Machine selection for inventory tracking with a continuous intuitionistic fuzzy approach

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dc.authoridDOGAN, ONUR/0000-0003-3543-4012
dc.contributor.authorCebeci, Ufuk
dc.contributor.authorSimsir, Ugur
dc.contributor.authorDoğan, Onur
dc.date.accessioned2025-03-20T09:50:32Z
dc.date.available2025-03-20T09:50:32Z
dc.date.issued2025
dc.departmentİzmir Bakırçay Üniversitesi
dc.description.abstractToday, businesses are adopting digital transformation strategies to make their production processes more agile, efficient, and sustainable. At the same time, lean manufacturing principles aim to create value by reducing waste in production processes. In this context, it is important that the machine to be selected for inventory tracking can meet both the technological features suitable for digital transformation goals and the operational efficiency criteria required by lean manufacturing. In this study, multi-criteria decision-making methods were used to select the most suitable machine for inventory tracking based on digital transformation and lean manufacturing perspectives. This study applies a framework that integrates the Continuous Intuitionistic Fuzzy Analytic Hierarchy Process (CINFU AHP) and the Continuous Intuitionistic Fuzzy Combinative Distance-Based Assessment (CINFU CODAS) methods to select the most suitable machine for inventory tracking. The framework contributes to lean manufacturing by providing actionable insights and robust sensitivity analyses, ensuring decision-making reliability under fluctuating conditions. The CINFU AHP method determines the relative importance of each criterion by incorporating expert opinions. Six criteria, Speed (C1), Setup Time (C2), Ease to Operate and Move (C3), Ability to Handle Multiple Operations (C4), Maintenance and Energy Cost (C5), and Lifetime (C6), were considered in the study. The most important criteria were C1 and C4, with scores of 0.25 and 0.23, respectively. Following the criteria weighting, the CINFU CODAS method ranks the alternative machines based on their performance across the weighted criteria. Four alternative machines (High-Speed Automated Scanner (A1), Multi-Functional Robotic Arm (A2), Mobile Inventory Tracker (A3), and Cost-Efficient Fixed Inventory Counter (A4)) are evaluated based on the criteria selected. The results indicate that Alternative A1 ranked first because of its superior speed and operational efficiency, while Alternative A3 ranked last due to its high initial cost despite being cost-effective. Finally, a sensitivity analysis further examines the impact of varying criteria weights on the alternative rankings. Quantitative findings demonstrate how the applied CINFU AHP&CODAS methodology influenced the rankings of alternatives and their sensitivity to criteria weights. The results revealed that C1 and C4 were the most essential criteria, and Machine A2 outperformed others under varying weights. Sensitivity results indicate that the changes in criterion weights may affect the alternative ranking.
dc.identifier.doi10.3390/app15010425
dc.identifier.issn2076-3417
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85214496614
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.3390/app15010425
dc.identifier.urihttps://hdl.handle.net/20.500.14034/2245
dc.identifier.volume15
dc.identifier.wosWOS:001393476800001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherMDPI
dc.relation.ispartofApplied Sciences-Basel
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250319
dc.subjectcinfu ahp
dc.subjectcinfu codas
dc.subjectMDCM
dc.subjectmachine selection
dc.subjectinventory tracking
dc.titleMachine selection for inventory tracking with a continuous intuitionistic fuzzy approach
dc.typeArticle

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