• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.5
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• pp.67-76
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• 2003

The principal operation rule of irrigation reservoir is to accelerate the water use and supply water actively when water is sufficient, and to restrict water use and supply water deficiently in order not to stop the irrigation activity when water is scarce. In drought seasons. water should be saved in order to keep the reservoir not to be dried up during the irrigation season. It is important to know how much water should be saved, depending on the rice-growing season and water storage volume. For the drought control of irrigation reservoirs. the rotational irrigation scheduling in paddy with the operation rule curve developed in this study could be utilized as a software program to install TM/TC system for irrigation water supply by automation facilities.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.1
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• pp.1-13
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• 2012

AESA radar is able to instantaneously and adaptively position and control the beam, and such adaptive beam pointing of AESA radar enables to remarkably improve the multi-mission capability, compared with mechanically scanned array radar. AESA radar brings a new challenges, radar resource management(RRM), which is a technique efficiently allocating finite resources, such as energy and time to each task in an optimal and intelligent way. Especially radar beam scheduling is the most critical component for the success of RRM. In this paper, we proposed the several dispatching rules for radar beam scheduling, and compared the performance on the multi-function radar scenario. We also showed that the dispatching rule which differently applying SPF(Shortest Processing time First) and ERF(Earliest Request time First) according to beam processing latency is the most efficient.

• Journal of the Korea Safety Management & Science
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• v.25 no.2
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• pp.1-8
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• 2023

This paper is proposing a novel machine scheduling model for the unrelated parallel machine scheduling problem without setup times to minimize the total completion time, also known as "makespan". This problem is a NP-complete problem, and to date, most approaches for real-life situations are based on the operator's experience or simple heuristics. The new model based on the Memetic Algorithm, which was proposed by P. Moscato in 1989, is a hybrid algorithm that includes genetic algorithm and local search optimization. The new model is tested on randomly generated datasets, and is compared to optimal solution, and four scheduling models; three rule-based heuristic algorithms, and a genetic algorithm based scheduling model from literature; the test results show that the new model performed better than scheduling models from literature.

• Journal of the Korea Safety Management & Science
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• v.6 no.1
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• pp.219-228
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• 2004

We can be acquire the conformation about on the due date of supplier by using the A TP(A vail able to Promise) function of management about real and concurrent access on the supply chain, also decide the affect about product availability due to forecasting or customer's orders through the A TP. Under the these environments, defines the A TP rule that can improve the customer value and data flow related the LTV(Life Time Value) and builds on a algorithm. In this paper, It consolidates the necessity on a LTV (Life Time Value) and analyzes data which is concerned of Customer Value. Under the these environments, defines the LTV rule that can improve the customer value. And then, Scheduling plays an important role in shop floor planning. Therefore, this study tries to proposed that Scheduling by customer needs group for minimizing the problem.

• IE interfaces
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• v.22 no.1
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• pp.85-94
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• 2009

Nowadays, most of the major manufacturing companies prepare their manufacturing schedule using package based solutions. Even though the accuracy of the detail scheduling result is high at implementation, however, it is low during maintenance period. The main cause of low accuracy during maintenance period is due to difficulties in maintaining the accurate level of master data. In this paper, we propose to easily maintain setup time, which is one of the most important factors required in master data to achieve good scheduling result, after changing job. This paper is mainly focused on how to deduce the factors that influence the setup time in a roll-based manufacturing field with print operations. For this purpose, we employed rule based algorithm and applied for deciding setup time for the existing product items. Likewise, it can be applied to new items without any complex setup procedures, and, finally, it displays the result of the real setup-time and calculated setup-time.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.213-222
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• 1998

