• Journal of Korean Society of Industrial and Systems Engineering
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• v.12 no.19
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• pp.25-30
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• 1989

This study is concerned with a job sequencing method using the concept of sampling technique. This sampling technique has never been applied to develop the scheduling algorithms. The most job sequencing algorithms have been developed to determine the best or good solution under the special conditions. Thus, it is not only very difficult, but also taken too much time to develop the appropriate job schedules that satisfy the complex work conditions. The application areas of these algorithms are also very narrow. Under these circumstances it is very desirable to develop a simple job sequencing method which can produce the good solution with the short tine period under any complex work conditions. It is called a sampling job sequencing method in this study. This study is to examine the selection of the good job sequence of 1%-5% upper group by the sampling method. The result shows that there is the set of 0.5%-5% job sequence group which has to same amount of performance measure with the optimal job sequence in the case of experiment of 2/n/F/F max. This indicates that the sampling job sequencing method is a useful job sequencing method to find the optimal or good job sequence with a little effort and time consuming. The results of ANOVA show that the two factors, number of jobs and the range of processing time are the significant factors for determining the job sequence at $\alpha$=0.01. This study is extended to 3 machines to machines job shop problems further.

• Management Science and Financial Engineering
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• v.3 no.2
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• pp.29-43
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• 1997

Many heuristics have been developed in order to overcome the computational complexity of job shop problems. In this research, we develop a new heuristic by selecting four simple dispatching rules, i.e., SPT, LPT, SR and LR, dynamically as scheduling proceeds. The selection is accomplished by using artificial neural networks. As a result of testing on 50 problems, the makespan obtained by our heuristic is, on the average, 13.0% shorter than the longest makespan, and 0.4% shorter than the shortest makespan obtained by existing dispatching rules.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.114-119
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• 2002

사출성형금형은 일반적으로 주문설계생산(Engineer-to-Order)방법에 의해 단품 또는 소량으로 제작된다 금형을 제작하기 위한 생산일 정계획은 여러 금형을 동시에 생산하기 위하여 자원을 언제 어떤 공정 및 부품에 할당할 것인가를 결정한다. 일반적으로 제조공장의 능력은 유산하므로 자원의 제약이 일정계획에 직접적인 영향을 준다. 본 논문에서는 자원제약 하에 있는 금형 공장에서 공정외주 비용과 납기 미준수 비용을 고려하여 금형을 구성하는 각 부품의 생산일정과 내외작 여부를 결정하는 최적화 모형과 이를 현실적으로 해결하는 휴리스틱 모형을 제시한다. 제시된 휴리스틱 모형은 조립공정배치 알고리듬인COMSOAL을 기반으로 job shop 형태의 생산공장과 프로젝트 일정계획을 혼합한 형태를 갖는다.

• Korean Management Science Review
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• v.17 no.2
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• pp.125-134
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• 2000

Keeping the promised delivery date for a customer order is crucial for a company to promote customer satisfaction and generate further businesses. For this, a company should be able to quote the delivery date that can be achieved with the capacity available on the shop floor. In a dynamic make-to-order manufacturing environment, the problem of determining a delivery date for an incoming order with consideration of resource capacity, workload, and finished-product inventory can hardly be solved by an analytical solution procedure. This paper considers a situation in which a delivery date for a customer order is determined based on a job schedule, and presents the SimTriD algorithm that provides the best scheduling for determining a delivery date of customer order through the job schedule that efficiently utilizes manufacturing resources with consideration of interacting factors such as resource utilization, finished-product inventory, and due date.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.237-242
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• 2002

