본 연구는 두 대의 기계로 연속해서 주문 처리를 수행하게 되는 생산시스템의 운영에 있어서 생산자와 고객의 입장을 고려하는 작업투입순서 결정방법을 제시한다. 생산자의 입장에서는 기계의 유휴시간을 최소화하는 것에 관심을 갖고 있고, 고객의 입장에서는 납기지연의 최소화에 관심이 있다고 가정한다. 두 대의 기계로 작업이 진행되는 생산시스템의 운영에 대한 연구는 그동안 많은 연구자들에 의해서 이루어져 왔으나 기계와 기계 사이에 임시저장공간에 대한 제한을 두지 않고 있다. 그런데 그러한 모델들은 작업장에 배치된 기계들 사이에 공간이 충분하여 재공품의 증가를 허용하는 경우에만 적용이 가능하다. 본 연구에서는 임시저장공간에 제한이 있는 생산시스템의 작업투입순서를 결정하는데 있어서 납기지연시간과 기계의 유휴시간을 함께 고려하기 위하여 평가함수를 이용한다. 본 연구에서 제시한 방법에 대해서 Stevens와 Gremmill이 제시한 방법과 비교하여 그 결과를 제시한다.

  In this paper, we consider a planning problem arising from printed circuit board manufacturing industries. Given a set of several types of PCBs, component feeders and surface mounting machines in series in a PCB assembly line, the problem is to define t

This paper is concerned with the integrated problem of line balancing and model sequencing in mixed model assembly lines(MMALBS), which is important to efficient utilization of the lines. In the problem, we deal with the objective of minimizing the overall line length To apply the GAs to MMALBS problems, we suggest a GA representation which suitable for its problems, an efficient decoding technique for the objective, and genetic operators which produce feasible offsprings. Extensive experiments are carried out to analyze the performance of the proposed algorithm. The computational results show that our algorithm is promising in solution quality.

This paper is concerned with the integrated problem of line balancing and model sequencing in mixed model assembly lines(MMALBS), which is important to efficient utilization of the lines. In the problem, we deal with the objective of minimizing the overall line length To apply the GAs to MMALBS problems, we suggest a GA representation which suitable for its problems, an efficient decoding technique for the objective, and genetic operators which produce feasible offsprings. Extensive experiments are carried out to analyze the performance of the proposed algorithm. The computational results show that our algorithm is promising in solution quality.

This paper presents a new method that can efficiently solve the integrated problem of line balancing and model sequencing in mixed-model U-lines (MMULs). Balancing and sequencing problems are important for an efficient use of MMULs and are tightly related with each other. However, in almost all the existing researches on mixed-model production lines, the two problems have been considered separately. A genetic algorithm for balancing and sequencing in mixed-model U line is proposed. A presentation method and genetic operators are proposed. Extensive experiments are carried out to analyze the performance of the proposed algorithm. The computational results show that the proposed algorithm is promising in solution quality.

The sequence which minimizes overall utility work in car assembly lines reduces the cycle time, the number of utility workers, and the risk of conveyor stopping. This study suggests mathematical formulation of the sequencing problem to minimize overall utility work, and present a genetic algorithm which can provide a near optimal solution in real time. To apply a genetic algorithm to the sequencing problem in car assembly lines, the representation, selection methods, and genetic parameters are studied. Experiments are carried out to compare selection methods such as roullette wheel selection, tournament selection and ranking selection. Experimental results show that ranking selection method outperforms the others in solution quality, whereas tournament selection provides the best performance in computation time.