存貨管理的目標通常是如何運用最少成本創造出最大的客戶服務水準，在不同的生產環境下如何找出最佳的平衡點便是企業經營管理的挑戰。在化學顏料產業裡，產品數量多且彼此不可互相替代的現況下，導致成品庫存管理的難度增加，半成品概念藉此迎運而生，企業如何取捨半成品的生產項目及設定最佳的安全存量成為現階段重要的議題。
本研究提出一生產與存貨策略模式，利用過去的歷史資料來預測未來某固定期間內的半成品需求量，並針對此固定期間半成品之存貨備料進行生產策略分析，建立一最適化存貨模型，以求出半成品最適的存貨水準。最後本研究將所得到的存貨成本與2011年實際存貨成本數據比較後，證實本研究所提出的生產與存貨策略模式優於原來使用的生產模式，可有效降低存貨成本。本研究結論並提出欲達到最小化存貨成本時，預測週期與平滑指數參數的設定建議，提供第一次採用此生產與存貨策略模式之設定參考。

The main purpose of the thesis is to minimize total inventory cost, while creating the maximum values for customer service. In the pigment industry, a variety of work in progress is required to produce customized goods and hence the production plan and inventory policy for work in progress are essential in balancing efficiency and customer value.
This thesis develops a model of production and inventory strategy for work in progress in the pigment industry. Based on the historical data, the model use data analyses to forecast product demands, and deploys an inventory control model. The numerical results indicate that the proposed model performs well in terms of cost reduction. In addition, they suggest some practical guideline for setting the model parameters in different scenarios.

王木琴，生產管理，台灣復文興業，1996。
林江亮、郭弘卿、吳仁杰，橫斷面權益評價模式正確性與解釋變動能力之實證研究，會計學報，1(1)，83-109，2008。
林聰明、吳水丕，指數平滑法之選擇與應用，華泰文化，1981。
吳柏林，時間數列分析導論，華泰文化，1995。
武為棣，週期性產品之二階存貨模型─上游製造商擁有定價控制權之情況，博碩士論文，國立成功大學，2000。
張保隆，生產管理四版，華泰書局，2011。
顏憶茹、張淳智，物流管理，前程文化事業有限公司，2005。
Allen, D.S., Changes in inventory management and the business cycle, Federal Reserve Bank of St. Louis, 17-26,1995.
Aucamp, D. C., Evaluation of safety stock, Production & Inventory Management, 27(2), 126-132, 1986.
Baker, K. R., Magazine, M. J., Nuttle, H. L. W., The effect of commonality on safety stocks in a simple inventory model, Management Science, 328, 982-988, 1988.
Benton, W. C., Safety stock and service levels in periodic review inventory systems, Journal of the Operational Research Society, 47, 562-569, 1996.
Ben-Daya, M., Raouf, A., Inventory models involving lead time as decision variable, Journal of the Operational Research Society, 45, 579-582, 1994.
Betts, M., Manage my inventory or else, Computer World, 28(5), 93-95, 1994.
Bose, S., Goswami, A. and Chaudhuri, K. S., An EOQ model for deteriorating items with linear time-dependent demand rate and shortages under inflation and time discounting, Journal of the Operational Research Society, 46(6), 771-782, 1995.
Cadenas, E., Jaramillo, O. A. and Rivera, W., Analysis and forecasting of wind velocity in chetumal, Quintana roo, using the single exponential smoothing method, Renewable Energy, 35, 925-930, 2010.
Chang, K. J. and Tsai, S. F., On the inventory model with variable lead time and price-quantity discount, Computers & Operations Research, 28(9), 915-934, 2001.
Clark, A. J., Scarf, H., Optimal policies for a multi-echelon inventory problem, Management Science, 6(4), 475-490, 1960.
De Faria, E. L., Albuquerque, M. P., Gonzalez, J. L., Cavalcante, J. T. P. and Albuquerque, M. P., Predicting the Brazilian stock market through neural networks and adaptive exponential smoothing methods. Expert Systems with Applications, 36, 12506-12509, 2009.
Goyal, S. K., Morin, D. and Nebebe,F., The finite horizon trended inventory replenishment problem with shortages, Journal of the Operational Research Society, 43(12), 1173–1178, 1992.