The sales activity of most of small manufacturing companies is based on orders of buyers. The process of promotion, receipt and selection of orders of the manufacturers is closely coupled with the load status of the production lines. The decision on whether to accept an order or not, or the selection of optimal order set among excessive orders is entirely dependent on the schedule of production lines. However, in the real world, since the production scheduling activity is mainly performed by human experts, most of small manufacturers are suffer from being unable to meet due dates, lack of rapid decision on the acceptance of new order. To cope with this problem, this paper deals with the development of an agent for selecting an optimal order set automatically. The main engine of selection agent is based on the typical job-shop scheduling model since our target domain is the injection molding company. To solve the problem, we have formulated it as IP (Integer Program) model, and it has been successfully implemented by ILOG and selection agent. And we have suggested an architecture of an agent for tackling web based order selection problems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.9
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• pp.3232-3238
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• 2010

As flexible manufacturing systems (FMSs) are highly automated and required flexibility to satisfy market need, dispatching rules are constrained by specific environments of manufacturing systems such as mechanical failures, absence of employees, and lack of spare parts. In this paper, an ontology-based knowledge approach is proposed to improve efficiency of system through adapting suitable dispatching rules, considering context in a FMS shop floor, which consists multiple manufacturing cells. the multi-agents monitor manufacturing system status and job so that it figures out a dispatching rule considering context. To demonstrate the proposed approach, a proof-of-concept prototype system has been implemented in the $JADE^{TM}$ platform and Protege to make OWL DL ontology.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.9
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• pp.2297-2311
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• 1994

This paper presents the study on the development of a DNC, system IPIS(Interactive Plant Information System)/DNC, which can manage NC machines and robots as a distributed control method in the machine. processing factory. The IPIS/DNC system is composed of a host computer, satellites and NC machines. A set of software modules are developed on the host computer and the satellites separately. By modularizing each functions of the IPIS/DNC system and using multi-taking method, the functions such as NC program management, NC program distribution, and shop monitoring can be performed on the host computer, and the functions such as NC program transfer to the NC machines, and NC program editing can be performed on the satellites. A Relational database which is linked with job scheduling system is used for IPIS/DNC system.

• IE interfaces
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• v.7 no.3
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• pp.125-135
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• 1994

This thesis reports the development of a Computer-Aided Process Planning system for rotational parts. The developed system ultimately generates process plans for rotational parts through a knowledge-base. The knowledge-base and decision-making algorithms are represented by Pascal computer programming language. We have developed a process planning system which adjusts the sequence of processes by itself to ensure the quality of the parts. This system generates more detailed job sequence and descriptions than other well-known process planning systems. We present realistic and efficient process plans through the integration of process planning and scheduling. This system optimizes flow time of parts by decreasing the number of machine set-ups.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.54
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• pp.77-85
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• 2000

One form of job shop scheduling problem in contemporary automated manufacturing such as flexible manufacturing systems (FMS's) is presented which we call the FMS dispatching priority problem. The FMS dispatching priority problem seeks the best dispatching priority of parts and operations, and is essentially a combinatorial optimization problem. Because of the complicated mechanism of the system, the performance of a given dispatching priority must be evaluated via simulation. Simulated annealing have been applied to the problem, and it is found that appropriate parameter setting will be desirable to get good, if not the optimal, solutions within a limited amount of time under the presence of heavy computational burden due to simulation. More specifically, experiments reveal that initial temperature is the single most important factor among other parameters and factors, and that the appropriate initial temperature depends on the allowable computer time in such a way that the less time one can afford to spend, the lower the appropriate initial temperature should be.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.1
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• pp.41-41
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• 1992

In the real world situations that some jobs need be processed only on certain limited machines frequently occur due to the capacity restrictions of machines such as tools fixtures or material handling equipment. In this paper we consider n-job non-preemptive and m parallel machines scheduling problem having two machines group. The objective function is to minimize the sum of earliness and tardiness with different release times and due dates. The problem is formulated as a mixed integer programming problem. The problem is proved to be Np-complete. Thus a heuristic is developed to solve this problem. To illustrate its suitability and efficiency a proposed heuristic is compared with a genetic algorithm and tabu search for a large number of randomly generated test problems in ship engine assembly shop. Through the experimental results it is showed that the proposed algorithm yields good solutions efficiently.