零件庫存預測與可維修零件補貨模式實證研究

Spare part buffer forecasting and repairable parts replenishment model: an empirical study

10.6840/cycu201700340

巫國興

零件可用度 ； 零件初始庫存預測 ； 可維修零件補貨 ； spare part availability ； initial buffer forecasting ； repairable spare part replenishment

中原大學工業與系統工程學系學位論文

2017年

博士

黃惠民

繁體中文

產品除了設計和功能外，售後服務是新產品導入市場成功或失敗的重要關鍵因素。零件可用度將影響服務的速度，也直接影響了服務品質。零件生命週期可以分為四個階段：準備、生產、生命週期終止 (EOL/End Of Life) 與服務終止 (EOS/End Of Service) 階段。在準備階段，由於缺乏歷史使用資訊，難以應用傳統統計技術進行需求預測。因此，需要採用不同的預測方法。新產品初始庫存的需求的問題可以通過延伸 Kahn (2002) 使用定性於預測的未來銷售的研究來完成。在本研究中，我們提出了一種用於預測零件需求準備階段的聯合定性方法 (JQM/Joint Qualitative Method) 方法。JQM的關鍵在於類比矩陣，及經由設定假設樂觀和悲觀的服務水平值分別為90％和60％。該標準化生成一種方法，使零件規劃人員可經由服務水準來取得零件需求預測值。 在零件生命週期中量產與EOL階段，本研究專注於可維修的零件，因為可維修零件通常屬於高單價。可維修的零件補充模型屬於為多階層庫存模型，可以是有限或無限多庫存的上層倉庫和下層倉庫的庫存管理模型。在實務，很多零件維修中心直覺認為服務點以固定週期退修故障零件的模式可便於維修工作的執行。然而，在實際上固定週期退修故障零件的模式在處理故障零件效率卻是不高。因此，本研究提出了一種稱為最短維修作業時間法 ( LTAT /Least Turn Around Time)，該方法利用最短維修作業時間作為退修作業底限。LTAT 是以零件故障率來預測可能的零件缺貨時間點，再以最短維修作業時間來反推其應退修時間點進行退修零件維修中心作業。使用此方法，零件維修中心修護品將即時到達服務點，補充已耗用量以避免任何缺貨。利用 LTAT 方法，與固定週期模型相比，總庫存需求和補貨週期將會減少。這表明 LTAT 模型可以提高零件庫存運行的效率和成本。

Due to the increasing market competition, shorter product life, small profit margin and rising customer service demand, after service quality is getting more and more important. Besides product design and function, after service is a vital decisive role in the success or fail in the new product introduction. Spare part availability will affect the speed of service, which directly impacts the service quality. Spare part lifecycle can be classified into four stages: preparation, production, EOL (End of Life) and EOS (End of Service) stages. In the preparation stage, due to lack of historical usage information, it is hard to apply traditional statistic technique to perform demand forecasting. Therefore, a different approach to forecast usage is necessary. The problem to new product sales forecasting can be done by extending the research done by Kahn (2002) who uses qualitative forecasting. In this study, we propose a JQM (Joint Qualitative Method)) method for forecasting the preparation stage of spare part demand. The key in JQM is centered in the similarity matrix, and by assuming the optimistic and pessimistic service level value of 90% and 60 % respectively. This standardization generates a method which enable user to choose the service level for the demand condition. For production and EOL stages, this study focusses in repairable spare part, since repairable spare part are likely the most expensive. Repairable spare part replenishing model can be classified into a multi-echelon inventory model with multi upper inventory hubs and lower level warehouses with limited or infinite stock. In current industrial practice, central component repair center intuitively assumes service point has a fixed cycle return for defects; this enables more convenient workload arrangement. However, a fixed cycle return model is not very efficient in handling the defect returns. Therefore, a LTAT (Least Turn Around Time) method is proposed in this study. The method leverages the minimum time in returning the repaired defect parts to the service point. The theory is based on the specific spare part failure rate to forecast the possible spare part shortage time; it is based on the minimum repair process time to reserve the time to ship defect parts to central component repair center. By this method, repaired parts should arrive at the service point in time and thus avoid any shortages. With LTAT method, the total inventory demand and replenishment cycle will be reduced compared to a fixed cycle model. This shows LTAT model can improve the efficiency of spare part inventory operation and the cost.