Hadley, G. and Whitin, T. M., Analysis of Inventory Systems, Englewood Cliffs, 1963.
Howell, R. A. and Soucy, S. R., The new manufacturing environment: major trend for management accounting, Management Accounting, 13-19, 1987.
Hung, L. C., Forecasting evaluation of public listed companies revenue in Taiwan tourism industry – comparison between grey forecasting regression analysis and exponential smoothing. Journal of Grey System, 12(2), 59-68, 2009.
Kneafsey, J. T., Transportation Economic Analysis, Lexington, 1975.
Lee, H. L., Information distortion in a supply chain: the bullwhip effect, Management Science, 43(4), 546-558, 1997.
Lee, W. C., Wu, J. W., Hou, W. B., A note on inventory model involving variable lead time with defective units for mixtures of distribution, International Journal of Production Economics, 89, 31-44, 2004.
Li, L., The role of inventory in delivery-time competition, Management Science, 38(2), 182-197, 1992.
Liao, C. J., Shyu, C. H., An analytical determination of lead time with normal demand, International Journal of Operations and Production Management, 11, 72-78, 1991.
Meyer, R. F., An adaptive method for routine short-term forecasting, International Federation of Operational Research Societies, 1963.
Mihaela, T., Stocks volume optimization and their management in case of risk, Faculty of Economics and Business Administration, 55, 9-16, 2008.
Montgomery, D. C., An application of statistical forecasting techniques in an inventory control policy. Production and Inventory Management, 66-74, 1969.
Montgomery, D. C., Adaptive control of exponential smoothing parameters by evolutionary operation. AIIE Transactions, 2(3), 268-269, 1970.
Okan, D., A multivariate model of fuzzy integrated logical forecasting method (M-FILF) and multiplicative time series clustering: A model of time-varying volatility for dry cargo freight market, Expert Systems with Applications, 39, 4135-4142, 2011.
Ouyang, L.Y., Yeh, N.C., Wu, K.S., Mixture inventory model with backorders and lost sales of variable lead time, Journal of the Operational Research Society, 47, 829-832. 1996.
Silver, E. A., Pyke, D. F., Peterson, R., Inventory Management and Production Planning and Scheduling, John Wiley, 1998.
Tan, K. V., Kannan, V. R. and Handfield, R.B., Supply chain management: supplier performance and firm performance, International Journal of Purchasing and Management,2-9, 1998.
Tersine, R. J., Principles of Inventory and Materials Management, North-Holland, 1982.
Tratar,. L. F., Minimising Inventory costs by properly choosing the level of safety stock, Economic and Business Review, 11(2), 109-117, 2009.
Tripathy, P. K., Wee, W. M. and Majhi, P. R., An EOQ model with process reliability considerations, Journal of the Operational Research Society, 54 , 549-554, 2003.
Van Der Heijden, M. C., Supply rationing in multi-echelon divergent systems, European Journal of Operational Research, 101 (3), 532-549, 1997.
Van Der Heijden, M. C., Matthieu C. Multi-echelon inventory control in divergent systems with shipping frequencies, European Journal of Operational Research, 116 (2), 331-351, 1999.
Verrijdt, J. H. C. M., De kok, A. G., Distribution planning for a divergent N-echelon network without intermediate stocks under service restrictions, International Journal of Production Economics, 38, 225-243, 1995.
Verrijdt, J. H. C. M., De kok, A. G., Distribution planning for a divergent depotless two-echelon network under service constraints, European Journal of Operational Research, 89, 341-354, 1996.
Wang, C., An inventory decision model with variable lead time and continuous price decrease, International Symposiums on Information Processing, 31, 670-674, 2008.
Way, D. and Irastorza, J., VMI is for fashion too, Apparel Industry Magazine, 57(3), 16, 1996.
Wei, Y., Chen, M.C., Forecasting the short-term metro passenger flow with empirical mode decomposition and neural networks, Transportation Research Part C, 21, 148-162, 2011.
Wu, J.W., Tsai, H.Y., Mixture inventory model with back orders and lost sales for variable lead time demand with the mixtures of normal distribution, International Journal of Systems Science, 32, 259-268, 2001.
Yang, G., Ronald, R. J., Chu, P., Inventory models with variable lead time and present value, European Journal of Operational Research, 164, 358-366, 2005.