The objective of this study is to develop a knowledge-based scheduler applying simulation and knowledge base. This study utilizes a machine induction to build knowledge base which enables knowledge acquisition without domain expert. In this study, the best job dispatching rule for each order is selected according to the specifications of the order information. And these results are built to the fact base and knowledge base using the attribute-oriented induction method and simulation. When a new order enters in the developed system, the scheduler retrieves the knowledge base in order to find a matching record. If there is a matching record, the scheduling will be carried out by using the job dispatching rule saved in the knowledge base. Otherwise the best rule will be added to the knowledge base as a new record after scheduling to all the rules. When all these above steps finished the system will furnish a learning function.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.5
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• pp.651-657
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• 1998

In this study, an intelligent scheduling with hybrid architecture, which integrates expert system and neural network, is proposed. Neural network is trained with the data acquired from simulation model of FMC to obtain the knowledge about the relationship between the state of the FMC and its best dispatching rule. Expert system controls the scheduling of FMC by integrating the output of neural network, the states of FMS, and user input. By applying the hybrid system to a scheduling problem, the human knowledge on scheduling and the generation of non-logical knowledge by machine teaming, can be processed in one scheduler. The computer simulation shows that comparing with MST(Minimum Slack Time), there is a little increment in tardness, 5% growth in flow time. And at breakdown, tardness is not increased by expert system comparing with EDD(Earliest Due Date).

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.823-835
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• 2019

Purpose: This study deals with a production planning and scheduling problem to minimize the total weighted tardiness on hybrid flow shop with sets of non-identical parallel machines on stages, where parallel machines in the set are dedicated to perform specific subsets of jobs and sequence-dependent setup times are also considered. Methods: A two-stage approach, that applies MILP model in the 1st stage and dispatching rules in the 2nd stage, is proposed in this paper. The MILP model is used to assign jobs to a specific machine in order to equalize the workload of the machines at each stage, while new dispatching rules are proposed and applied to sequence jobs in the queue at each stage. Results: The proposed two-stage approach was implemented by using a commercial MILP solver and a commercial simulation software and a case study was developed based on the spark plug manufacturing process, which is an automotive component, and verified using the company's actual production history. The computational experiment shows that it can reduce the tardiness when used in conjunction with the dispatching rule. Conclusion: This proposed two-stage approach can be used for HFS systems with dedicated machines, which can be evaluated in terms of tardiness and makespan. The method is expected to be used for the aggregated production planning or shop floor-level production scheduling.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.4
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• pp.415-424
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• 2002

Semiconductor manufacturing has been emerged as a highly competitive but profitable business. Accordingly it becomes very important for semiconductor manufacturing companies to meet customer demands at the right time, in order to keep the leading edge in the world market. However, due-date oriented production is very difficult task because of the complex job flows with highly resource conflicts in fabrication shop called FAB. Due to its cyclic manufacturing feature of products, to be completed, a semiconductor product is processed repeatedly as many times as the number of the product manufacturing cycles in FAB, and FAB processes of individual manufacturing cycles are composed with similar but not identical unit processes. In this paper, we propose a production scheduling and control scheme that is designed specifically for semiconductor scheduling environment (FAB). The proposed scheme consists of three modules: simulation module, cycle due-date estimation module, and dispatching module. The fundamental idea of the scheduler is to introduce the due-date for each cycle of job, with which the complex job flows in FAB can be controlled through a simple scheduling rule such as the minimum slack rule, such that the customer due-dates are maximally satisfied. Through detailed simulation, the performance of a cycle due-date based scheduler has been verified.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.3
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• pp.318-327
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• 2008

This paper considers a single-machine scheduling problem with availability constraints. In many realistic situations, machines may not be always available due to various reasons such as maintenance, breakdown and repair. However, most literature on scheduling assume that the machines are available at all times. This paper deals with a single-machine scheduling problem with periodic maintenance. If the maintenance decision is made jointly with the job scheduling, the system will be more effective. The objective is to minimize the total completion time of jobs. This problem is proved to be NP-hard in the strong sense. The proposed breaking heuristic(BH) algorithm rule is established by some theorems and conditions. Our computational results show that the BH algorithm is much more efficient than existing heuristic.