2026-06-09T20:40:29+03:30 http://ijiepr.iust.ac.ir/browse.php?mag_id=83&slc_lang=en&sid=1

83-2152 2026-06-09 10.1002

International Journal of Industrial Engineering & Production Research IJIEPR 2008-4889 2345-363X 2025 36 2 Tenaw Tegbar Tsega tenaw.tegbar@bdu.edu.et Thoben Klaus-Dieter tho@biba.uni-bremen.de Rao D.K. Nageswara dk.rao@bdu.edu.et Bereket Haile Woldegiorgis bereket.haile@bdu.edu.et So far, several models for measuring supply chain performance (SCP) have been developed. The supply chain operation reference (SCOR) model is regarded as the most crucial in the manufacturing business. However, none of the models, including the SCOR model, are comprehensive enough to measure the overall SCP of manufacturing firms. In practice, the existing models are only used in a few of the numerous steps necessary to calculate the overall SCP. Furthermore, the existing models lack fundamental elements that a model should include. The objective of this research is to develop a powerful SCP measurement using a systematic literature review (SLR). Accordingly, this research has proposed a complete supply chain operations measurement (C-SCOM) model. The proposed model consists of four major components: the application of the SCOR model, the application of the AHP method, a template that enables overall SCP calculation, and a direction for linking supply chain management practices (SCMPS) with gap analysis. By having these features, the model provides users with the ability to calculate the overall SCP, conduct gap analysis, carry out benchmarking, and link the gap analysis outputs to existing SCMPs, which the previous models lack. The validation using the fuzzy Delphi technique reveals that the proposed model is unique in its explicitness and will be user-friendly for real-world industrial applications. Finally, this study contributes to the body of knowledge by providing a comprehensive model that could help solve the real challenges that manufacturing firms face when measuring SCP. Supply chain operations measurement model Complete supply chain operations measurement model C-SCOM model Manufacturing supply chain performance Supply chain performance measurement 2025 6 01 1 28 http://ijiepr.iust.ac.ir/article-1-2152-en.pdf 10.22068/ijiepr.36.2.2152

83-2072 2026-06-09 10.1002

International Journal of Industrial Engineering & Production Research IJIEPR 2008-4889 2345-363X 2025 36 2 Khatereh Rajinia kh.rajinia@mail.um.ac.ir Mostafa Razmkhah razmkhah_m@um.ac.ir A periodic maintenance policy through either an imperfect repair or replacement is proposed for a repairable system. It is assumed that the system is subject to an inverse Gaussian degradation process. The effect of imperfect repair is modelled through both arithmetic reduction of degradation and arithmetic reduction of age approaches. The degradation level of the system is measured after each imperfect repair in periodic time intervals. The system is replaced if its deterioration level exceeds a pre-determined technical threshold or at the nth inspection time, whichever occurs first. The main goal of the paper is to find the optimal value of n based on expected cost rate function. Some theoretical results are derived and then the optimal policy is obtained numerically. The effect of imperfect repair, the inspection time interval, the value of technical degradation threshold, and the costs of interest are all studied on the optimal policy. Cost function Inverse Gaussian process Maintenance Reduction of degradation (age) model 2025 6 01 29 38 http://ijiepr.iust.ac.ir/article-1-2072-en.pdf 10.22068/ijiepr.36.2.2072

83-2302 2026-06-09 10.1002

International Journal of Industrial Engineering & Production Research IJIEPR 2008-4889 2345-363X 2025 36 2 Nadera Hourani nalhourani@kau.edu.sa Artificial intelligence (AI) has been integrated into human resource management (HRM), enabling the transformation of the field through routine job automation, decision-making enhancement, and evidence-based strategies. This article will systematically review the role of AI in HRM, focusing on applications related to recruitment, employee engagement, workforce planning, and retention. This systematic review article underlines the significant benefits of AI adoption by analyzing ten peer-reviewed studies using advanced statistical analysis. These benefits include efficiency gains, increased employee satisfaction, and strategic workforce optimization. Yet, there are significant challenges in the form of algorithmic bias, data privacy concerns, and organizational readiness. Regression and correlation analyses show a strong positive relationship between AI use and HR performance metrics, with a greater effect on recruitment and retention. Though AI has a huge potential for transformation, the findings have brought into focus the need for ethical guidelines, strong data protection, and employee upskilling for the full realization of AI's capabilities in HRM. Thus, this study provides practical insights for organizations seeking to adopt AI technologies while addressing the associated challenges.   Artificial Intelligence (AI) Human Resource Management (HRM) Workforce Analytics Employee Engagement Recruitment Retention Algorithmic Bias Data Privacy. 2025 6 01 39 51 http://ijiepr.iust.ac.ir/article-1-2302-en.pdf 10.22068/ijiepr.36.2.2302

