預測性維修及信用交易下的非完美生產系統｜國立臺灣科技大學博碩士論文系統

簡易檢索 / 詳目顯示

回結果列表

研究生：	范國政 Gou-Zheng Fan
論文名稱：	預測性維修及信用交易下的非完美生產系統 Imperfect Production System under Predictive Maintenance and Trade Credit
指導教授：	曹譽鐘 Yu-Chung Tsao
口試委員:	喻奉天 Vincent F. Yu 郭伯勳 Po-Hsun Kuo
學位類別：	碩士 Master
系所名稱：	管理學院 - 工業管理系 Department of Industrial Management
論文出版年：	2017
畢業學年度：	105
語文別：	英文
論文頁數：	59
中文關鍵詞：	信用交易、經濟生產批量、預測性維修、非完美生產系統
外文關鍵詞：	Trade credit, Economic production quantity, Predictive maintenance, Imperfect production system
相關次數：	點閱：392 下載：0
分享至:	分享至facebook 分享至twitter

查詢本校圖書館目錄查詢臺灣博碩士論文知識加值系統勘誤回報

近年，工業4.0的革新已相繼在企業間展開。預測性維護是智慧型生產系統中重要的一環，透過感測器的監測及資料分析使生產系統得以在失控前先一步進行維修而提高系統可靠度。傳統上的經濟生產量模型假設生產系統的產出皆為良品，但實際上生產過程中卻有可能產生不良。生產系統可能由可控狀態轉移到失控狀態而導致不良率的增加。因此，將收入來源區分為良品與瑕疵品較於貼近實務。在現實狀況中，供應商經常提供零售商信用交易，以減輕零售商財務負擔及增加自身銷售。本研究的第一個模型建立預測性維修下建立非完美生產系統，第二個模型則延伸考慮當供應商提供信用交易之情況。模型的目標為決定最佳的生產期間及預測性維護投入程度已最大化總期望利潤。最後，我們探討系統參數對決策變數與利潤的影響，並提出相關的結論與管理意涵。

Lately, Industry 4.0 revolution is initiated among enterprises. As a part of intelligence production system, predictive maintenance is able to estimate production system breakdown points through cyber-physics sensors and data analysis, which is capable executing maintenances before system breakdown and improving system reliability. The traditional EPQ model assumes production system all products are perfect quality, which is unrealistic. In reality, production system may produces imperfect items, and shifting from “in-control” to “out-of-control” statuses, causing a higher defective rate. Due to system characteristic considered revenue sources as two types of item depends on quality is more reasonable. In reality, suppliers often provides trade credit to customers, in order to release their financial pressure and increases supplier’s demands. In this study, first imperfect economic production quantity model we proposed is under predictive maintenance. The second model is taking trade credit financing arrangement as an additional extension. Primary objective of models are determine optimal production runtime, predictive maintenance efforts level and maximized expected total revenue. In the finish, we characterized the relation among decisions and profit so as to obtain conclusions and relevant managerial phenomena.

摘要    I
ABSTRACT    II
CONTENTS    IV
LIST OF FIGURES    V
LIST OF TABLES    V
CHAPTER 1    5
1.1    Background and Motivation    2
1.2    Research Objectives    4
1.3    Research Organization    4
CHAPTER 2    6
2.1 EPQ model and Imperfect Production Process    6
2.2 Maintenance Policy    7
2.3    Trade Credit    9
CHAPTER 3    11
3.1    Notations and Assumptions    11
3.2    Mathematical Model    13
3.3    Solution Approach    17
3.4    Numerical Examples    17
3.5    Sensitivity Analysis    21
CHAPTER 4    21
4.1    Mathematical Model    24
4.2    Solution Approach    28
4.2.1 Optimal production runtime      28
4.2.2 Optimal Solution and Algorithm Development    34
4.3    Numerical Examples    38
4.4    Sensitivity Analysis    41
CHAPTER 5    46
5.1    Conclusions    47
5.2    Future Research    49
REFERENCE    50