1. Abdul-Jalbar, B., Segerstedt, A., Sicilia, J., and Nilsson, A., 2010. A new heuristic to solve the one-warehouse N-retailer problem, Computers & Operations Research, 37 (2), 265-272.
   連結：
2. Agrawal, S., Singh, R. K., and Murtaza, Q., 2015. A literature review and perspectives in reverse logistics, Resources, Conservation and Recycling, 97, 76-92.
   連結：
3. Armstrong J. S. (ed.),2009. Principles of Forecasting: A Handbook for Researchers and Practitioners, Kluwer Academic Publishers.
   連結：
4. Ashayeri, J., Heuts, R., Jansen, A., and Szczerba, B., 1996. Inventory management of repairable service parts for personal computers: A case study, International Journal of Operations & Production Management, 16 (12), 74-97.
   連結：
5. Batyrshin, I., and Sheremetov, L., 2007. Perception-Based Functions in Qualitative Forecasting, Studies in Computational Intelligence, 36, 119–134.
   連結：
6. Berry, L., and Parasuraman, A. 1997. Listening to the Customer - The Concept of a Service-Quality Information System, Sloan Management Review; 38 (3), 65-76.
   連結：
7. Bowersox, D. J., Stank, T. P. and Daugherty, P. J., 1999. Lean launch: managing product introduction risk through response-based logistics, Journal of Product Innovation Management, 16, 557-568.
   連結：
8. Beautel, A., & Minner, S., 2012. Safety stock planning under causal demand forecast, International Journal Production Economics, 140, 637-645.
   連結：
9. Cho, D. C., 2001. Optimal Stationary Policy for a Repairable Item Inventory Problem, Canadian Journal of Administrative Sciences, 18 (2),130–143.
   連結：
10. Cobbaert, K., and Oudheusden, Dirk., 1996. Inventory models for fast moving spare parts subject to “sudden death” obsolescence, International Journal Production Economics, 44, 239-248.
    連結：
11. Cohen, M. A., Zheng, Y. and Agrawal, V., 1996. Service parts logistics: a benchmark analysis, IEEE Transactions, 29, 627-639.
    連結：
12. Cohen, M. A. and Whang, S., 1997. Competing in Product and Service: A Product Life-Cycle Model, Management Science, 43 (4), 535-545.
    連結：
13. Danese, P., Kalchschmidt, M., 2011. The role of the forecasting process in improving forecast accuracy and operational performance, International Journal Production Economics, 131, 204-214.
    連結：
14. Daniel Jr. R. G., Rajesh S., 1997. Repairable inventory theory: Models and applications, European Journal of Operational Research, 102, 1-20.
    連結：
15. Dekker, R., Kleijn, M.J., Rooij P.J., 1998. A spare parts stocking policy based on equipment criticality, International Journal Production Economics, 56-57, 69-77.
    連結：
16. Dekker, R., Pinçe, Ç., Zuidwijk, R., and Jalil, M. N., 2013. On the use of installed base information for spare parts logistics: a review of ideas and industry practice, International Journal Production Economics, 143 (2), 536-545.
    連結：
17. Gaiardelli, P., Saccani, N. and Songini, L., 2007. Performance measurement of the after-sales service network—Evidence from the automotive industry, Computers in Industry, 58, 698-708.
    連結：
18. Ghobbar, A. A., and Friend, C. H., 2003. Evaluation of forecasting methods for intermittent parts demand in the field of aviation: a predictive model, Computers & Operations Research, 30, 2097-2114.
    連結：
19. Goodwin, P., Meeran, S., and Dyussekeneva, K., 2014. The challenges of pre-launch forecasting of adoption time series for new durable products, International Journal Production Economics, 30, 1082-1097.
    連結：
20. Graves, S. C., 1985. A Multi-Echelon Inventory Model for a repairable Item with one-for-one Replacement, Management Science, 31 (10), 1247-1256.
    連結：
