2015.07.30 09:34
author | Kichang Lee |
---|---|
2nd author | / Jinwoo Park (Dept. of Industrial Engineering, Seoul National University) / Hanil Jeong (Dept. of Industrial Engineering, Seoul National University) / Chankwon Park (Dept. of Industrial Engineering, Seoul National University) |
info | International Journal of Production Research (SCI, 0.774), Vol. 40, No. 15, pp.3913-3930, 2002 |
year | 2002 |
c | IJ |
저널/학회 | IJPR |
group | SCI |
keyword | Distributed production; supply network design; Production planning; Distribution planning |
abstract | Corporate strategy can be divided into various substrategies, such as marketing, manufacturing, research and development, etc. In the current enterprise environment, products are highly varied and product life-cycles are shortening owing to customers' changing needs and market competition. In such an environment, the formulation of a good manufacturing strategy is critical for the success of manufacturing enterprises. In this research, for the establishment of good manufacturing strategy, we propose a framework enabling a decision-support system for the modelling and analysis of the manufacturing system. For this task, we have constructed a single integrated object model that contains information about products, processes and resources in the manufacturing system. The model is flexible, allowing the objects in the model to be defined according to the levels of detail required by analysis. The process model can then be trasformed to a generalized stochastic Petri net (GSPN). Furthermore, a Petri net separation procedure is presented to relieve the complexity of the analytic method. By using the analytic analysis of GSPN, the system throughput is easily obtainable. An example is indcluded to demonstrate the applicability of this framework. The proposed decision-support system for manufacturing strategy formulation enables (1) the analysis of the relationship between strategic input variables and performance measures. (2) the scenario evaluation for coordination between the manufacturing department and other departments, and (3) the formulation of manufacturing starategy using what-if analysis against dynamic manufacturing environments. |
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