金屬零件製造產業在多廠區情況下生產物流優化之個案研究：以T公司為例

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蔡宗虔(Tsung-Chien Tsai) 查詢紙本館藏

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高階主管企管碩士班

論文名稱

金屬零件製造產業在多廠區情況下生產物流優化之個案研究：以T公司為例

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摘要(中)

本研究為金屬零件製造產業在多廠區情況下生產物流優化之個案研究，以本土深耕各式各樣高附加價值零配組件的T公司為研究對象，從實際生產角度出發，統計各廠區製程加工時間、停滯時間、運輸時間與各廠區距離，對各生產廠區間製程進行組件式生產流程表，這種方法不僅可以分析模擬廠區間製程布局之優劣，呈現多廠區情況下實際生產物流優化作業場景，還可以對產品生產製造環節進行分析計算。
本研究採用蒐集取得自ERP的各項研究資料，找出生產環節中出現的瓶頸問題，並進行合理改進，對製造流程加以流程再造優化，縮短運輸時間提升了產品品質，並成功的為客戶縮短了產能所需的時間，也是本研究的主要動機。
本研究在探討這項優化計畫的過程中，深刻了解到T公司為生產在多廠區間運輸所投入的龐大人力、物力、決心及成就，並將這項計劃成功的原因做出以下的歸納。
經本研究深入探討分析後，對本研究個案可歸納出以下結論：
1.從過去浪費的經驗中找出成功的最佳設備搬移組合方案。
2.正確規劃與分析各方案，能準確的執行專案任務，以確保專案的成功。
3.科學統計的輔助分析。
對於個案也提出以下的建議：
1.可再利用經由ERP系統取得的資料進一步分析，如何再縮短多廠區間製程物流的時間，以最少的搬運成本達成最佳獲利的目的。
2.在製程流程改造成功的基礎上，繼續研究維持成長與獲利。
對於未來研究方向之建議為：
1.採取統計與分析研究，並以模擬的方式得到專案計畫優化的全貌。
2.持續在多廠區情況下生產物流優化研究，提出解決方案，快速縮短製造與除錯時間。
對於本研究主題的選定，本研究資料之建立分析與個案公司高階經營管理層級之訪談上雖力求嚴謹以符合科學原則，然而仍有一些限制：
1.研究方法的限制，本研究部分資料有商業機密的考量而無法全然揭露。
2.研究對象僅針對單一個案，客觀度不足。
3.資料蒐集存在公司商業機密限制的考量。

摘要(英)

This research is a case study of the production logistics optimization of the metal parts manufacturing industry in the multi-plant situation. The local T company, which is deeply engaged in a variety of high-value-added components, is the research object. From the actual production point of view, statistics are made on the processing of each plant. Time & stagnation time & transportation time and the distance between each plant area, the component production flow chart is performed for each production plant interval process. This method can not only analyze the advantages and disadvantages of the simulated plant interval process layout, but also present the actual production logistics optimization operation scenario in the case of multiple plants. , Can also analyze and calculate the product manufacturing process.
This research uses various research data collected from ERP to find out the bottlenecks in the production process and make reasonable improvements. The manufacturing process is reengineered and optimized, shortening the transportation time, improving product quality, and successfully shortening the time for customers. The time required to increase production capacity is also the main motivation for this study.
In the process of discussing this optimization plan, this research has a deep understanding of the huge manpower, material resources, determination and achievements invested by T Company in the production of multi-factory transportation, and the reasons for the success of this plan are summarized as follows .
After in-depth discussion and analysis of this research, the following conclusions can be drawn from this research case:
1. Find out the best successful equipment moving combination plan from the wasted experience in the past.
2. Properly plan and analyze each plan, and be able to accurately execute the project tasks to ensure the success of the project.
3. Auxiliary analysis of scientific statistics.
The following suggestions are also made for the individual case:
1. The data obtained through the ERP system can be reused for further analysis, how to shorten the time of multi-plant inter-process logistics and achieve the best profit with the least handling cost.
2. On the basis of the successful transformation of the manufacturing process, continue to study to maintain growth and profitability.
Suggestions for future research directions are:
1. Adopt statistics and analysis research, and get the full picture of project plan optimization by means of simulation.
2. Continue to research on the optimization of production logistics in the case of multiple factories, and propose solutions to quickly shorten the manufacturing and debugging time.
Regarding the selection of the subject of this research, the establishment and analysis of the research data and the interviews with the company′s senior management level have strived to be rigorous and consistent with scientific principles, but there are still some limitations:
1. Restrictions on research methods. Some of the materials in this research are considered for commercial secrets and cannot be fully disclosed.
2. The research object is only for a single case and lacks objectivity.
3. Data collection is subject to company trade secret restrictions.

