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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2503.21832 |
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| _version_ | 1866915217482448896 |
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| author | Nur, Gazi Nazia Sadat, Mohammad Ahnaf Shahriar, Basit Mahmud |
| author_facet | Nur, Gazi Nazia Sadat, Mohammad Ahnaf Shahriar, Basit Mahmud |
| contents | In this paper, we address the inherent limitations in traditional assembly line balancing, specifically the assumptions that task times are constant and no defective outputs occur. These assumptions often do not hold in practical scenarios, leading to inefficiencies. To address these challenges, we introduce a framework utilizing an "adjusted processing time" approach based on the distributional information of both processing times and defect occurrences. We validate our framework through the analysis of two case studies from existing literature, demonstrating its robustness and adaptability. Our framework is characterized by its simplicity, both in understanding and implementation, marking a substantial advancement in the field. It presents a viable and efficient solution for industries seeking to enhance operational efficiency through improved resource allocation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_21832 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Assembly line balancing considering stochastic task times and production defects Nur, Gazi Nazia Sadat, Mohammad Ahnaf Shahriar, Basit Mahmud Performance 62P30 G.1.10; G.3 In this paper, we address the inherent limitations in traditional assembly line balancing, specifically the assumptions that task times are constant and no defective outputs occur. These assumptions often do not hold in practical scenarios, leading to inefficiencies. To address these challenges, we introduce a framework utilizing an "adjusted processing time" approach based on the distributional information of both processing times and defect occurrences. We validate our framework through the analysis of two case studies from existing literature, demonstrating its robustness and adaptability. Our framework is characterized by its simplicity, both in understanding and implementation, marking a substantial advancement in the field. It presents a viable and efficient solution for industries seeking to enhance operational efficiency through improved resource allocation. |
| title | Assembly line balancing considering stochastic task times and production defects |
| topic | Performance 62P30 G.1.10; G.3 |
| url | https://arxiv.org/abs/2503.21832 |