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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/98210Full metadata record
| ???org.dspace.app.webui.jsptag.ItemTag.dcfield??? | Value | Language |
|---|---|---|
| dc.contributor.advisor | 王建凱 | zh_TW |
| dc.contributor.advisor | Chien-Kai Wang | en |
| dc.contributor.author | 林楷倫 | zh_TW |
| dc.contributor.author | Kai-Lun Lin | en |
| dc.date.accessioned | 2025-07-30T16:21:03Z | - |
| dc.date.available | 2025-07-31 | - |
| dc.date.copyright | 2025-07-30 | - |
| dc.date.issued | 2025 | - |
| dc.date.submitted | 2025-07-23 | - |
| dc.identifier.citation | [1] I. Ribas, R. Leisten, and J. M. Framiñan, “Review and classification of hybrid flow shop scheduling problems from a production system and a solutions procedure perspective,” Computers & Operations Research, vol. 37, no. 8, pp. 1439-1454, 2010.
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Vázquez-Rodríguez, “The hybrid flow shop scheduling problem,” European Journal of Operational Research, vol. 205, no. 1, pp. 1-18, 2010. [7] R. Linn and W. Zhang, “Hybrid flow shop scheduling: A survey,” Computers & Industrial Engineering, vol. 37, no. 1–2, pp. 57-61, 1999. [8] L. Lassig, F. Mazzer, M. Nicolich, and C. Poloni, “Hybrid flow shop management: multi objective optimisation,” Procedia CIRP, vol. 62, pp.147-152, 2017. [9] J. Behnamian and S.M.T. F. Ghomi, “Hybrid flowshop scheduling with machine and resource-dependent processing times,” Applied Mathematical Modelling, vol. 35, no. 3, pp. 1107-1123, 2011. [10] M. D. F. Morais, T. J. P. Boiko, R. P. Coelho, and P. R. Paraiso, “Multicriteria hybrid flow shop scheduling problem: literature review, analysis, and future research,” Independent Journal of Management & Production, vol. 5, no. 4, pp. 1004-1031, 2014. [11] S. Taguemount, D. Lamy, and X. Delorme, “Multi-line hybrid flow shop scheduling problem with energy considerations,” 2023 International Conference on Networking, Sensing and Control (ICNSC), pp. 1-5, Marseille, France, 2023. [12] X. Yue, X. Xiong, M. Zhang, X. Xu, and L. Yang, “Multi-objective optimization for energy-efficient hybrid flow shop scheduling problem in panel furniture intelligent manufacturing with transportation constraints,” Expert Systems with Applications, vol. 274, 2025. [13] V. Fernandez-Viagas, “A speed-up procedure for the hybrid flow shop scheduling problem,” Expert Systems with Applications, vol. 187, 2022. [14] Y. Ge, H. Ding, A. Wang, H. Yang, and Y. Wang, “Scheduling for hybrid flow shop with energy-efficiency and machine preventive maintenance in sheet metal manufacturing system,” Computers & Industrial Engineering, vol. 204, 2025. [15] D. A. Alexander, A. Pandey, and S. K. Kumar, “Mathematical models for multi-stage hybrid assembly flow-shop scheduling with preventive maintenance and release times,” Computers & Industrial Engineering, vol. 186, 2023. [16] Y. C. Cheng, Time-Dependent System Reliability Evaluation for a Stochastic Hybrid Flow Shop Network with Preventive Maintenance Strategy, Master Thesis, Department of Industrial Engineering and Management, National Yang Ming Chiao Tung University, 2021. [17] Y. K. Lin, “System reliability evaluation for a multistate supply chain network with failure nodes using minimal paths,” IEEE Transactions on Reliability, vol. 58, no. 