Fabrication runtime decision for a hybrid system incorporating probabilistic breakdowns, scrap, and overtime
Manufacturers today need to optimize their fabrication runtime decision by meeting short customer order due dates externally and managing the potentially unreliable machines and manufacturing processes internally. Outsourcing and overtime are commonly utilized strategies to expedite fabrica...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Growing Science
2022-01-01
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| Series: | International Journal of Industrial Engineering Computations |
| Online Access: | http://www.growingscience.com/ijiec/Vol13/IJIEC_2022_10.pdf |
| _version_ | 1818008972968329216 |
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| author | Yuan-Shyi Peter Chiu Yunsen Wang Tsu-Ming Yeh Singa Wang Chiu |
| author_facet | Yuan-Shyi Peter Chiu Yunsen Wang Tsu-Ming Yeh Singa Wang Chiu |
| author_sort | Yuan-Shyi Peter Chiu |
| collection | DOAJ |
| description | Manufacturers today need to optimize their fabrication runtime decision by meeting short customer order due dates externally and managing the potentially unreliable machines and manufacturing processes internally. Outsourcing and overtime are commonly utilized strategies to expedite fabricating time. Additionally, detailed analyses and necessary actions on inevitable product defects (i.e., removal of scraps) and equipment breakdowns (such as machine repairing) are prerequisites to fabrication runtime planning. Motivated by assisting today’s manufacturers decide the best batch runtime plan under the situations mentioned above, this study applies mathematical modeling to a hybrid fabrication problem that incorporates partial overtime and outsourcing, inevitable product defects, and a Poisson-distributed breakdown. We develop a model to accurately represent the problem’s characteristics. Formulations and detailed model analyses allow us to find the cost function first. Differential equations and algorithms help us confirm the gain function’s convexity and find the best runtime decision. Lastly, we use numerical illustrations to show our study’s applicability by revealing in-depth crucial managerial information of the studied problem. |
| first_indexed | 2024-04-14T05:37:00Z |
| format | Article |
| id | doaj.art-da105a95dbe742c28af2bed354498403 |
| institution | Directory Open Access Journal |
| issn | 1923-2926 1923-2934 |
| language | English |
| last_indexed | 2024-04-14T05:37:00Z |
| publishDate | 2022-01-01 |
| publisher | Growing Science |
| record_format | Article |
| series | International Journal of Industrial Engineering Computations |
| spelling | doaj.art-da105a95dbe742c28af2bed3544984032022-12-22T02:09:37ZengGrowing ScienceInternational Journal of Industrial Engineering Computations1923-29261923-29342022-01-0113329330810.5267/j.ijiec.2022.4.001Fabrication runtime decision for a hybrid system incorporating probabilistic breakdowns, scrap, and overtimeYuan-Shyi Peter ChiuYunsen WangTsu-Ming YehSinga Wang Chiu Manufacturers today need to optimize their fabrication runtime decision by meeting short customer order due dates externally and managing the potentially unreliable machines and manufacturing processes internally. Outsourcing and overtime are commonly utilized strategies to expedite fabricating time. Additionally, detailed analyses and necessary actions on inevitable product defects (i.e., removal of scraps) and equipment breakdowns (such as machine repairing) are prerequisites to fabrication runtime planning. Motivated by assisting today’s manufacturers decide the best batch runtime plan under the situations mentioned above, this study applies mathematical modeling to a hybrid fabrication problem that incorporates partial overtime and outsourcing, inevitable product defects, and a Poisson-distributed breakdown. We develop a model to accurately represent the problem’s characteristics. Formulations and detailed model analyses allow us to find the cost function first. Differential equations and algorithms help us confirm the gain function’s convexity and find the best runtime decision. Lastly, we use numerical illustrations to show our study’s applicability by revealing in-depth crucial managerial information of the studied problem.http://www.growingscience.com/ijiec/Vol13/IJIEC_2022_10.pdf |
| spellingShingle | Yuan-Shyi Peter Chiu Yunsen Wang Tsu-Ming Yeh Singa Wang Chiu Fabrication runtime decision for a hybrid system incorporating probabilistic breakdowns, scrap, and overtime International Journal of Industrial Engineering Computations |
| title | Fabrication runtime decision for a hybrid system incorporating probabilistic breakdowns, scrap, and overtime |
| title_full | Fabrication runtime decision for a hybrid system incorporating probabilistic breakdowns, scrap, and overtime |
| title_fullStr | Fabrication runtime decision for a hybrid system incorporating probabilistic breakdowns, scrap, and overtime |
| title_full_unstemmed | Fabrication runtime decision for a hybrid system incorporating probabilistic breakdowns, scrap, and overtime |
| title_short | Fabrication runtime decision for a hybrid system incorporating probabilistic breakdowns, scrap, and overtime |
| title_sort | fabrication runtime decision for a hybrid system incorporating probabilistic breakdowns scrap and overtime |
| url | http://www.growingscience.com/ijiec/Vol13/IJIEC_2022_10.pdf |
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