83-2234 2026-06-09 10.1002

International Journal of Industrial Engineering & Production Research IJIEPR 2008-4889 2345-363X 2025 36 2 Mehdi Abdollahi Kamran mehdi.kamran@gutech.edu.om Samira Afsharfar samira.afsharfar@gutech.edu.om Fatma Al Mawali Al_Mawali345@gmail.com Reza Babazadeh r.babazadeh@urmia.ac.ir Marya Al Balushi marya.albalushi@gutech.edu.om One of the most critical concerns in supply chain management (SCM) is supplier selection, which significantly impacts an organization's efficiency and market agility. Balancing ordinal and basic criteria in supplier selection has become increasingly crucial in recent years within SCM. This research presents three multi-criteria decision-making (MCDM) methods including Fuzzy analytic hierarchy process (AHP) and Fuzzy technique for order preference by similarity to ideal solution (TOPSIS) methods to assess and select suppliers in oil and gas (O&G) industry. The critical criteria for supplier selection in the O&G sector have been reviewed in the literature and validated by experts actively working in the field. Initially, the Fuzzy AHP technique determines criterion weights and ranks suppliers. Subsequently, the Fuzzy TOPSIS approach is applied to rank prospective suppliers identified through objective evaluation. The findings show the capability of the utilized approaches in supplier selection procedure in O&G industry. Supplier Selection Oil and Gas Industry Fuzzy AHP Fuzzy TOPSIS MCDM 2025 6 01 52 67 http://ijiepr.iust.ac.ir/article-1-2234-en.pdf 10.22068/ijiepr.36.2.2234

83-2271 2026-06-09 10.1002

International Journal of Industrial Engineering & Production Research IJIEPR 2008-4889 2345-363X 2025 36 2 SOUAD LAHMINE souad.lahmine@usmba.ac.ma FATIMA BENNOUNA Fatima.bennouna@usmba.ac.ma Quality 4.0 is the fusion between the long-standing quality management tenets and Industry 4.0 technologies like AI, Blockchain, IoT, and Big Data. Although it can improve product quality, control operational efficiency, and supply chain transparency for organizations, adopting these technologies comes with high challenges. This study, therefore, carries out a meta-analytic review incorporating 80 peer-reviewed papers from between 2018 to 2024 to exposit the effectiveness, challenges, and prospects of Quality 4.0. Results show that machine learning-based predictive analytics significantly reduce defect rates and production costs, while Blockchain enhances visibility into the supply chain. On the other hand, organizational readiness and workforce training are major barriers. The paper can give much-needed input to practitioners through actionable recommendations and suggest avenues for further research that would advance Quality 4.0 adoption. Quality 4.0 Industry 4.0 AI Blockchain Big Data IoT. 2025 6 01 68 79 http://ijiepr.iust.ac.ir/article-1-2271-en.pdf 10.22068/ijiepr.36.2.2271

83-2088 2026-06-09 10.1002

International Journal of Industrial Engineering & Production Research IJIEPR 2008-4889 2345-363X 2025 36 2 Saeed Dehnavi-Arani dehnavi@kashanu.ac.ir Hadi Mokhtari mokhtari_ie@kashanu.ac.ir The selection of material handling equipment is crucial for companies as it significantly impacts productivity in manufacturing and service operations. This decision-making process involves multiple criteria that are often conflicting and cannot be easily compared. To address this complexity, a multi-criteria decision-making framework is employed, where experts' preferences and criteria weights are expressed using fuzzy numbers, such as trapezoidal or triangular fuzzy numbers. The fuzzy VIKOR methodology is then utilized to rank the alternatives based on the aggregate fuzzy values of ratings and weights. A Monte Carlo simulation and a centroid method are employed to derive a suitable shape and obtain a precise value. This additional step enhances the robustness and accuracy of the decision-making process. To demonstrate the effectiveness of this approach, a case study is conducted at R.S-Arvin, a manufacturing company. By applying the proposed methodology to a real-world scenario, the study showcases how it can be used to make informed decisions in practical settings. The results obtained from this case study highlight the benefits of incorporating fuzzy logic and simulation techniques in material handling equipment selection processes. Overall, this research contributes to advancing decision-making practices in companies by providing a systematic and comprehensive approach that considers multiple criteria and uncertainties inherent in such complex systems. The integration of fuzzy logic and defuzzification methods (simulation and centroid method) offers a practical solution for addressing real-world challenges related to equipment selection and optimization in manufacturing environments. Material handling equipment Fuzzy set Multi-criteria decision making Fuzzy VIKOR Monte Carlo simulation 2025 6 01 80 95 http://ijiepr.iust.ac.ir/article-1-2088-en.pdf 10.22068/ijiepr.36.2.2088

