Sustainability metrics and a hybrid decision-making model for selecting lean manufacturing tools
The literature review reveals that lean manufacturing tool selection models still have some gaps. These models lack the criteria for selecting LM tools. Only a few of these models adopted hybrid multi-criteria decision-making (MCDM) methods. Obtaining reliable criteria weights in these models is com...
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| Format: | Article |
| Language: | English |
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Elsevier B.V.
2023
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| Online Access: | http://eprints.utm.my/106677/1/WongKuanYew2023_SustainabilityMetricsandaHybridDecisionMaking.pdf |
| _version_ | 1811132390164135936 |
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| author | Al-Allaj, Ali Jaber Naeemah Wong, Kuan Yew |
| author_facet | Al-Allaj, Ali Jaber Naeemah Wong, Kuan Yew |
| author_sort | Al-Allaj, Ali Jaber Naeemah |
| collection | ePrints |
| description | The literature review reveals that lean manufacturing tool selection models still have some gaps. These models lack the criteria for selecting LM tools. Only a few of these models adopted hybrid multi-criteria decision-making (MCDM) methods. Obtaining reliable criteria weights in these models is complicated. They lack the consideration of grey uncertainty. Thus, this study is the first to propose a hybrid model for selecting a set of LM tools based on their effect on sustainability. This model combines the best-worst method (BWM) for weighting the criteria and the grey technique for order of preference by similarity to the ideal solution (Grey-TOPSIS) method to rank the alternatives and address the grey uncertainty problem. A set of sustainability metrics (selection criteria) was determined based on a literature review and expert evaluation to prioritize a set of LM tools. An Iraqi cement company was utilized to evaluate the proposed model. The ranking results showed that the value stream mapping (VSM) tool was the most important, whereas the single-minute exchange of die (SMED) tool was the least important. The rankings of the remaining LM tools ranged between these two tools depending on their effects on sustainability. The study conducted a sensitivity analysis using three strategies that verified the model's robustness and reliability. This research provides 16 applicable sustainability metrics and 12 LM tools that could function as a knowledge foundation for future research. It can help researchers and manufacturers maximize sustainability performance by delivering a hybrid MCDM model to select the appropriate LM tools. |
| first_indexed | 2024-09-24T00:03:16Z |
| format | Article |
| id | utm.eprints-106677 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-09-24T00:03:16Z |
| publishDate | 2023 |
| publisher | Elsevier B.V. |
| record_format | dspace |
| spelling | utm.eprints-1066772024-07-14T09:40:02Z http://eprints.utm.my/106677/ Sustainability metrics and a hybrid decision-making model for selecting lean manufacturing tools Al-Allaj, Ali Jaber Naeemah Wong, Kuan Yew TJ Mechanical engineering and machinery The literature review reveals that lean manufacturing tool selection models still have some gaps. These models lack the criteria for selecting LM tools. Only a few of these models adopted hybrid multi-criteria decision-making (MCDM) methods. Obtaining reliable criteria weights in these models is complicated. They lack the consideration of grey uncertainty. Thus, this study is the first to propose a hybrid model for selecting a set of LM tools based on their effect on sustainability. This model combines the best-worst method (BWM) for weighting the criteria and the grey technique for order of preference by similarity to the ideal solution (Grey-TOPSIS) method to rank the alternatives and address the grey uncertainty problem. A set of sustainability metrics (selection criteria) was determined based on a literature review and expert evaluation to prioritize a set of LM tools. An Iraqi cement company was utilized to evaluate the proposed model. The ranking results showed that the value stream mapping (VSM) tool was the most important, whereas the single-minute exchange of die (SMED) tool was the least important. The rankings of the remaining LM tools ranged between these two tools depending on their effects on sustainability. The study conducted a sensitivity analysis using three strategies that verified the model's robustness and reliability. This research provides 16 applicable sustainability metrics and 12 LM tools that could function as a knowledge foundation for future research. It can help researchers and manufacturers maximize sustainability performance by delivering a hybrid MCDM model to select the appropriate LM tools. Elsevier B.V. 2023-09 Article PeerReviewed application/pdf en http://eprints.utm.my/106677/1/WongKuanYew2023_SustainabilityMetricsandaHybridDecisionMaking.pdf Al-Allaj, Ali Jaber Naeemah and Wong, Kuan Yew (2023) Sustainability metrics and a hybrid decision-making model for selecting lean manufacturing tools. Resources, Environment and Sustainability, 13 (NA). pp. 1-24. ISSN 2666-9161 http://dx.doi.org/10.1016/j.resenv.2023.100120 DOI:10.1016/j.resenv.2023.100120 |
| spellingShingle | TJ Mechanical engineering and machinery Al-Allaj, Ali Jaber Naeemah Wong, Kuan Yew Sustainability metrics and a hybrid decision-making model for selecting lean manufacturing tools |
| title | Sustainability metrics and a hybrid decision-making model for selecting lean manufacturing tools |
| title_full | Sustainability metrics and a hybrid decision-making model for selecting lean manufacturing tools |
| title_fullStr | Sustainability metrics and a hybrid decision-making model for selecting lean manufacturing tools |
| title_full_unstemmed | Sustainability metrics and a hybrid decision-making model for selecting lean manufacturing tools |
| title_short | Sustainability metrics and a hybrid decision-making model for selecting lean manufacturing tools |
| title_sort | sustainability metrics and a hybrid decision making model for selecting lean manufacturing tools |
| topic | TJ Mechanical engineering and machinery |
| url | http://eprints.utm.my/106677/1/WongKuanYew2023_SustainabilityMetricsandaHybridDecisionMaking.pdf |
| work_keys_str_mv | AT alallajalijabernaeemah sustainabilitymetricsandahybriddecisionmakingmodelforselectingleanmanufacturingtools AT wongkuanyew sustainabilitymetricsandahybriddecisionmakingmodelforselectingleanmanufacturingtools |