.com/link.php?id=150242
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Handle: RePEc:ids:ijisen:v:51:y:2025:i:4:p:413-434