83-2249 2026-06-09 10.1002

International Journal of Industrial Engineering & Production Research IJIEPR 2008-4889 2345-363X 2025 36 2 Weny Findiastuti weny.findiastuti@trunojoyo.ac.id Fitri Agustina fitri.agustina@trunojoyo.ac.id Rullie Annisa rullie.annisa@trunojoyo.ac.id Ach Dafid ach.dafid@trunojoyo.ac.id Iffan Maflahah iffanmaflahah@trunojoyo.ac.id Ananda Rafli Siswanto 200421100027@student.trunojoyo.ac.id Indonesia faces environmental challenges due to the increasing exploitation of natural resources and industrial emissions. This study aims to design an environmental impact mitigation strategy in the furniture industry using the Life Cycle Assessment (LCA) method, with a case study of UD Putra Bali. The analysis includes the Life Cycle Inventory (LCI), Life Cycle Impact Assessment (LCIA), and Life Cycle Interpretation to identify the greatest impacts and develop recommendations for improvement. The results of the study indicate that the life cycle of wooden door products produces an environmental impact of 13.1 kPt. The stage with the greatest impact is the finishing process, especially in the human toxicity water category of 11.3 kPt, due to thinner-based paint. In addition, the delivery of finished products contributes to the global warming category of 0.0539 kPt, which is caused by the use of vehicles with high emission specifications and inefficient delivery routes. Recommendations for improvement include the implementation of cleaner production, namely replacing thinner-based paint with more environmentally friendly water-based paint and optimizing delivery routes using the saving matrix nearest insert method to reduce the total distance traveled and transportation emissions. After the implementation of the mitigation strategy, the environmental impact of the finishing process decreased to 10.3 kPt, while the impact of the finished product delivery decreased to 0.0526 kPt. This study shows that the application of LCA can identify the main sources of environmental impacts and generate data-based improvement strategies. The implementation of this strategy is expected to enhance the sustainability of the furniture industry and reduce the production process's environmental footprint. Green productivity Environmental impact Life cycle assessment Cleaner production Savings matrix. 2025 6 01 96 115 http://ijiepr.iust.ac.ir/article-1-2249-en.pdf 10.22068/ijiepr.36.2.2249

83-2153 2026-06-09 10.1002

International Journal of Industrial Engineering & Production Research IJIEPR 2008-4889 2345-363X 2025 36 2 Mehdi Ajalli m.ajalli@basu.ac.ir Narges Soleiman Ekhtiyari 288841@student.pwr.edu.pl Peyman Zandi peyman.zandi@pwr.edu.pl This study aims to evaluate the traditional, lean and agility criteria that are effective in evaluating the performance of suppliers and ranking them with the combined approach Path Analysis (PA), SWARA (Stepwise Weight Assessment Ratio Analysis) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) in Automation Industry. The research method is applied from the perspective of the objective and is descriptive-survey in terms of data collection. For this purpose, the sub-criteria were first extracted by reviewing the literature. Then, using PA approach, the effectiveness of these criteria in automation industry was investigated. The statistical population in this section includes 60 experts and managers of the industry, which due to the smal size, all members of the community were considered as a sample. The PA output showed that after evaluating twentycriteria, seventeen criteria were finally approved by the experts. Then, using the SWARA and the opinions of experts, the criteria importance and weight was calculated. The results showed that the criterion of "agility" was in the first place, "lean" was in the second place and "traditional" was in the last place. Then, considering the importance of ranking of lean and agile suppliers in the industry, using TOPSIS and based on the weight of the criteria, six suppliers were evaluated by experts. The results showed that the fourth supplier was ranked first. The first supplier was also ranked sixth. Finally, a sensitivity analysis of the ranking was conducted. Overall, the results show a high degree of stability of the rankings according to the method used. Thus, the model proposed in this study provides a suitable framework for evaluating industry suppliers based on key criteria of traditional, lean and agility. Leanness Agility Path Analysis SWARA TOPSIS 2025 6 01 116 129 http://ijiepr.iust.ac.ir/article-1-2153-en.pdf 10.22068/ijiepr.36.2.2153