1, pp. 34-40, March 2009. [18] Y. K. Lin, “Reliability of a stochastic-flow network with unreliable branches & nodes, under budget constraints,” IEEE Transactions on Reliability, vol. 53, no. 3, pp. 381-387, Sept. 2004. [19] Y. K. Lin, “Two-commodity reliability evaluation of a stochastic-flow network with varying capacity weight in terms of minimal paths,” Computers & Operations Research, vol. 36, no. 4, pp. 1050-1063, 2009. [20] Y. K. Lin, D. H. Huang, and L. C. L. Yeng, “Reliability evaluation of a hybrid flow-shop with stochastic capacity within a time constraint,” IEEE Transactions on Reliability, vol. 65, no. 2, pp. 867-877, June 2016. [21] Y. K. Lin, P. C. Chang, and J. C. Chen, “Performance evaluation for a footwear manufacturing system with multiple production lines and different station failure rates,” International Journal of Production Research, vol. 51, no. 5, pp. 1603-1617, 2012. [22] C. E. Ebeling, An Introduction to Reliability and Maintainability Engineering, McGraw-Hill Inc, New York, 1997. [23] J. Ribrant, Reliability Performance and Maintenance-A Survey of Failures in Wind Power Systems, Master Thesis, KTH School of Electrical Engineering, Stockholm, Sweden, 2006. [24] M. A. Prasetya, F. I. Adhim, and B. Al Kindhi, “Implementation of Weibull analysis method in designing predictive maintenance for medical mask machine,” 2023 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation (ICAMIMIA), Surabaya, Indonesia, pp. 519-527, 2023. [25] S. Ferrisi, P. Cappellari, R. Guido, D. Umbrello, and G. Ambrogio, “Application of two-parameter Weibull distribution for predictive maintenance: A case study, Procedia Computer Science,” vol. 253, pp. 3160-3168, 2025. [26] E. E. Elmahdy, “A new approach for Weibull modeling for reliability life data analysis,” Applied Mathematics and Computation, vol. 250, pp. 708-720, 2015. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/98210 | - |
| dc.description.abstract | 混合型流線式生產系統(Hybrid flow shop)為一種常見的製造系統,是一組作業依照指定順序、經過多個階段的生產流程,其中各階段可能擁有數台機器運作,以實現高效率生產。在混合型流線式生產系統的研究議題上,多數研究著重於探討理想狀態下的調度問題(Scheduling problem),討論系統於特定目標的最佳化生產,忽略其中可能牽涉到的不確定性。本研究除了針對生產系統滿足產量需求的調度問題進行探討之外,考量生產系統所使用機器性能會隨時間衰退(Degradation),而引入可靠度工程(Reliability engineering)裡的衰退概念,評估生產系統能夠滿足產量需求的可能性,並以機率呈現;本研究也考量每台機器單位時間產量的隨機性(Randomness),重新探討前述問題。研究結果發現,源由於機器性能的衰退、可靠度的下降,調度問題分析所得的生產系統原可滿足產量需求,但隨著時間演進,滿足需求的機率逐漸降低;若再考量每台機器單位時間產量的隨機性,則生產系統滿足產量需求的機率將會降至更低。為求改善,本研究進一步探討機器與系統預防維護(Preventive maintenance)的成效,最後並依定期維護(Scheduled maintenance)和狀態維護(Condition based maintenance)兩種不同考量,提出三套不同維護策略,以優化生產系統,並供決策者參考。 | zh_TW |
| dc.description.abstract | The Hybrid Flow Shop (HFS) is a common manufacturing system where a sequence of operations is carried out across multiple stages in a predefined order. Each stage may contain multiple machines operating simultaneously to achieve high production efficiency. In research related to hybrid flow shops, most studies focus on the scheduling problem under ideal conditions, aiming to optimize specific objectives of the system while often neglecting potential uncertainties. This study not only investigates the scheduling problem to meet production demand but also considers machine performance degradation over time, incorporating the concept of degradation from reliability engineering to assess the probability that the production system