• Journal of the Korean Society for Precision Engineering
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• v.29 no.4
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• pp.373-379
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• 2012

Disruptions in manufacturing systems caused by system changes and disturbances such as the tool wear, machine breakdown, malfunction of transporter, and so on, reduce the productivity and the increase of downtime and manufacturing cost. In order to cope with these challenges, a new method to build an intelligent manufacturing system with biological principles, namely an ant colony inspired manufacturing system, is presented. In the developed system, the manufacturing system is considered as a swarm of cognitive agents where work-pieces, machines and transporters are controlled by the corresponding cognitive agent. The system reacts to disturbances autonomously based on the algorithm of each autonomous entity or the cooperation with them. To develop the ant colony inspired manufacturing system, the disturbances happened in the machining shop of a transmission case were analyzed to classify them and to find out the corresponding management methods. The system architecture with the autonomous characteristics was generated with the cognitive agent and the ant colony technology. A test bed was implemented to prove the functionality of the developed system.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.2
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• pp.77-95
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• 2004

This paper deals with the process planning of flexible manufacturing systems (FMS) with various flexibilities and multiple objectives. The consideration of the manufacturing flexibility is crucial for the efficient utilization of FMS. The machine, tool, sequence, and process flexibilities are considered In this research. The flexibilities cause to increase the Problem complexity. To solve the process planning problem, an this paper an evolutionary algorithm is used as a methodology. The algorithm is named multiobjective competitive evolutionary algorithm (MOCEA), which is developed in this research. The feature of MOCEA is the incorporation of competitive coevolution in the existing multiobjective evolutionary algorithm. In MOCEA competitive coevolution plays a role to encourage population diversity. This results in the improvement of solution quality and, that is, leads to find diverse and good solutions. Good solutions means near or true Pareto optimal solutions. To verify the Performance of MOCEA, the extensive experiments are performed with various test-bed problems that have distinct levels of variations in the four kinds of flexibilities. The experiments reveal that MOCEA is a promising approach to the multiobjective process planning of FMS.

• Composites Research
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• v.19 no.2
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• pp.13-19
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• 2006

In this paper, parametric study was carried out to design sandwich structures for EDM machines controlling stacking sequence, stacking thickness of composites and rib configuration. Sandwich structures which are dealt with in this paper are composed of fibre reinforced composite for skin material and foam or resin concrete for core materials. The sandwich column has cruciform rib to enhance bending stiffness of the structure and the bed has several vertical ribs to resist the normal forces and vibration. The design parameters such as rib thickness and stacking sequence were controlled to enhance the system robustness. Finite element analysis was also carried out to verify the variation of static and dynamic stiffness of the structures according to the variation of the parameters. Vibration tests were performed to verify the natural frequencies and damping ratios of the manufactured composite structures. The appropriate shape and configuration conditions for micro-EDM machine structures are proposed.