• Journal of Institute of Control, Robotics and Systems
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• v.8 no.4
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• pp.292-298
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• 2002

We focus on the slicing off some sub-nets using the transitive matrix. Control flows in the Petri nets is done based on the token flows. One control f]ow explains the independent tokens status and if the token-in divides into several tokens after firing a transition then the control flow divides to several flows, as well. Accordingly, we define that the basic unit of concur-rency (short BUC) is a set of the executed control flows based on the behavioral properties in the net. The BUC is S-invariant which has one control flow. We show the usefulness of transitive matrix to slice off some subnets from the original net based on BUC-through on an example.

• Journal of the Korea Institute of Military Science and Technology
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• v.2 no.2
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• pp.83-91
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• 1999

Dynamic characteristic of manufacturing stage is understood and the utilization of each machine is maximized by developing on-line dynamic CAPP system to consider the overloads in the aircraft part manufacturing line. In this paper, a scheme of production planning and scheduling system was proposed through inspection about some predeveloped CAPP system. Developed production planning and scheduling system included process planning module. After precise inspection of some FMS line schema at domestic heavy industry, optimized FMS line was applied to aircraft part manufacturing and repairing factory. By virtue of considering overloads of factory and machine through on-line dynamic CAPP system, the utilization of resources is maximized and manufacturing lead time is minimized.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.132.3-132
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• 2001

In this paper, we focus on the analysis of the scheduling problem in FMS after slicing off some sub-nets using the transitive matrix. This class of Time Petri nets is obtained by merging subnets based on the machine's operations. We can divide original system into some subnets based on machine's operations using Time Petri nets slice and analyze the feasibility time in each schedules. In this paper, we show the usefulness of transitive matrix to slice off some subnets from the original net, and explain on an example.

• 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 of Industrial and Systems Engineering
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• v.21 no.47
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• pp.35-45
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• 1998

Scheduling problem in Flexible Manufacturing Systems(FMS) is complex because of various situation of Manufacturing Systems. Especially, in case of short-term scheduling demanding high efficiency, low cost at short-period, efficient scheduling is a serious problem. To solve this problem, many dispatching rules are developed. But, it leave much to be desired, because real situation in shop floor is complex and real-time scheduling is needed in real manufacturing shop floor. In this paper, search algorithm that allocate different dispatching rules to each machine is presented to complement lack of dispatching rule and develop practical real-time scheduling system. The search algorithm is described in detail. First, algorithm detect machine breakdown, evaluate each dispatching rule. dispatching rules for each machine meeting performance criteria are ranked. The algorithm selects new dispatching nile for bottleneck machine. The effectivenes and efficiency of the mixed dispatching rule and search algorithm is demonstrated.

• Industrial Engineering and Management Systems
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• v.11 no.4
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• pp.310-330
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• 2012

Scheduling is an important tool for a manufacturing system, where it can have a major impact on the productivity of a production process. In manufacturing systems, the purpose of scheduling is to minimize the production time and costs, by assigning a production facility when to make, with which staff, and on which equipment. Production scheduling aims to maximize the efficiency of the operation and reduce the costs. In order to find an optimal solution to manufacturing scheduling problems, it attempts to solve complex combinatorial optimization problems. Unfortunately, most of them fall into the class of NP-hard combinatorial problems. Genetic algorithm (GA) is one of the generic population-based metaheuristic optimization algorithms and the best one for finding a satisfactory solution in an acceptable time for the NP-hard scheduling problems. GA is the most popular type of evolutionary algorithm. In this survey paper, we address firstly multiobjective hybrid GA combined with adaptive fuzzy logic controller which gives fitness assignment mechanism and performance measures for solving multiple objective optimization problems, and four crucial issues in the manufacturing scheduling including a mathematical model, GA-based solution method and case study in flexible job-shop scheduling problem (fJSP), automatic guided vehicle (AGV) dispatching models in flexible manufacturing system (FMS) combined with priority-based GA, recent advanced planning and scheduling (APS) models and integrated systems for manufacturing.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1991.10a
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• pp.77-89
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• 1991

One of the important problems concerning the efficient operation of an automated manufacturing system is the flow control problem. Most research papers about scheduling and control of a FMS consider fabrication, machining and assembly independently. In this paper an effective flow control strategy for a FMS with an assembly subsystem which may be called FMAS (Flexible Machining and Assembly System) is designed using the operation-oriented and, combined Push and Pull control method. The flow control system to be described here could meet production demands with a minimum makespan while satisfying assigned due-dates and keeping a low volume of work-in-process at the same time. The control mechanism also considers machine failures and rush jobs.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.61-61
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• 2000

Since FMS(Flexible Manufacturing System) such as semiconductor production systems have the characteristic that each device has to be commonly used in several stages, it is difficult to find an optimal solution. In this paper, we proposed the new algorithm which can get the optimal ratio of sharing resources. We will implement the proposed algorithm to semiconductor production systems. We introduce the optimal algorithm, which is modeled and analyzed by ExSpect, a petri net based simulation tool. When there exist conflicts of sharing resources, the scheduling method is adopted, which gives a priority to the most preceded process. The suggested algorithm can be used not only in semiconductor production systems but also in various FMS.

• Journal of the Korean Society for Precision Engineering
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• v.9 no.4
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• pp.36-43
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• 1992

This paper presents a hierarchical real-time operation control and monitoring scheme of the FMS/CIM center which has been implemented at the Automation and Systems Research Institute of Seoul National University. The hierarchical structure of the whole scheme consists of three lavers. The upper layer is in charge of on-line scheduling, computer network control, shop-floor monitoring and command generation for AGV dispatching, machining, assembly, inspection, set-up, etc. The middle layer has six modules, which are installed in the FMS host computer with the upper layer and run on the multi-tasking basis. Each module is connected to one of six cell controllers distributed in the FMS model plant and transfers operation command down to each cell controller through the Ethernet/TCP-IP local area network. The lower layer is comprised of six cell control software modules for machining cell, assembly cell, inspection cell, set-up stations. AS/RS and AGV. Each cell controller reports the status of the manufacturing facilites to the middle layer as well as ecxecuting the appropriate sequence control of the manufacturing processes.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.187-190
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• 2003

Many manufacturing companies consider the integrated and concurrent scheduling because they need the global optimization technology that could manufacture various products more responsive to customer needs. In this paper, we propose an advanced scheduling model to generate the schedules considering resource constraints and precedence constraints in make-to-order (MTO) manufacturing environments. Precedence of work- in-process(WIP) and resources constraints have recently emerged as one of the main constraints in advanced scheduling problems. The advanced scheduling problems is formulated as a multiobjective mathematical model for generating operation schedules which are obeyed resources constraints, alternative workstations of operations and the precedence constraints of WIP in MTO manufacturing. For effectively solving the advanced scheduling problem, the multi-objective hybrid genetic algorithm (m-hGA) is proposed in this paper. The m-hGA is to minimize the makespan, total flow time of order, and maximum tardiness for each order, simultaneously. The m-hGA approach with local search-based mutation through swap mutation is developed to solve the advanced scheduling problem. Numerical example is tested and presented for advanced scheduling problems with various orders to describe the performance of the proposed m-hGA.