在國內中小型企業中，大多數的工廠屬於混合存貨及客製化生產型態。此生產型態以需求預測的技術，預先投產並以成品存貨的方式來平抑需求波動及縮短接單前置時間。因此其生產績效極需仰賴需求預測之精確度。但傳統的工令是針對特定產品規格所開立，因此成品存貨皆已客製化，存貨調撥彈性較小，工令指派的彈性也因而受限，決策者必須在成品或半成品存貨成本以及接單前置時間中擇一目標。故此類型之工廠在工令指派上必須具備相當大的彈性，一方面必須存貨成本，也必須兼顧顧客服務水準如期完成訂單。
本研究針對混合存貨及客製化生產型態之作業特性，提出一複合式工令指派方法，以提升此生產型態之半成品調撥、工令指派彈性及有效縮短接單前置時間。並根據生產作業的特性給予各生產區段合適之工令指派法則，以提升生產績效。最後並利用模擬軟體進行個案之應用分析，以評量個案工令指派與複合式工令指派之績效。

There are many business in Taiwan that their production type are indistinct between make-to-stock and make-to-order. This kind of production type can shorten the lead time of order and decrease the fluxion of customer’s demand, on it’s technology of predicting customer’s demand for pre-production and inventory. Thus, the efficacy of production must depend on it’s precision of predicting customer’s demand. Recognition that traditional work order dispatching made to some specific standardization. Therefore, it is leaded to customization product and less flexible. And the decision-maker must choose one goal between minizing inventory cost, WIP’s level and lead time. The production type, work order dispatching must have flexibility,and it must accomplish the customer’s order on time considering inventory cost and customer service.
This thesis hopes that it would be to develop a work order dispatching method to improve the efficiency of WIP administering, the flexibility for work order dispatching and decreasing lead time of customer’s order. According to production’s characteristic of different manufacturing stage, it can create one applicable dispatching rules to increase the production efficiency. Finally, using simulation software, applying to case study comparing the performance of the real case and new work order dispatching

目錄 I
圖目錄 III
表目錄 IV
摘要 V
Abstract VI
第一章 導論 1
1.1 研究背景 2
1.2 研究目的 3
1.3 研究方法與步驟 4
第二章 文獻回顧 7
2.1 生產系統文獻 7
2.2 排程文獻 9
2.2.1 排程問題分類 9
2.2.2 工令指派準則 10
2.2.3 績效評估指標 11
2.3 排程求解方法 16
第三章 問題描述及分析 19
3.1 存貨及客製化生產型態 19
3.2 生產管制系統 20
3.2.1 推擠式生產管制系統 20
3.2.2 牽引式生產管制系統 23
3.2.3 推擠式與牽引式生管系統之問題 23
3.3傳統工令指派分析 26
第四章 複合式工令指派 28
4.1 複合式工令指派架構 28
4.2 複合式工令指派原則 33
第五章 應用分析 37
5.1 個案現況 37
5.2 複合式工令指派應用 40
5.2.1個案導入複合式工令 40
5.2.2實驗設計 43
5.3 模擬評比 47
5.3.1模擬模式建構 47
5.3.2實驗分析 47
5.4營運績效 50
第六章 結論 52
6.1 研究回顧 52
6.2 研究結論 53
6.3 研究貢獻 53
6.4 未來發展 54
參考文獻 55
附錄 A 應用分析之模擬模式 58