關鍵字(中)

★ 物流優化
★ 多廠區

關鍵字(英)

★ logistics optimization
★ Multi-site

論文目次

第一章緒綸 1
1.1研究背景與動機 1
1.2研究目的 1
第二章文獻探討 2
2.1多廠區製程說明 2
2.2多廠區相關文獻整理 3
2.3文獻探討結語 6
第三章個案公司介紹 7
3.1個案公司簡介與產業屬性 7
3.2 個案公司客戶區分&公司營業額&人數與毛利各項成本說明 8
3.3 個案公司製造模式&廠區說明 9
3.4個案公司產品與製程流程分析 10
第四章個案公司物流改善方案 36
4.1 個案公司改善方案的基礎 36
4.2 個案公司改善方案內容說明 36
4.3 個案公司改善方案效益分析說明 42
第五章結論與後續建議 45
5.1結論 45
5.2研究限制 45
5.3建議 46
5.4後續研究的建議 46
參考文獻 48

參考文獻

中文部份：
Apple, James M.(1999)，設施規劃，頁159-199。
林樹強、陳文哲與葉宏謨(2017)，工作研究工業4.0，頁67-130。
陳堅元(2008)，具訂單貢獻度之多目標多廠區生產指派與排程系統，東海大學工業工程
與經營資訊學系碩士論文。
賴士葆(1994)，生產作業管理─理論與實務，華泰書局。
經濟部中小企業處(2018)，中小企業發展面臨問題與因應對策，頁3。
外文部份：
Archimede, B., Charbonnaud, P., and Mercier, N. (2003). “Robustness evaluation of multisite distributed schedule with perturbed virtual jobshops,” Production Planning & Control, Vol. 14, No. 1, 55-67.
Caroloin, T., Pascal, B., Dinitri, G., and Gernar, B. (1995).“Multi-site planning: non flexible production units and set-up time treatment,” Proceedings of the Emerging Technologies and Factory Automation, 1995., Vol. 3, 261-269.
Chang, P.T., Lo, Y. T. July/August, (2001). “Modelling of job-shop scheduling with multiple quantitative and qualitative objectives and a GA/TS mixture approach,”International Journal of Computer Integrated Manufacturing, v 14, n 4, 367-384.
Daniels, R.L. (1994). “Incorporating performance information into multi-objective scheduling,” European Journal of Operational Research, 77, 272-286.
Dasci, A., and Verter, V. (2001). “A continuous model for production-distribution system design,” European Journal of Operational Research, Vol. 129, 287-298.
Faria, A., Fenn, P., and Bruce, A. (2002). “Determinants of adoption of flexible production technologies: evidence from Portuguese manufacturing industrial,” Economics Innovation New Technology, Vol. 11, No. 6, 569-580.
Guinet, A. (2001). “Multi-site planning: a transshipment problem,” International Journal of Production Economics, Vol. 74, 21-32.
Ishibuchi, H. and Murata, T. (1998). “A multi-objective genetic local search algorithm and its application to flowshop scheduling,” IEEE Transactions on System, Man, and Cybernetics-Part C: Application and Review, 28, 392-403.
Itoh, K, Huang, D. and Enkawa, T. (1993). “Twofold look-ahead search for multi-criterion job shop scheduling,” International Journal of Production Research, 31, 2215-2234.
Kim, C.-O., Min, H.-S. and Yih, Y. (1995). “Integration of inductive learning and neural networks for multi-objective FMS scheduling,” International Journal of Production Research, 36, 2497-2509.
Mellor, P. (1996). “A review of job shop scheduling ,” Operational Research Quarterly, Vol. 17, No. 2, 161-170.
Min, H. S., Yih, Y. and Kim, C.-O. (1998). “A competitive neural network approach to multi-objective FMS scheduling,” International Journal of Production Research, 36, 1749-1765.
Moon, C., Kim, J., and Hur, S. (2002). ”Integrated process planning and scheduling with minimizing total tardiness in multi-plant supply chain,” Computers & Industrial Engineering, Vol. 43, 331-349.
Murata, T., Ishibuchi, H. and Tanaka, H. (1996). “Multi-objective genetic algorithm and its applications to flowshop scheduling,” Computers and Industrial Engineering, 30, 957-968.
Neppalli, V.R., Chen, C.L. and Gupta, J. (1996). “Genetic algorithms for two-stage bicriteria flowshop problem,” European Journal of Operational Research, 95, 356-373.
Sauer, J., Suelmann, G., and Appelrath, H. J. (1998).“Multi-site scheduling with fuzzy concepts,” International Journal of Approximate Reasoning, Vol. 19, 145-160.
Timple, C. H., and Kallrath, J., (2000). “Optimal planning in large multi-site production networks,” European Journal of Operational Research, Vol. 126, 422-435.
Vercellis, C. (1999).“Multi-plant production planning in capacitated self-configuring two-stage serial systems,” European Journal of Operational Research, Vol. 119, 451-460.

指導教授

呂俊德

審核日期

2021-6-17

推文