• Proceedings of the Korean Operations and Management Science Society Conference
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• 1992.04b
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• pp.249-257
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• 1992

An automated machining system involves concurrent use of manufacturing resources, alternative process plans, and flexible routings. High investment in the installation of automated facilities requires an efficient scheduling system that is able to allocate the resources specified for operations over a scheduling horizon. The primary emphasis of this paper is to generate schedules that accurately reflect details of the automated environment and the objectives stated for the system. In this paper, a scheduling algorithm for automated machining is presented. Using the previous simulation research for this topic, a rule-based scheduling system is constructed. An architecture for an intelligent scheduling system is proposed, and the system has a high potential to provide efficient schedules based on the task-specific knowledge for the dynamic scheduling environment

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.5
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• pp.527-537
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• 1990

This paper describes an intelligent control-based job scheduler, named ESIJOBS, for flexible manufacturing system. In order to construct rulebase of this system, traditional rules of job scheduling in FMS are examined and evaluated. This result and the repetitional simulations with graphic monitoring system are used to form the rulebase of ESIJOBS, which is composed of three parts:six part selection rules, four machine center selection rules, and twenty-one metarules. Appropriate scheduling rule sets are selected by this rulebase and manufacturing system status. The performances of all simulations are affected by random breakdowns of major FMS components during each simulation. Six criteria are used to evaluate the performance of each scheduling. The two modes of ESIJOBS are simulated and compared with combinational 24 rule-set simulations. In this comparison ESIJOBS dominated the other rule-set simulations and showed the most excellent performance particularly in three criteria.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.4
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• pp.219-229
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• 2010

The PERT/CPM are considered as the base procedures for the most successful project scheduling programs. Unfortunately, it is not easy to apply these procedures to real-life projects. This is due to the fact that PERT/CPM assume an infinite number of resources for each activity in project networks. Obviously, the completion time under no constraints is less than when constraints are imposed. One way of approaching this problem is to use heuristic solution techniques. In this paper, we present three heuristics; MRU (Maximum Resource Use) rule, STU (Shortest Time Use) rule, MRUP (Max Resource Use and Period) rule for allocating resources to activities of projects under multiple resource constraints. Comparisons of the project durations show that these heuristic rules are superior to AG3 rule that has been widely used in practice (Elsayed and Boucher, 1994).

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.299-302
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• 1996

The purpose of this study is developing scheduling logic and program for machining scheduling of automobile part production line with unbalanced processing time. Three rules are developed to minimize slack and effect on other job. Fourth rule is suggested which considered weighted sum of three factors. schedule is generated totally 1, 000 times and then optimal weight parameter is selected. The program is developed to schedule situation to compare with the performance measure, total finish time of machine and total tardiness of part. As a result, the rule which considered weighted sum of three factors is effective for both measure.

• Journal of the Korea Safety Management & Science
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• v.2 no.2
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• pp.85-94
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• 2000

This paper deals with the selection of a proper dispatching rule for an one-process Job scheduling that follows a particular distribution of an order production. That is, it makes a distribution on an order per unit period and applies to simulation model that uses it. This study consists of two purposes either seeks adequately production scheduling using priority rule or seeks extension of the facilities that increase current production efficiency through computer simulation in scheduling.

• Industrial Engineering and Management Systems
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• v.3 no.1
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• pp.12-21
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• 2004

This paper investigates the design of a priority rule in a multi-product disassembly environment. Specifically, it is concerned with product scheduling by which the inventory control of disassembled parts can be incorporated into a priority rule to reduce part lead times. The part lead time consists of two components: flow time and supply delay. The primary focus of the paper is on the development of a disassembly priority rule that aims to reduce the supply delay. We propose a priority rule, called Minimum Distance (MD) rule, to improve the supply delay performance. Finally, we provide a comparative analysis on the performance of traditional rules and the new rule proposed in this paper via a simulation model.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.5 no.1
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• pp.04-10
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• 1987

We consider a time sharing computer system with a single processor where tasks ofK different types arrive at the system according to independent time homogeneous Poisson processes from outside. A task, after given a quantum for processing, leaves the system, or changes the type and rejoins the system according to specified probabilitycs. While many existing priority time sharing models determine the priorities of tasks strictly by their service time requirements, this paper develops a new scheduling rule wherein the importances or urgencies in addition to the service time requirements of tasks are counted, by inposing an appropriate reward structure on the system. Also presented is the algorithm through which to determine the rankings of K types according to this new scheduling rule.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.8
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• pp.831-840
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• 1992

This paper presents an efficient short-term generation scheduling method using a rule-based expert/consulting system approach to assist electric energy system operators and planners. The expert system approach is applied to improve the Dynamic Programming(DP) based generation scheduling algorithm. In the selection procedure of the feasible combinations of generating units at each stage, automatic consulting on the manipulation of several constraints such as the minimum up time, the minimum down time and the maximum running time constraints of generating units will be performed by the expert/consulting system. In order to maximize the solution feasibility, the aforementioned constraints are controlled by a rule-based expert system, that is, instead of imposing penalty cost to those constraint violated combinations, which sometimes may become the very reason of no existing solution, several constraints will be manipulated within their flexibilities using the rules and facts that are established by domain experts. In this paper, for the purpose of implementing the consulting of several constraints during the dynamic process of generation scheduling, an expert system named STGSCS is developed. As a building tool of the expert system, C Language Integrated Production System(CLIPS) is used. The effectiveness of the proposed algorithm has been demonstrated by applying it to a model electric energy system.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.488-492
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• 1991

This paper deals with modeling and scheduling for flexible manufacturing systems(FMS). In modeling extended Petri nets are used to describe various and complex properties. To resolve multiple conflict without predefined properties, such as part selection, machine selection, rule-based scheduling method is introduced. This structure have a capability of on-line scheduling with systematic modeling description.

• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.1
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• pp.57-57
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• 1988

This paper develops an adaptive scheduling policy for flexible manufacturing systems. The inductive learning methodology used for constructing this state-dependent scheduling policy provides and understanding of the relative importance of the various system parameters in determining the appropriate scheduling rule. Experimental studies indicated the superiority of the suggested approach over the alternative approach involving the repeated application of a single scheduling rule for randomly generated test problems as well as a real system, and under both stationary and nonstationary conditions. In particular, its relative performance improves further when there are frequent disruptions, and when disruptions are caused by the introduction of tiiight due date jobs, one of the most common surces of disruptions in most manufacturing systems.