This paper develops an algorithm to determine the batch size of the batch process in real time for improving production and efficient control of production system with multiple processes and batch processes. It is so important to find the batch size of the batch process, because the variability arising from the batch process in the production system affects the capacity of the production. Specifically, batch size could change system efficiency such as throughput, WIP (Work In Process) in production system, batch formation time and so on. In order to improve the system variability and productivity, real time batch size determined by considering the preparation time and batch formation time according to the number of operation of the batch process. The purpose of the study is to control the WIP by applying CONWIP production system method in the production line and implements an algorithm for a real time batch size decision in a batch process that requires long work preparation time and affects system efficiency. In order to verify the efficiency of the developed algorithm that determine the batch size in a real time, an existed production system with fixed the batch size will be implemented first and determines that batch size in real time considering WIP in queue and average lead time in the current system. To comparing the efficiency of a system with a fixed batch size and a system that determines a batch size in real time, the results are analyzed using three evaluation indexes of lead time, throughput, and average WIP of the queue.

This paper seeks to present a multi-control method that can contribute to effective control of the production line with multiple bottleneck processes. The multi-control method is the production system that complements shortcomings of CONWIP and DBR, and it is designed to determine the raw material input according to the WIP level of two bottleneck processes and WIP level of total process. The effectiveness of the production system developed by applying the multi-control method was verified by the following three procedures. Raw material input conditions of the multi-control method are as follows. First, raw materials are go into the production line when the number of the total process WIP is lower than established number of WIP in total process and first process is idle. Second, raw materials are introduced when the number of WIP of two bottleneck processes is lower than the established number of WIP of each bottleneck process. Third, raw materials are introduced when the first process and in front of bottleneck process are idle even if the number of WIP in the total process is less than established number of WIP of the total process. The production line with two bottleneck processes was selected as the condition for production environment, and the production process modeling of CONWIP, DBR and multi-control production method was defined according to the production condition. And the optimum limited WIP level suitable for each system was obtained by applying a genetic algorithm to determine the total limited number of WIP of CONWIP, the limited number of WIP of DBR bottleneck process, the number of WIP in the total process of multi-control method and the limited number of WIP of bottleneck process. The limited number of WIP of CONWIP, DBR and multi-control method obtained by the genetic algorithm were applied to ARENA modeling, which is simulation software, and a simulation was conducted to derive result values on the basis of three criteria such as production volume, lead time and number of goods in-progress.

CONWIP is robust and efficient for various type of operating system, such as series, parallel, and assembly systems. Especially, assembly system would be controlled couple of modified CONWIP system. In the following paper, we developed Critical Path CONWIP system that gives signal to sub-line from a station of critical path then, compared with m-conwip, discrete-card-buffer CONWIP. 2 representative asymmetric assembly system models are used to compare each control system. As a result, critical path CONWIP holds less whole work-in-process with similar output. It can decrease total cost and WIP for high holding cost assembly system

The traditional Kanban needs a lot of preconditions for fitting conditions of dynamic production processing environment. The traditional Kanban isn't suitable conditions of dynamic production processing environment. Therefore conditions of dynamic production processing environment is needed more stable system. This study is describe CONWIP system such as suitable in dynamic production processing environment. Most Pull system is a Kanban system than use Kanban cards or signal for production management and inventory control. The object of Kanban system is reducing inventory between shop-floor that can reduce inventiry cost. If the system reduce the number of Kanban cards would be reduce the working process WIP, can be reduced and can be found all potential problem of production between shop-floors. This study apply to CONWIP system model for Korean industrial companies.

동적환경하에서의 JIT 생산 시스템의 운영에 관한 연구는 Terada, Kimura(1981), Bitran과 Chang(1985), Deleersnyder(1989), Mitra, Mitrani(1990) 그리고 Philipoom(1990)에 의한 분석적 모델의 발표로부터 시작하여 Terada와 Kimura(1981)의 다단계 연속 생산 시스템에서 간판 시스템에 대한 여러 가지 기본 공식의 제공, Bitan과 Chang(1985)에 다단계 스테이지의 조립생산 시스템에서 여러 가지 기본 공식과 해의 절차의 발표로 발전되어 왔다. 그 이후 Spearman 은 CONWIP을 이용한 간판 시스템의 변형된 형태를 연구ㆍ발표하였고(1990), Generic 간판 시스템에 대한 Chang과 YIH (1994)에 의해 연구되었다. Hybrid Push/Pull 시스템의 하나인 CONWIP 시스템은 현재까지 다른 시스템보다 정책면에서 동적인 기업환경에 적합한 것으로 평가받고 있다. 본 논문은 생산/제조 시스템의 운용에 대해 동적인 기업환경 하에서 고전적 kanban 시스템보다 우월하다고 입증된 CONWIP 시스템을 모형화하고 시스템 운영에 대한 실례를 들어 비선형 계획법의 하나인 내부점 알고리즘으로 수행, 해의 수렴과정을 고찰 기존의 시뮬레이션 결과와 비교 고찰하고자 한다.