83-1911 2026-06-09 10.1002

International Journal of Industrial Engineering & Production Research IJIEPR 2008-4889 2345-363X 2025 36 2 Dino Caesaron dinocaesaron@telkomuniversity.ac.id Farell Ardani farellardani@gmail.com Vidhea Nurhadi vidheanurhadi@gmail.com Yusuf Yekti doyoyekti@telkomuniversity.ac.id A typical definition of New Product Development is a series of actions that begins with the identification of a market opportunity and concludes with the creation, marketing, and delivery of a product. It is a knowledge-based process where constraints and needs are converted into a product description. The competition for businesses now centers on innovation and new products. Industries and investors are constantly looking for new upgrade methods and/or equipment to reduce costs and increase capability. One industry in Indonesia that has a tight competitive level is the ceramics industry with a growth rate of 10% per year. The main objective of this study was to create the design of specific machining sanitary Spare Parts production due to complexity of the design. In the proposed methodology, Quality Function Deployment is used to convert the subjective requirements from users into an objective technical response. Theory of Solving Problem Inventively is used to enhance the subpar design by reducing system conflicts and creating a balanced solution between two requirements. The implications of the integration of Quality Function Deployment and Theory of Solving Problem Inventively in this paper are a product design and concept of the specific machining for sanitary spare parts that have been adjusted to the needs of users. Product Design and Development New Product Development Theory of Solving Problem Inventively Quality Function Deployment House of Quality 2025 6 01 130 140 http://ijiepr.iust.ac.ir/article-1-1911-en.pdf 10.22068/ijiepr.36.2.1911

83-2182 2026-06-09 10.1002

International Journal of Industrial Engineering & Production Research IJIEPR 2008-4889 2345-363X 2025 36 2 Hendro Prassetiyo prasshendro@itenas.ac.id Said Muhammad Baisa Saidbaisa175@gmail.com Arif Imran imran@itenas.ac.id Sri Suci Yuniar suciyuniar7@gmail.com Rangga Try Anugrah tryrangga1060@gmail.com This study focuses on optimizing vendor selection in laser cutting services through a comprehensive evaluation framework integrating the Vendor Performance Indicator (VPI) and the Fuzzy Analytical Network Process (F-ANP). The methodology quantifies vendor performance across five key criteria: quality, cost, delivery, flexibility, and responsiveness. The results indicate that product quality (39.7%) and cost efficiency (41.4%) are the most influential factors in vendor selection. Sensitivity analysis reveals that a 10% increase in quality consistency improves overall vendor ranking stability by 15%, while cost variations above 8% significantly affect final rankings. The study recommends implementing performance-based contracts, quality assurance protocols, and digital supply chain solutions to enhance vendor assessments. Collaborative partnerships with top-performing vendors can yield mutual benefits and foster sustainable practices, aligning with the company's resilience and operational excellence objectives. Vendor Evaluation Fuzzy Analytical Network Process Supplier Performance Vendor Selection Criteria laser cutting service 2025 6 01 141 155 http://ijiepr.iust.ac.ir/article-1-2182-en.pdf 10.22068/ijiepr.36.2.2182

83-2274 2026-06-09 10.1002

International Journal of Industrial Engineering & Production Research IJIEPR 2008-4889 2345-363X 2025 36 2 Davood Nazari Maryam Abadi d.nazari@grandmaghsoud.com Mohammad Bagheri m.bagheri@grandmaghsoud.com In this paper, an optimal Electrical Cam (Ecam) profile is obtained by identifying the best breakpoint positions for piecewise polynomials using the cubic spline interpolation method. To achieve a curve that best tracks the reference Ecam curve, the breakpoint positions are determined using particle swarm optimization with random inertia weight (RNW-PSO). The previous programmable logic controller (PLC) used in the sanding mechanism was the DELTA DVP40ES2, utilizing the Ecam capability of DELTA ASD-A2 servo motors. To implement the Ecam function independently of the servo motor type, it has been integrated into a PLC, specifically the SIEMENS SIMATIC CPU 1215C. The optimized Ecam curve is then applied to a computer numerical control (CNC) sanding machine. Practical results demonstrate the effectiveness of the proposed method, showing improved sanding quality and better compliance with the reference curve. Cubic Spline Interpolation Ecam CNC sanding machine RNW–PSO 2025 6 01 156 169 http://ijiepr.iust.ac.ir/article-1-2274-en.pdf 10.22068/ijiepr.36.2.2274

