• Korean Management Science Review
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• v.13 no.2
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• pp.25-48
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• 1996

Mixed Model Assembly Lines (MMALs) are increasingly used to produce differentiated products on a single assembly line without work-in-process storage, Usually, a typical MMAL consists of a number of (1) stations doing exactly the same operation on every job, (2) stations involving operations with different choices, and (3) stations offering operations that are not performed on every job, or that are performed on every job but with many options. For stations of the first type there is no sequencing problem at all. However, for the second type a set-up cost is incurred each time the operation switches from one choice to another. At the third type of stations, different models, requring different amounts and choices of assembly work, creates an uneven flow of work along the line and variations in the work load at these stations. When a subsequence of jobs requires more work load than the station can handle, it is necessary to help the operations at the station or to complete the work elsewhere. Therefore, a schedule which minimize the sum of set-up cost and utility work cost is desired. So this study has developed Fixed Random Ordering Rule (FROR), Fixed Ascending Ordering Rule (FAOR), Fixed Descending Ordering Rule, and Extended NHR (ENHR). ENHR is to choose optimal color ordering of each batch with NHR, and to decide job sequence of the batch with it, too. As the result of experiments, ENHR was the best heuristic algorithm. NHR is a new heuristic rule in which only the minimum addition of violations from both partial sequence and unassigned sequence at every branch could be considered. And this is a heuristic sequencing rule for the third type of stations at MMAL. This study developed one more heuristic algorithm to test the performance of NHR, which is named as Practical Heuristic Rule (PHR).

• 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).

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.3
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• pp.212-216
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• 2002

A practical issue is studied to improve the performance of a new energy based method of achieving stable, high performance haptic interface control. The issue is related to resetting the amount of energy accumulated in the Passivity Observer for faster operation. A heuristic method is derived and experimentally tested for the resetting and it is shown to help the PC to operate sooner when the system gets active. Experimental results are presented for the “Excalibur” haptic device.

• Korean Management Science Review
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• v.13 no.3
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• pp.173-186
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• 1996

This paper presents an approach for classifying scheduling problems and selecting a heuristic rule to yield best solution in terms of certain performance measure(s). Classification parameters are employed from previous studies on job shop scheduling and project scheduling. Neural network is used for learning and estimating the performance of heuristic rules. In addition, multi-criteria decision making techniques are employed to combine the preferences for each performance measure and heuristic rule for the problems with multi-objectives.

• Industrial Engineering and Management Systems
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• v.14 no.4
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• pp.401-412
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• 2015

In this paper, we present a modeling approach to production planning for an actual production line and a heuristic method. We also illustrate the successful implementation of the proposed method on the production line. A heuristic algorithm called the push-back algorithm was designed for a single machine earliness/tardiness production planning with distinct due date. It was developed by combining a minimum slack time rule and shortest processing time rule with a push-back procedure. The results of a numerical experiment on the heuristic's performance are presented in comparison with the results of IBM ILOG CPLEX. The proposed algorithm was applied to an actual case of production planning at Woongjin Chemical, a leading manufacturer of filter products in South Korea. The seven-month execution of our algorithm led to a 24.5% decrease in the company's inventory level, thus demonstrating its practicality and effectiveness.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.5
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• pp.485-493
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• 1990

The idea of expert control is to incorporate a rule based expert system in a feedback control system. In this paper, we present some heuristic rules based on relay experiment for the choice of controller structure and the setting of the controller parameters. Heuristic rules are used as an element of the feedback loop in an auto-tuning PID controller. The algorithms are coded in a form which is as pure as possible and the heuristic logic is implemented with the rules. This paper reports an implementation of an expert controller on microcomputer-based system, including an industrial programmable controller.

• Journal of Information Technology Applications and Management
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• v.12 no.4
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• pp.1-12
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• 2005

In general, other conventional researches propose the fuzzy Petri net-based fuzzy reasoning algorithms based on the exhaustive search algorithms. If it can allow the certainty factors representing in the fuzzy production rules to use as the heuristic information, then it can allow the reasoning of rule-based systems to perform fuzzy reasoning in more effective manner. This paper presents a fuzzy Petri net(FPN) model to represent the fuzzy production rules of a rule-based system. Based on the fuzzy Petri net model, a weighted fuzzy reasoning algorithm is proposed to Perform the fuzzy reasoning automatically, This algorithm is more effective and more intelligent reasoning than other reasoning methods because it can perform fuzzy reasoning using the certainty factors which are provided by domain experts as heuristic information

• Journal of Korean Institute of Industrial Engineers
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• v.17 no.2
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• pp.51-61
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• 1991

This paper presents a heuristic method for the Assembly Line Balancing(ALB) of the large-sized product. In the ALB problem of the large-sized product such as bus and truck, the assignments of the Related Task Groups(RTG), the same side tasks, and team tasks should be considered. In this paper, a new concept of the RTG and two kinds of assignment rules are proposed to resolve the above considerations. The first assignment rule allots the RTG with the constraint of the same side tasks to the station while the second allots the RTG to the station, relaxing the above constraint to increase the applicability of the method. An assignment rule for team tasks is also presented. The benefits of the method are to improve work methods, to give more job satisfaction to workers, and to allow greater flexibility in the design of assembly lines.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.3
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• pp.59-65
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• 2010

This paper proposes a modified heuristic mixed model assembly line (MMAL) balancing algorithm that provides consistent station assignments on a model by model basis as well as on a station by station. Basically, some of single model line balancing techniques are modified and incorporated to be fit into the MMAL. The proposed algorithm is based on N.T. Thomopoulos' [8] method and supplemented with several well proven single model line balancing techniques proposed in the literature until recently. Hoffman's precedence matrix [2] is used to indicate the ordering relations among tasks. Arcus' Rule IX [1] is applied to generate rapidly a fairly large number of feasible solutions. Consequently, this proposed algorithm reduces the fluctuations in operation times among the models as well as the stations and the balance delays. A numerical example shows that the proposed algorithm can provide a good feasible solution in a relatively short time and generate relatively better solutions comparing to other three existing methods.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1991.10a
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• pp.281-281
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• 1991