21. Gruber, T., Szmigin, I., and Voss, R., 2006. The Desired Qualities of Customer Contact Employees in Complaint Handling Encounters, Journal of Marketing Management, 22 (5-6), 619-642.
    連結：
22. Guide, D. R. and Srivastava, R., 1997. Repairable inventory theory: Models and applications, European Journal of Operational Research, 102, 1-20.
    連結：
23. Heijden, M., and Iskandar, B. P., 2013. Last time buy decisions for products sold under warranty, European Journal of Operational Research, 224, 302-312.
    連結：
24. Hua, Z., and Zhang, B., 2006. A hybrid support vector machines and logistic regression approach or forecasting intermittent demand of spare parts, Applied Mathematics and Computation, 181, 1035-1048.
    連結：
25. Huang*, G.Q., Yee, W.Y., Mak, K.L., 2003. Current practice of engineering change management in Hong Kong manufacturing industries, Journal of Materials Processing Technology, 139, 481-487.
    連結：
26. Huiskonen, J., 2001. Maintenance spare parts logistics: Special characteristics and strategic choices, International Journal Production Economics, 71, 125-133.
    連結：
27. Hyndman, R. J., and Koehlerb.1, Anne B., 2006. Another look at measure of forecast accuracy, International Journal of Forecasting, 22 (4), 679-688.
    連結：
28. Inderfurth, K. and Mukherjee, K., 2008. Decision support for spare parts acquisition in post product life cycle, Central European Journal of Operations Research, 16, 17-42.
    連結：
29. Jin S. A., & So Y. S., 2009. Customer pattern search for after-sales service in manufacturing, Expert Systems with Applications, 36, 5371-5375.
    連結：
30. Jung, M., and Bai, D.S., 2007. Analysis of field data under two-dimensional warranty, Reliability Engineering and System Safety, 92, 135-143.
    連結：
31. Kahn, K. B., 2002. An exploratory Investigation of new product forecasting practices, The Journal of Product Innovation Management, 19, 133-143.
    連結：
32. Kennedy, W.J., Patterson, W., Fredendall, J., and Lawrence D., 2002. An overview of recent literature on spare parts inventories, International Journal Production Economics, 76, 201–215.
    連結：
33. Bowon, K. K., and Sangsun, P., 2008. Optimal pricing, EOL (end of life) warranty, and spare parts manufacturing strategy amid product transition, European Journal of Operational Research, 188, 723-745.
    連結：
34. Kumar, R. and Kumar, U., 2004, A conceptual framework for the development of a service delivery strategy for industrial systems and products, Journal of Business & Industrial Marketing, 19 (5), 310-319.
    連結：
35. Kurata, H., and Namb, S., 2010. After-sales service competition in a supply chain: Optimization of customer satisfaction level or profit or both? International Journal Production Economics, 127, 136-146.
    連結：
36. Lau, H. C., Song, G., See, C. T., and Cheng, S.Y., 2006. Evaluation of time-varying availability in multi-echelon spare parts systems with passivation, European Journal of Operational Research, 170, 91-105.
    連結：
37. Lee, H., Kim, S., Park, H., and Kang, P., 2014. Pre-launch new product demand forecasting using the Bass model: A statistical and machine learning-based approach, Technological Forecasting & Social Change, 86, 49-64.
    連結：
38. Lee, J., Lee, C., and Lee, K. S., 2012. Forecasting demand for newly introduced product using reservation price data and Bayesian updating, Technological Forecasting & Social Change, 79, 1280-1291.
    連結：
39. Lee, W. Y., Goodwin, P., Fildes, R., Nikolopoulos, K., and Lawreance, M., 2007. Providing support for the use of analogies demand forecasting tasks, International Journal of Forecasting, 23, 377-390.
