Articles & Issues
- Language
- korean
- Conflict of Interest
- In relation to this article, we declare that there is no conflict of interest.
- Publication history
-
Received December 5, 2007
Accepted February 5, 2008
-
This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits
unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright © KIChE. All rights reserved.
All issues
불확실한 공정과 불량품 처리체계를 포함하는 공정-저장조 망 최적설계
Optimal Design of Batch-Storage Network Including Uncertainty and Waste Treatment Processes
부경대학교 화학공학과, 608-739 부산광역시 남구 용당동 산 100 1동국대학교 화공생물공학과, 100-715 서울시 중구 필동3가 26
Department of Chemical Engineering, Pukyong National University, San 100 Yongdang-Dong Nam-Gu, Busan 608-739, Korea 1Department of Chemical and Biochemical Engineering, Dongguk University, 3 Ga 26 Pil-Dong Jung-Gu, Seoul 100-715, Korea
Korean Chemical Engineering Research, June 2008, 46(3), 585-597(13), NONE Epub 7 July 2008
Download PDF
Abstract
본 연구의 목적은 가동 시간과 생산량에 있어서 무작위 변동을 일으키는 공정 시스템에서 최종 제품의 수요를 만족 하는 공정-저장조 망구조의 최적용량을 결정하는 문제의 해석적인 해를 유도하는 것이다. 여기서 논의되는 공장의 구조는 회분식 공정과 저장조가 병렬 또는 직렬로 연결된 망구조를 구성하고 있다. 생산공정은 다수의 원료물질을 다수의 제품으로 일정 비율로 전환한다. 최종제품의 수요는 주문주기와 물량이 무작위 변동을 일으킨다. 일부 생산공정은 생산량에 있어서 무작위 변동을 일으키며, 오염된 물질은 재생공정이나 폐기과정을 거쳐서 처리된다. 다른 공정들은 모두 가동시간이 무작위로 변한다. 최적화의 목적함수는 총비용을 최소화하는 것인데, 여기서 총비용은 준비비와 재고 유지비 그리고 공정과 저장조의 자본비용으로 구성되어 있다. 새로운 생산 재고 분석도구인 사각파 모형은 무작위 흐름의 상한값과 하한값을 계산하는 도형적 방법을 제공한다. 이 모형의 장점은 공정과 저장조 사이의 무작위 흐름을 사실적으로 묘사하면서도 간단한 해석적인 해를 제공하는데 있다. 결과적으로 계산량이 획기적으로 줄어든다.
The aim of this study was to find an analytic solution to the problem of determining the optimal capacity (lotsize) of a batch-storage network to meet demand for a finished product in a system undergoing random failures of operating time and/or batch material. The superstructure of the plant considered here consists of a network of serially and/or parallel interlinked batch processes and storage units. The production processes transform a set of feedstock materials into another set of products with constant conversion factors. The final product demand flow is susceptible to short-term random variations in the cycle time and batch size as well as long-term variations in the average trend. Some of the production processes have random variations in product quantity. The spoiled materials are treated through regeneration or waste disposal processes. All other processes have random variations only in the cycle time. The objective function of the optimization is minimizing the total cost, which is composed of setup and inventory holding costs as well as the capital costs of constructing processes and storage units. A novel production and inventory analysis, the PSW (Periodic Square Wave) model, provides a judicious graphical method to find the upper and lower bounds of random flows. The advantage of this model is that it provides a set of simple analytic solutions while also maintaining a realistic description of the random material flows between processes and storage units; as a consequence of these analytic solutions, the computation burden is significantly reduced.
References
Subrahmanyam S, Peknyt JF, Reklaitis GV, Ind. Eng. Chem. Res., 33(11), 2688 (1994)
Hax AC, Candea D, Production and Inventory Management, Englewood Cliff : Prentice-Hall (1984)
Barbaro A, Bagajewicz MJ, AIChE J., 50(5), 990 (2004)
Sahinidis NV, Comput. Chem. Eng., 28(6-7), 971 (2004)
Petkov SB, Maranas CD, Ind. Eng. Chem. Res., 36(11), 4864 (1997)
Petkov SB, Maranas CD, AIChE J., 44(4), 896 (1998)
Balasubramanian J, Grossmann IE, Comput. Chem. Eng., 27(4), 469 (2003)
Lin XX, Janak SL, Floudas CA, Comput. Chem. Eng., 28(6-7), 1069 (2004)
Yin KK, Yin GG, Liu H, AIChE J., 50(11), 2877 (2004)
Moyle DT, Mitchell CM, CEP, 100(10), 39 (2004)
Yi G, Reklaitis GV, AIChE J., 49(12), 3084 (2003)
Papoulis A, Probability, Random Variables, and Stochastic Processes, Korea: McGraw-Hill (1984)
Yi G, Reklaitis GV, AIChE J., 50(11), 2849 (2004)
Hax AC, Candea D, Production and Inventory Management, Englewood Cliff : Prentice-Hall (1984)
Barbaro A, Bagajewicz MJ, AIChE J., 50(5), 990 (2004)
Sahinidis NV, Comput. Chem. Eng., 28(6-7), 971 (2004)
Petkov SB, Maranas CD, Ind. Eng. Chem. Res., 36(11), 4864 (1997)
Petkov SB, Maranas CD, AIChE J., 44(4), 896 (1998)
Balasubramanian J, Grossmann IE, Comput. Chem. Eng., 27(4), 469 (2003)
Lin XX, Janak SL, Floudas CA, Comput. Chem. Eng., 28(6-7), 1069 (2004)
Yin KK, Yin GG, Liu H, AIChE J., 50(11), 2877 (2004)
Moyle DT, Mitchell CM, CEP, 100(10), 39 (2004)
Yi G, Reklaitis GV, AIChE J., 49(12), 3084 (2003)
Papoulis A, Probability, Random Variables, and Stochastic Processes, Korea: McGraw-Hill (1984)
Yi G, Reklaitis GV, AIChE J., 50(11), 2849 (2004)