can meet the required output. Furthermore, the study considers the randomness in each machine's unit-time output, and reexamines the problem from this perspective. The results indicate that, due to machine degradation and decreased reliability, a production system that was initially capable of meeting output demand may experience a decline in this probability over time. When randomness in machine productivity is also taken into account, the likelihood of meeting production requirements becomes even lower. To address this issue, the study further explores the effectiveness of preventive maintenance at both the machine and system levels. Based on two different maintenance approaches—scheduled maintenance and condition based maintenance—the study proposes three distinct maintenance strategies to optimize the production system and provide practical guidance for decision-makers. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2025-07-30T16:21:03Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2025-07-30T16:21:03Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 致謝 I
摘要 II ABSTRACT III 目次 IV 圖次 VII 表次 IX 第一章 緒論 1 1.1研究背景與動機 1 1.2文獻回顧 2 1.3論文架構 4 第二章 應用理論 6 2.1可靠度基本概念 6 2.1.1可靠度函數 6 2.1.2連續機率分布 7 2.1.2.1韋伯分布 7 2.1.2.2常態分布 8 2.2系統可靠度 9 2.2.1串聯系統 10 2.2.2並聯系統 10 2.2.3 k-out-of-n冗餘系統 11 2.3維護策略 11 2.3.1矯正性維護 12 2.3.2預防性維護 12 2.4期望值 13 2.5混合型流線式生產 13 第三章 研究方法 15 3.1產量為定值的系統可靠度 16 3.1.1總產量期望值 18 3.2產量為隨機變數的系統可靠度 20 3.2.1參數調整 22 3.3預防性維護 22 3.3.1維護策略一 23 3.3.2維護策略二 24 3.3.3維護策略三 24 第四章 單一工作站案例 25 4.1產量為定值的系統可靠度 25 4.1.1期望值 27 4.2產量為隨機變數的系統可靠度 30 4.2.1平均數 33 4.2.2標準差 35 4.2.3機器數量 39 4.3可靠度比較 41 第五章 多工作站案例 43 5.1產量為定值的系統可靠度 44 5.1.1維護策略一 46 5.1.2維護策略二 49 5.1.3維護策略三 52 5.2產量為隨機變數的系統可靠度 54 5.2.1維護策略一 56 5.2.2維護策略二 58 5.2.3維護策略三 60 5.3可靠度比較 62 5.4維護策略分析 64 第六章 結論 68 參考文獻 70 | - |
| dc.language.iso | zh_TW | - |
| dc.subject | 混合型流線式生產系統 | zh_TW |
| dc.subject | 調度問題 | zh_TW |
| dc.subject | 性能衰退 | zh_TW |
| dc.subject | 可靠度工程 | zh_TW |
| dc.subject | 隨機性 | zh_TW |
| dc.subject | 預防維護 | zh_TW |
| dc.subject | degradation | en |
| dc.subject | hybrid flow shop | en |
| dc.subject | preventive maintenance | en |
| dc.subject | randomness | en |
| dc.subject | reliability engineering | en |
| dc.subject | scheduling problem | en |
| dc.title | 考量隨機性之混合型流線式生產系統可靠度分析 | zh_TW |
| dc.title | Reliability Analysis of Hybrid Flow Shop Systems in Consideration of Randomness | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 113-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 黃瀅瑛;吳文方 | zh_TW |
| dc.contributor.oralexamcommittee | Ying-Yin Huang;Wen-Fang Wu | en |
| dc.subject.keyword | 混合型流線式生產系統,調度問題,性能衰退,可靠度工程,隨機性,預防維護, | zh_TW |
| dc.subject.keyword | hybrid flow shop,scheduling problem,degradation,reliability engineering,randomness,preventive maintenance, | en |
| dc.relation.page | 73 | - |
| dc.identifier.doi | 10.6342/NTU202502020 | - |
| dc.rights.note | 同意授權(全球公開) | - |
| dc.date.accepted | 2025-07-25 | - |
| dc.contributor.author-college | 工學院 | - |
| dc.contributor.author-dept | 機械工程學系 | - |
| dc.date.embargo-lift | 2025-07-31 | - |
| Appears in Collections: | 機械工程學系 | |
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| File | Size | Format | |
|---|---|---|---|
| ntu-113-2.pdf | 2.1 MB | Adobe PDF | View/Open |
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