LIST OF FIGURES
Figure 1. Total On-hand inventory of model 1    16
Figure 2. Production Period Length influences Expected Total Revenue    19
Figure 3. Predictive Maintenance Efforts Level influences Expected Total Revenue    19
Figure 4. 3D graphic of Predictive Maintenance Efforts Level, Production Period Length influences and Expected Total Revenue    20
Figure 5. Total On-hand inventory of model 2    24
Figure 6. Production Period Length influences Expected Total Revenue    39
Figure 7. Predictive Maintenance Efforts Level influences Expected Total Revenue    40

LIST OF TABLES
Table 1. Numerical Example for Model1    18
Table 2. Sensitivity analysis of Set-up Cost for model 1    22
Table 3.Sensitivity analysis of Holding Cost for model 1    22
Table 4.Sensitivity analysis of Corrective Maintenance Cost for model 1    22
Table 5.Sensitivity analysis of Predictive Maintenance Cost for model 1    22
Table 6.Sensitivity analysis of Perfect Item Selling Price for model 1    23
Table 7.Sensitivity analysis of Imperfect Item Selling Price for model 1    23
Table 8. Numerical Example for Model2    39
Table 9. Sensitivity analysis of Set-up Cost for model 2    42
Table 10. Sensitivity analysis of Holding Cost for model 2    42
Table 11. Sensitivity analysis of Corrective Maintenance Cost for model 2    43
Table 12. Sensitivity analysis of Predictive Maintenance Cost for model 2    43
Table 13. Sensitivity analysis of Perfect Item Selling Price for model 2    44
Table 14. Sensitivity analysis of Imperfect Item Selling Price for model 2    44
Table 15. Sensitivity analysis of Credit Period for model 2    45
Table 16. Sensitivity analysis of Interest Paid for model 2    45
Table 17. Sensitivity analysis of Interest Earned for model 2    46


                                

