2014•Modelling and Simulation in EngineeringOpen access

A Simulation Model for Machine Efficiency Improvement Using Reliability Centered Maintenance: Case Study of Semiconductor Factory

Srisawat Supsomboon, Kanthapong Hongthanapach

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Abstract

The purpose of this study was to increase the quality of product by focusing on the machine efficiency improvement. The principle of the reliability centered maintenance (RCM) was applied to increase the machine reliability. The objective was to create preventive maintenance plan under reliability centered maintenance method and to reduce defects. The study target was set to reduce the Lead PPM for a test machine by simulating the proposed preventive maintenance plan. The simulation optimization approach based on evolutionary algorithms was employed for the preventive maintenance technique selection process to select the PM interval that gave the best total cost and Lead PPM values. The research methodology includes procedures such as following the priority of critical components in test machine, analyzing the damage and risk level by using Failure Mode and Effects Analysis (FMEA), calculating the suitable replacement period through reliability estimation, and optimizing the preventive maintenance plan. From the result of the study it is shown that the Lead PPM of test machine can be reduced. The cost of preventive maintenance, cost of good product, and cost of lost product were decreased.

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The purpose of this study was to increase the quality of product by focusing on the machine efficiency improvement. The principle of the reliability centered maintenance (RCM) was applied to increase the machine reliability. The objective was to create preventive maintenance plan under reliability centered maintenance method and to reduce defects. The study target was set to reduce the Lead PPM for a test machine by simulating the proposed preventive maintenance plan. The simulation optimization approach based on evolutionary algorithms was employed for the preventive maintenance technique selection process to select the PM interval that gave the best total cost and Lead PPM values. The research methodology includes procedures such as following the priority of critical components in test machine, analyzing the damage and risk level by using Failure Mode and Effects Analysis (FMEA), calculating the suitable replacement period through reliability estimation, and optimizing the preventive maintenance plan. From the result of the study it is shown that the Lead PPM of test machine can be reduced. The cost of preventive maintenance, cost of good product, and cost of lost product were decreased.

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Available abstract

The purpose of this study was to increase the quality of product by focusing on the machine efficiency improvement. The principle of the reliability centered maintenance (RCM) was applied to increase the machine reliability. The objective was to create preventive maintenance plan under reliability centered maintenance method and to reduce defects. The study target was set to reduce the Lead PPM for a test machine by simulating the proposed preventive maintenance plan. The simulation optimization approach based on evolutionary algorithms was employed for the preventive maintenance technique selection process to select the PM interval that gave the best total cost and Lead PPM values. The research methodology includes procedures such as following the priority of critical components in test machine, analyzing the damage and risk level by using Failure Mode and Effects Analysis (FMEA), calculating the suitable replacement period through reliability estimation, and optimizing the preventive maintenance plan. From the result of the study it is shown that the Lead PPM of test machine can be reduced. The cost of preventive maintenance, cost of good product, and cost of lost product were decreased.

Key concepts: Preventive maintenance, Reliability engineering, Reliability (semiconductor), Predictive maintenance, Factory (object-oriented programming), Test plan, Failure mode and effects analysis, Engineering

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