83-2111 2026-06-09 10.1002

International Journal of Industrial Engineering & Production Research IJIEPR 2008-4889 2345-363X 2025 36 2 Ahmad Aliyari Boroujeni a.aliyari@znu.ac.ir Ameneh Khadivar a.khadivar@alzahra.ac.ir The Traveling Salesman Problem (TSP) is a well-known problem in optimization and graph theory, where finding the optimal solution has always been of significant interest. Optimal solutions to TSP can help reduce costs and increase efficiency across various fields. Heuristic algorithms are often employed to solve TSP, as they are more efficient than exact methods due to the complexity and large search space of the problem. In this study, meta-heuristic algorithms such as the Genetic Algorithm and the Teaching-Learning Based Optimization (TLBO) algorithm are used to solve the TSP. Additionally, a discrete mutation phase is introduced to the TLBO algorithm to enhance its performance in solving the TSP. The results indicate that, in testing two specific models of the TSP, the modified TLBO algorithm outperforms both the Genetic Algorithm and the standard TLBO algorithm in terms of convergence to the optimal solution and response time. Traveling Salesman problem Modified Teaching-Learning Based Optimization Meta-heuristic algorithms Graph theory 2025 6 01 170 184 http://ijiepr.iust.ac.ir/article-1-2111-en.pdf 10.22068/ijiepr.36.2.2111

83-2155 2026-06-09 10.1002

International Journal of Industrial Engineering & Production Research IJIEPR 2008-4889 2345-363X 2025 36 2 Ahmad Mohammadpour Larimi amp.larimi@gmail.com Babak Shirazi shirazi_b@icloud.com Iraj Mahdavi irajarash@rediffmail.com location-inventory problem (LIP) is a significant issue in supply chain management (SCM), aiming to reduce and integrate the costs of inventory and location. Perishable-LIP (PLIP) includes products, particularly those with a short expiration date, also known as perishable items. This feature necessitates the supply chain to maintain high reliability and resilience to minimize costs faced with disruption risks. Implementing reliability and resilience in PLIP (R2-PLIP) requires methods such as lateral transshipment. These methods not only enhance the reliability and resiliency of the SC but also mitigate the risks associated with supply disruptions and demand fluctuations. Demand for perishable products is influenced by their expiration dates. By incorporating lateral transshipment, companies can ensure a more balanced inventory distribution. This study investigates the role of lateral transshipment in enhancing supply chain robustness. A multi-objective optimization model is developed, focusing on minimizing costs while maximizing resilience and service levels. The project aims to optimize the overall system efficiency. Additionally, the sensitivity analysis conducted in the research indicates that the shortage cost and the DC capacity each had the greatest variations in one of the objective functions. This research provides practical insights for designing resilient perishable supply chains.   Location-Inventory Problem Resiliency Lateral transshipment Disruption Risk Perishability multi-objective optimization 2025 6 01 185 200 http://ijiepr.iust.ac.ir/article-1-2155-en.pdf 10.22068/ijiepr.36.2.2155

83-2222 2026-06-09 10.1002

International Journal of Industrial Engineering & Production Research IJIEPR 2008-4889 2345-363X 2025 36 2 Alemayehu Derege alemayehu.ethiopia@astu.edu.et The booming of construction sector, including cement factories, has been great success, however, the price of cement has been quadrupled. Among others, critical shortage of cement is observed throughout the country regardless of the success, demanding a critical investigation into its supply chain, governance and regulatory system. Mixed, qualitative and quantitative approaches are applied to investigate the value chain, its administration and regulatory framework. SEM was used to index the level of cement supply distortions in the country.  Samples are taken through referral technique from stratified target group across Ethiopian cement supply chain, starting from factory CEO to end-users, from purposively selected major factories. Multinomial logit model is used to analyze the determinant of cement supply distortion. The study found mis-management of regulation, high intervention with ineffective regulatory measure, opened up a room for bribery, favoritism, government interventionism and amplified the roles of intermediaries beyond the market requirement. Brokers are involved in about 85 percent of the country's total cement distribution. Besides, not only intermediaries but also the factories and their agents are contributing a lot in cement supply distortion. The supply chain distortion is observed in all market types, black, gray, and white respectively. The regulatory framework is ineffective and few regulatory bodies are fixed towards reactive measures. Majority of cement distribution is facilitated by brokers and factory agent. Hoarding and smuggling emerge as the most influential factors, with their increase being strongly and significantly linked to a rise in high and severe illegal cement distribution. Regulatory strength and administrative malpractice display complex patterns, indicating that having policies in place is not sufficient; effective enforcement is crucial. Strengthening regulatory, good governance and law enforcement system reduces the cement supply distortion while long run digitalization should be targeted along with supply side intervention. Cement Supply Distortion Supply Chain Regulatory Measure Good Governance Ethiopia 2025 6 01 201 213 http://ijiepr.iust.ac.ir/article-1-2222-en.pdf 10.22068/ijiepr.36.2.2222