Machine Selection for Inventory Tracking with a Continuous Intuitionistic Fuzzy Approach
Today, 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...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/1/425 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841549391973842944 |
|---|---|
| author | Ufuk Cebeci Ugur Simsir Onur Dogan |
| author_facet | Ufuk Cebeci Ugur Simsir Onur Dogan |
| author_sort | Ufuk Cebeci |
| collection | DOAJ |
| description | Today, 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. |
| format | Article |
| id | doaj-art-eebefde3e8aa4962baf6e2437a487d0d |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-eebefde3e8aa4962baf6e2437a487d0d2025-01-10T13:15:31ZengMDPI AGApplied Sciences2076-34172025-01-0115142510.3390/app15010425Machine Selection for Inventory Tracking with a Continuous Intuitionistic Fuzzy ApproachUfuk Cebeci0Ugur Simsir1Onur Dogan2Department of Industrial Engineering, Istanbul Technical University, 34367 Istanbul, TürkiyeMilteksan CNC A.S., Basibuyuk Mh. Sureyyapaşa Basibuyuk Yolu Sk. No:4/1, 34854 Istanbul, TürkiyeDepartment of Mathematics, University of Padua, 35131 Padua, ItalyToday, 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.https://www.mdpi.com/2076-3417/15/1/425cinfu ahpcinfu codasMDCMmachine selectioninventory tracking |
| spellingShingle | Ufuk Cebeci Ugur Simsir Onur Dogan Machine Selection for Inventory Tracking with a Continuous Intuitionistic Fuzzy Approach Applied Sciences cinfu ahp cinfu codas MDCM machine selection inventory tracking |
| title | Machine Selection for Inventory Tracking with a Continuous Intuitionistic Fuzzy Approach |
| title_full | Machine Selection for Inventory Tracking with a Continuous Intuitionistic Fuzzy Approach |
| title_fullStr | Machine Selection for Inventory Tracking with a Continuous Intuitionistic Fuzzy Approach |
| title_full_unstemmed | Machine Selection for Inventory Tracking with a Continuous Intuitionistic Fuzzy Approach |
| title_short | Machine Selection for Inventory Tracking with a Continuous Intuitionistic Fuzzy Approach |
| title_sort | machine selection for inventory tracking with a continuous intuitionistic fuzzy approach |
| topic | cinfu ahp cinfu codas MDCM machine selection inventory tracking |
| url | https://www.mdpi.com/2076-3417/15/1/425 |
| work_keys_str_mv | AT ufukcebeci machineselectionforinventorytrackingwithacontinuousintuitionisticfuzzyapproach AT ugursimsir machineselectionforinventorytrackingwithacontinuousintuitionisticfuzzyapproach AT onurdogan machineselectionforinventorytrackingwithacontinuousintuitionisticfuzzyapproach |