Anis, C., Nidhal, R., & Mehdi, R. (2008). Simultaneous determination of production lot size and preventive maintenance schedule for unreliable production system. Journal of Quality in Maintenance Engineering, 14(2), 161-176. doi:10.1108/13552510810877665
Bouslah, B., Gharbi, A., & Pellerin, R. (2016). Integrated production, sampling quality control and maintenance of deteriorating production systems with AOQL constraint. Omega, 61, 110-126. doi:https://doi.org/10.1016/j.omega.2015.07.012
Chiu, S. W., Wang, S.-L., & Chiu, Y.-S. P. (2007). Determining the optimal run time for EPQ model with scrap, rework, and stochastic breakdowns. European Journal of Operational Research, 180(2), 664-676. doi:https://doi.org/10.1016/j.ejor.2006.05.005
Deloux, E., Castanier, B., & Bérenguer, C. (2009). Predictive maintenance policy for a gradually deteriorating system subject to stress. Reliability Engineering & System Safety, 94(2), 418-431. doi:https://doi.org/10.1016/j.ress.2008.04.002
Goyal, S. K. (1985). Economic order quantity under conditions of permissible delay in payments. Journal of the Operational Research Society, 36(4), 335-338. doi:10.1057/jors.1985.56
Goyal, S. K., & Gunasekaran, A. (1995). An integrated production-inventory-marketing model for deteriorating items. Computers & Industrial Engineering, 28(4), 755-762. doi:http://dx.doi.org/10.1016/0360-8352(95)00016-T
Hariga, M., & Ben-Daya, M. (1998). Note: the economic manufacturing lot-sizing problem with imperfect production processes: bounds and optimal solutions. Naval Research Logistics, 45(4), 423-433.
Kreng, V. B., & Tan, S.-J. (2011). Optimal replenishment decision in an EPQ model with defective items under supply chain trade credit policy. Expert Systems with Applications, 38(8), 9888-9899. doi:https://doi.org/10.1016/j.eswa.2011.02.040
Liao, H., Elsayed, E. A., & Chan, L.-Y. (2006). Maintenance of continuously monitored degrading systems. European Journal of Operational Research, 175(2), 821-835. doi:https://doi.org/10.1016/j.ejor.2005.05.017
Lee, Jay & Bagheri, Behrad & Kao, Hung-An (2015). A Cyber-Physical Systems
architecture for Industry 4.0-based manufacturing systems. Manufacturing
Letters, 3,18-23, 2213-8463.
doi: https://doi.org/10.1016/j.mfglet.2014.12.001
Maillart, L. M., & Pollock, S. M. (2002). Cost-optimal condition-monitoring for predictive maintenance of 2-phase systems. IEEE Transactions on Reliability, 51(3), 322-330. doi:10.1109/TR.2002.801846
Park, C., Moon, D., Do, N., & Bae, S. M. (2016). A predictive maintenance approach based on real-time internal parameter monitoring. The International Journal of Advanced Manufacturing Technology, 85(1), 623-632. doi:10.1007/s00170-015-7981-6
Peng, H., & Van Houtum, G. J. (2016). Joint optimization of condition-based maintenance and production lot-sizing. European Journal of Operational Research, 253(1), 94-107. doi:10.1016/j.ejor.2016.02.027
Porteus, E. L. (1986). Optimal lot sizing, process quality improvement and setup cost reduction. Oper. Res., 34(1), 137-144. doi:10.1287/opre.34.1.137
Rosenblatt, M. J., & Lee, H. L. (1986). Economic Production Cycles with Imperfect Production Processes. IIE Transactions, 18(1), 48-55. doi:10.1080/07408178608975329
Salameh, M. K., & Jaber, M. Y. (2000). Economic production quantity model for items with imperfect quality. International Journal of Production Economics, 64(1), 59-64. doi:http://dx.doi.org/10.1016/S0925-5273(99)00044-4
Sana, S. S., & Chaudhuri, K. (2010). An EMQ model in an imperfect production process. International Journal of Systems Science, 41(6), 635-646. doi:10.1080/00207720903144495
F. Shrouf & J. Ordieres & G. Miragliotta (2014). Smart factories in Industry 4.0: A
review of the concept and of energy management approached in
production based on the Internet of Things paradigm. 2014 IEEE
International Conference on Industrial Engineering and Engineering Management, 697-701, 2157-3611. doi: 10.1109/IEEM.2014.7058728
Terence, J. P. (1997). Data requirements for the prioritization of predictive building maintenance. Facilities, 15(3/4), 97-104. doi:10.1108/02632779710160612
Tsao, Y.-C., Chen, T.-H., & Huang, S.-M. (2011). A production policy considering reworking of imperfect items and trade credit. Flexible Services and Manufacturing Journal, 23(1), 48-63. doi:10.1007/s10696-010-9070-3
Tsao, Y.-C., Chen, T.-H., & Zhang, Q.-H. (2013). Effects of maintenance policy on an imperfect production system under trade credit. International Journal of Production Research, 51(5), 1549-1562. doi:10.1080/00207543.2012.714001
Wen, D., Ershun, P., Ying, W., & Wenzhu, L. (2014). An economic production quantity model for a deteriorating system integrated with predictive maintenance strategy. Journal of Intelligent Manufacturing. doi:10.1007/s10845-014-0954-z
Wen, D., Ershun, P., Ying, W., & Wenzhu, L. (2016). An economic production quantity model for a deteriorating system integrated with predictive maintenance strategy. Journal of Intelligent Manufacturing, 27(6), 1323-1333. doi:10.1007/s10845-014-0954-z
Yang, Z., Chang, Q., Djurdjanovic, D., Ni, J., & Lee, J. (2007). Maintenance priority assignment utilizing on-line production information. Journal of Manufacturing Science and Engineering, 129(2), 435-446.
Yedes, Y., Chelbi, A., & Rezg, N. (2012). Quasi-optimal integrated production, inventory and maintenance policies for a single-vendor single-buyer system with imperfect production process. Journal of Intelligent Manufacturing, 23(4), 1245-1256. doi:10.1007/s10845-010-0423-2

全文公開日期 2022/07/26 (校內網路)
全文公開日期本全文未授權公開 (校外網路)
全文公開日期本全文未授權公開 (國家圖書館：臺灣博碩士論文系統)

簡易檢索 / 詳目顯示

相關論文