    連結：
40. Lutz, N. A. and Padmanabhan, V., 1998. Warranties, extended warranties, and product quality, International Journal of Industrial Organization, 16, 463-493.
    連結：
41. Lynn, Gary S., Schnaars, Steven P. and, Skov, Richard B., 1999. Survey of New Product Forecasting Practices in Industrial High Technology and low Technology Business, Industrial Marketing Management, l (28), 565-571.
    連結：
42. Mahajan, V. and Sharma, S., 1986. A simple algebraic estimation procedure for innovation diffusion models of new product acceptance, Technological Forecasting and Social Change, 30 (4), 331-345.
    連結：
43. Murthy, D.N.P. and W.R. Blischke, 2000. Strategic Warranty Management: A Life-Cycle Approach, IEEE Transaction on Engineering Management, 47 (1), 40-54.
    連結：
44. Murthy, D.N.P., and Djamaludina, I., 2002. New product warranty: A literature review, International Journal Production Economics, 79, 231-260.
    連結：
45. Milind, M. L., 1997. After-sales service - necessary evil or strategic opportunity? Managing Service Quality: An International Journal, 7 (3), 141-145.
    連結：
46. O’Connor, M., Remus, W., and Griggs, K., 2000. Does updating judgmental forecasts improve forecast accuracy, International Journal of Forecasting, 16, 101-109.
    連結：
47. Paqium, R., 2015. The importance of Inventory Optimization and MRO, Aberdeen Group.
    連結：
48. Pascual, R., Santelices, G., Lüer-Villagra, A. Mac Cawleyc, J., 2017. Optimal repairable spare-parts procurement policy under total business volume discount environment, Reliability Engineering and System Safety, 159, 276-282.
    連結：
49. Pérès, F. and Grenouilleau, J., 2002. Initial Spare Parts Supply of an Orbit System, Aircraft Engineering and Aerospace Technology, 74 (3), 252-262.
    連結：
50. Piccoli, C., Brohman, M.K., Watson, R. T., 2004. Net-Based Customer Service Systems: Evolution and Revolution in Web Site Functionalities, Decision Sciences, 35 (3), 423-455.
    連結：
51. Poutakbar, M., Dekker, R., 2012. Customer differentiated end-of-life inventory problem, European Journal of Operational Research, 222, 44-53.
    連結：
52. Regattieri, A., Gamberi, M., Gamberini, R., and Manzini, R., 2005. Managing lumpy demand for aircraft spare parts, Journal of Air Transport Management, 11, 426-431.
    連結：
53. Berger, R. 2013. think: act content, Service study Roland Berger Strategy Consultants GMBH.
    連結：
54. Saaty, T. L., 2000. Fundamentals of decision making with the analytic hierarchy process, RWS Publications.
    連結：
55. Sanders, N. R., and Ritzman, L. P., 1995. Bring judgment into Combination Forecasts, Journal of Operation Manager, 13, 311-321.
    連結：
56. Sandders, NR, 1997. The Impact of Task Properties Feedback on Time Series Judgmental Forecasting Tasks, Omega, 25 (2), 135-144.
    連結：
57. Schrady, D. A., 1967. A Deterministic Inventory model for Repairable item, Naval Research Logistics Quarterly, 14, 391-398.
    連結：
58. Shafiee, M. and Chukova, S., 2013. Maintenance models in warranty: A literature review, European Journal of Operational Research, 229, 561-572.
    連結：
59. Sherbrook, C. C., 1966. METRIC: A Multi Echelon Technique for Recoverable Item Control, The Rand Corporation.
    連結：
60. Solomon R. et al, 2000. Electronic part life cycle concepts and obsolescence forecast, IEEE Trans. On Components and Packaging Technologies, 707-717.
    連結：
61. Somarina, A. R., Chena, S., Asianc, S., and Wang, D. Z. W., 2017. A heuristic stock allocation rule for repairable service parts, International Journal Production Economics, 184, 131-140.
    連結：