參考文獻
[1]. 劉賓陽，趙平宜，1999，「電器容生產管理系統整合」，華容公司產學合作計畫成果報告。
[2]. Aderson, E. J. and Nyrenda, J. C., 1990,”Two new rules to minimize tardiness in a job shop,” International Journal of Production Research, Vol. 28, No. 12, pp. 2277-2292.
[3]. Baker, K. R., 1974, Introduction to sequencing and scheduling, John Wiley, New York.
[4]. Baker, K. R., 1984,”Sequencing rules and due-date assignments in a job shop,” Management Science, Vol. 30, No. 9, pp. 1093-1104.
[5]. Baker, K. R., 1984,”Improved decision rules in a combind system for minimizing job tardiness,” International Journal of Production Research, Vol. 22, No. 6, pp. 917-921.
[6]. Barman, S., 1997,”Simple priority rule combinations: an approach to improve both flow time and tardiness,” International Journal of Production Research, Vol. 35, No. 10, pp. 2857-2870.
[7]. Blackstone, J. H. ,Phillips, D. T. and Hogg, G. L.,”A state-of-art survey of dispatching rules for manufacturing job shop operation,” International Journal of Production Research, Vol. 20, No. 1, pp. 27-45.
[8]. Bonvik, A. M., Couch, C. E. and Gershwin, S. B., 1997,”A comparison of production-line control mechanisms,” International Journal of Production Research, Vol. 35, No. 3, pp. 789-804.
[9]. Dennis, P. C. and Shannon, R. E., 1995, Introduction to simulation using SIMAN, McGraw-Hill, New York.
[10]. Hopp, W. J. and Spearman, M. L.,1996, Factory Physics, McGraw-Hill, New York.
[11]. Kelton, W. D., Sadowski, R. P., 1998, Simulation with Arena, McGraw-Hill, New York.
[12]. Graves, S. C., 1981,”A review of production scheduling,”Operation Research, Vol. 29, No. 4, pp. 646-675.
[13]. Gstettner, S. and Kuhn, H., 1996,”Analysis of production control systems kanban and CONWIP,” International Journal of Production Research, Vol. 34, No. 11, pp. 3253-3273.
[14]. Haupt, R. 1989,” A survey of Priority rule-based scheduling,”OR Spectrum, No. 11, pp. 3-16.
[15]. Holthaus, O. and Chandrasekharan, R., 1997,”New dispatching rules for scheduling in a job shop- An Experimental study,”Advance Manufacturing Technology, Vol. 13, pp. 148-153.
[16]. Kimura, O. and Terada, H., 1981,”Design and analysis of pull system, a method of multi-stage production control,” International Journal of Production Research, Vol. 19, No. 3, pp. 241-253.
[17]. Maccarthy, B. L. and Jiyin, Liu, 1993,” Adressing the gap in scheduling research: a review of optimization and heuristic methods in production scheduling,” International Journal of Production Research, Vol. 31, No. 1, pp. 59-79.
[18]. Melnyk, S. A. and Phillip L. C., 1986, "Scheduling, sequencing, and dispatching: alternative perspectives," Production and Inventory Management, Second quarter, pp.58-67.
[19]. Narasimhan, S. L. and Mangiameli, P. M., 1987, “A comparison of sequencing rules for two stage hybird flow shop,” Decision Sciences, Vol. 18, No. 2, pp. 250-265.
[20]. Panwalker, S. S. and Isander, W., 1977,”A survey of scheduling rules,” Operations Research, Vol. 25, No. 1, pp. 45-61.
[21]. Ramasesh, R. 1990,”Dynanic job shop scheduling: a survey of simulation research,”International Journal of Management science, Vol. 18, No. 1, pp. 43-57.
[22]. Rodammer, F. A. and White, K. P., 1988,”A recent survey of production scheduling,”IEEE Transactions System, Man, and Cybernetics, Vol, 18, No. 6 , pp. 841-851.
[23]. Spearman, M. L. , Woodruff, D. L. and Hopp, W. J., 1990,”CONWIP: a pull alternative to kanban,” International Journal of Production Research, Vol. 28, No. 5, pp. 879-894.
[24]. Sule, D. R, 1997, Industrial scheduling, PWS Publishing Company, Boston.
[25]. Sun, D. and Lin, L., 1994,”A dynamic job shop scheduling framework: a backward apporach," International Journal of Production Research, Vol. 32, No. 4, pp. 967-985.
[26]. Yang, K. K. and Sum, C. C., 1994, “A comparison of job shop dispatching rules using a total cost criterion,” International Journal of Production Research, Vol. 32, No. 4, pp. 807-820.