以鞋業製造而言，典型的生產線根據製程順序可以切分成三段生產區域：裁加、針車以及成型，而在生產過程中，裁加與針車之間以及針車與成型之間在製品的傳遞有三個關鍵的控制因子，將會一定程度的影響產線的生產效率，分別是在製品水準設定、搬運批量以及搬運頻率。然而，控制因子分別有多種水準，並且因子之間也可能存在著交互作用，要如何訂定此三項因子的水準組合並不是一件容易的事，因此，鞋廠生產線的管理者通常憑藉著主觀的工作經驗或沿用舊規，來設定因子水準的數值。
本研究主要致力於建構一個具備代表性的鞋業生產線模擬模型，並且探討三項控制因子對於產線關鍵績效指標的影響，如：每人每小時之生產雙數、總在製品水準以及生產週期時間。研究中模擬模式的建構透過產學合作，對象為一座位於中國南方生產品牌鞋款的製鞋工廠；模式確認部份則是與廠內專家合作討論，比對數據遽以完成。模擬結果顯示，不同因子水準的組合確實影響績效指標的表現，而基於實驗設計的概念，本研究也找出了三項控制因子最佳的水準組合。

In footwear manufacturing, a typical production line can be separated into three production areas: cutting/preparation, stitching and assembling, according to the sequence of manufacturing process. Between cutting/preparation and stitching as well as between stitching and assembling, Work-in-process (WIP) level setting, transportation batch size and transportation frequency are three critical control factors affecting the production efficiency. However, it is difficult to optimally determine these three control factors due to multiple levels of each factor and the interactions among these factors. Therefore, factory managers tend to set these factors based on experiences.
This study aims to build up a representative simulation model in footwear manufacturing and to investigate the effect of the control factors on Key Performance Indicators (KPIs) such as pairs per man hour (PPMH), total WIP level, and cycle time. The development and validation of the model is done in cooperation with experts from a footwear factory making name brand shoes located in south China. The simulation results show that different combinations of different levels of these control factors lead to different KPI performance and the “optimal” combination of these factors is investigated on the basis of experimental design.

Chen, J. C., Huang, P. B., Peng, H.Y., Hung, M. C., Chen, C. C., Peng, T. W., Wei, Y.Y., and Feng, C. H. (2011). CONWIP for Order Release and WIP Control in Color Filter Fabs. SID Symposium Digest of Technical Papers, 42(1), 1388-1391.
Chen, J. C., Lee, S.H., Chen, C. Y., Chen, C. C., and Peng, T. W. (2012). Simulation-based look-ahead release planning for color-filter fabs. SID Symposium Digest of Technical Papers , 21(1), 1264-1267.
Chen, J. C., Su, L. H., Chao, G. C., Chen, C. C., and Peng, T. W. (2012). Capacity improvement for color-filter fabs through computer modeling and iterative simulation. Journal of the Society for Information Display, 19(7), 480-487.
Chen, J. C., Putra, A. P., Anggono, N., Chen, Jeff. and Su, Y. S., (2014). Simulation Modeling and Analysis for Stitching Line of Footwear Industry. International Conference on Industrial Engineering and Operations Management. 1099-1106.
Chen, J. C., Anggono, N., Putra, A. P., Chou, River and Chang, E.S. (2014). Simulation Modeling and Analysis of Line Length and Batch Size in Footwear Factory. International Conference on Industrial Engineering and Operations Management. 1173-1180.
Derringer, G., Suich, R. (1980). Simultaneous Optimization of Several Response Variables.. Journal of Quality Technology, 12(4), 214-219.
Eryilmaz, M. S., Kuşakci, A. O., Gavranovic, H., and Findik, F. (2012). Analysis of Shoe Manufaturing Factory by Simulation of Production Processes. Southeast Europe Journal of Soft Computing, 1(1), 120-127.
Fishman, G. S. (2001). Discrete-Event Simulation: Modeling, Programming, and Analysis. Baker & Taylor Books.
Golding, F. Y. (1902). The manufacture of boots and shoes: being a modern treatise of all the processes of making and manufacturing footgear. London: Chapman & Hall.
Greasley, A. (2008). Using simulation for facility design: A case study. Simulation Modelling Practice and Theory, 16(6), 670-677.
Kleijnen, J. and van Groenendaal, W. (1992). Simulation: A Statistical Perspective. Chichester: John Wiley & Sons Ltd..
Knepell, P. L. and Arangno, D. C. (1993). Simulation Validation: A Confidence Assessment Methodology. Los Alamitos: IEEE Computer Society Press.

Koo, P. H., Bulfin, R., and Koh, S. G. (2007). Determination of Batch Size at A Bottleneck Machine in Manufacturing Systems. International Journal of Production Research, 45(5), 1215-1231.
Law, A. M. (2003). How to Conduct A Successful Simulation Study. Winter Simulation Conference, 66-70.
Law, A. M. (2009). How to Build Valid and Credible Models. Winter Simulation Conference , 24-33.
Law, A. M. and Kelton, W. D. (2007). Simulation Modeling and Analysis. McGraw Hill.
Lin, Y. K., Chang P. C., and Chen J. C. (2012) Performance evaluation for a footwear manufacturing system with multiple production lines and different station failure rates. International Journal of Production Research, 51(5), 1603-1617
Lin, J. T., Wang, F. K., Wu, C. K. (2003). Simulation Analysis of the Connecting Transport AMHS in a wafer fab. IEEE Transctions on Semiconductor Manufacturing, 16(3), 555-564
Miller, S. and Pegden, D. (2000). Introduction to Manufacturing Simulation. Winter Simulation Conference, 63-66.
Myers, R. H. and Montgomery, D. C. (1995). Response Surface Methodology. New York: Wiley.
Nisanci, H. I., and Sury, R. J. (1980). Production Analysis by Simulation in A Shoe Manufacturing Factory. International Journal of Production Research, 18(1), 31-41.
Pillai, D. D., Bass, E. L., Dempsey, J. C. and Yellig, E. J. (2004). 300-mm full-factory simulations for 90-and 65-nm IC manufacturing. IEEE Transactions on Semiconductor Manufacturing, 17(3), 292-298.
Portuguese Footwear, Components, Leather Goods Manufacturers’ Association (APICCAPS). (2011). World Footwear Yearbook..
Portuguese Footwear, Components, Leather Goods Manufacturers’ Association (APICCAPS). (2012). World Footwear Yearbook.
Stevenson, W. J. (2007). Operation management: international student edition with global readings. New York: McGraw-Hill.
Yang, T., Hsieh, C. H and Cheng B, Y. (2010). Lean-pull strategy in a re-entrant. International Journal of Production, 49(6), 1511-1529.
United Nations, Department of Economic and Social Affairs. (2013). Population, Development and Environment.