62. Skye, H.B. and D. Dunham, 1995. Critical assumption planning a practical tool for managing business development risk, Journal of Business Venturing, 10, 413-424.
    連結：
63. Snyder, R. D., Ord. J. K, and Beaumont, A., 2012. Forecasting the intermittent demand for slow-moving inventories: A modeling approach, International Journal of Forecasting, 28, 485-496.
    連結：
64. Thomas, R. J., 1985. Estimating market growth for new products: An analogical diffusion model approach, Journal of Product Innovation Management, 2 (1), 45-55.
    連結：
65. Trachta, K., Funkea, L., and Schneidera, D., 2014. Varying Repair Capacity in a Repairable Item System, Procedia CIRP, 17, 446 – 450.
    連結：
66. Ulrike, B., 1995. New Industrial Service Development: Scenarios for Success and Failure, Journal of Business Research, 32, 93-103.
    連結：
67. Vasumathi, B. and A. Saradha, A., 2013. Forecasting Intermittent Demand for Spare Parts, International Journal of Computer Applications, 75 (11), 12-16.
    連結：
68. Wasmera, A., Staub, G., and Vroomb, R. W., 2011. An industry approach to shared, cross-organizational engineering change handling - The road towards standards for product data processing, Computer-Aided Design, 43, 533-545.
    連結：
69. Wong*, H., Cattrysse, D., and Oudheusden D., 2005. Stocking decisions for repairable spare parts pooling in a multi-hub system, International Journal Production Economics, 93-94, 309-317.
    連結：
70. Wong, H., Cattrysse, D., and Oudheusden, D., 2005. Inventory pooling of repairable spare parts with non-zero lateral transshipment time and delayed lateral transshipment, European Journal of Operational Research, 165, 207-218.
    連結：
71. Wu, M. C., and Hsuy, Y. K. 2007. Design of BOM configuration for reducing spare parts logistic cost, Expert System with Application, 34 (4), 2417-2423.
    連結：
72. Wu, S., and Akbarov, A., 2012, Forecasting warranty claims for recently launched products, Reliability Engineering and System Safety, 106, 160-164.
    連結：
73. Yang, K. H., and Wu, K. H., 2016. A spare part management model considering service level at a new product introduction: case of mobile phone, Journal of Quality (accepted).
    連結：
74. 參考文獻
75. Apgar, David, Nov. 2011. Assumption-Based Metrics: Recipe for Success, Strategic Finance.
76. Behfard, S., Heijden, M.C., Hanbali, A. A., and Zijm, W. H. M., 2015. Last Time Buy and Repair Decisions for Spare Parts, European Journal of Operational Research, 244 (2), 498-510.
77. Blumberg, Donald F., 1999. Strategic examination of reverse logistics & repair service requirements, needs, market size, and opportunities, Journal of Business Logistics, 20 (2),141-159
78. Butner, K. and Wilterding, M., 2006. The perfect product launch: Innovation drives growth in the consumer products industry, IBM Global Business Services
79. Barkawi, C., Bendig, O., Springmann, M., and Janik, J., 2016. After Sales Services: The Quest for Faster Growth and Higher Margins: A Guide on Turning Opportunities into Results, Barkawi Management Consultants.
80. Callegaro A., 2010. Forecast methods for spare parts demand, Universita’ Degli Studo Di Padova, Facolta’ Di Ingegneria.
81. Cohen, M. A., and Lee, H. L., 1990. Out of Touch Customer Needs? Spare Parts and After Sales Service, Sloan Management Review, 31, 2.
82. Diaz, A. and Fu, M.C., Oct 1997. Multi-Echelon Models for Repair Items: A Review, Computers & Operations Research.
83. Díaz, V. G., Fernández, J. F. G., and Márquez, A. C., Case Study: Warranty costs estimation according to a defined lifetime distribution of deliverables, paper presented at the meetings of Proceedings of the 4th World Congress on Engineering Asset Management (WCEAM 2009), 28-30, Athens, Greece.
84. Dixon, M., Freeman, K., and Toman, N., Jul.-Aug. 2010. Stop Trying to Delight Your Customers, Harvard Business Review.
85. Dombrowski, U., Wrehde, J. K. and Schulze, S. 2007. Efficient Spare Part Management to Satisfy Customers Need, Paper presented at the meeting of SOLI 2007 IEEE International Conference on Philadelphia, USA.
86. Duinkerken, W., and Brinkkemper, S., 2006. Customized Assumption Planning in Business Planning, Utrecht University, the Netherlands.
87. Dutta, S., 2013, Fixing-First Time Fix: Repair Field Service Efficiency to Enhance Customer Return, Aberdeen Group.
88. Guilherme, N., Madiagne, D., and Junqueira, L. L., 2008. Initial Electronic Spare Parts Stock and Consumption Forecasting, Investigação Operacional, 28, 45-58.
89. Gujarati, D. and Porter, D., Introduction to Forecasting Basic Econometrics (5th Ed.), McGraw-Hill/Irwin.
90. Hatchett, J.W., McNall, P. F., Scheardy, D.A. and Zehna, P. W., 1966. A Repairable Item Inventory, United States Naval Postgraduate School, Technical Report/Research Paper No. 71.
91. Jean-François Mathieu, 2016, Smart Logistics for better after-sales services, UPS Europe.
92. KAPOOR, R., and AMBEKAR, S., 2015. Closed loop Repairable Parts Inventory System: a Literature Review, Indian Journal of Economics & Business, 14 (1), 31-47.
93. Kaki A., 2007, Forecasting end-of-life spare parts procurement, Helsinki University, System Analysis Laboratory.
94. Kordic, V.; Lazinica, A. & Merdan, M., 2006. Manufacturing the Future, Concepts - Technologies – Visions, ARS/plV (ed), Germany.
95. Makridakis S. and S.C. Wheelwright, 1989. Forecasting Methods for Management, John Wiley & Sons, New York.
96. Nenni1, M. E., Tecchio, P., and Politeconico, J., 2013. Optimizing Spare Parts Inventory in Shipping Industry, International Journal of Engineering and Technology (IJET),1, 3.
97. Paqium, R., 2014. NPI velocity in discrete manufacturing: the hidden cost of late product, Aberdeen Groups.
98. Paqium, T., 2017. IOT and Field Service: Leveraging Connected Devices to Provide Exceptional Service, Aberdeen Group.
99. Pinder, A., July 2014. After the deal is sealed: Should Sales care about service? Aberdeen Group.
100. Pinder, A., 2016. State of Service Management in 2016 Empowerment the Data-Driven CSO, Aberdeen Group.
101. Pinder, A., 2015. Flash Forward: See the Future of Field 3D, Aberdeen Group.
102. Pinder, A., 2016. Service Parts Management: The Aftermarket can’t be an Afterthought, Aberdeen Group.
103. Rapoza, J. 2016. Real User Data is Vital for Good Performance Management, Aberdeen Group.
104. Reni, C., Mar. 2016. Customer Experience’s Secret Weapon: Responding to Customer Feedback Fast, CustomerGauge.
105. Hyken, S. Jan 2017. Ten Customer Service and Experience Trends for 2017, Forbes.
106. Tysseland, B.E. and Halskau, Ø., 2007. Spare parts inventory - A literature review with focus on initial provision and Obsolescence management in Proceedings. 19th Annual NOFOMA Conference, 1075-1092.
107. Yang, K. H., and Wu, K. H., 2015. The impact factor study of the lifecycle of recyclable spare parts, paper presented at the meetings of the 2015 International Conference on Robotics, Mechanics, and Mechatronics (ICRMM 2015), March 21th-23th, 2015, Singapore.
108. Yang, K. H., and Wu, K. H., 2015. The link between new product introduction, customer satisfaction, service quality, and the spare part availability, paper presented at the meetings of The Asian Network for Quality (ANQ) and Chinese Society for Quality (CSQ, Chinese Taipei), Sept. 23nd-24th, 2015, Taipei, Taiwan (R.O.C.).