| dc.description.abstract | Equipment and machinery required in semiconductor manufacturing have always exposed semiconductor plants to potential hazards and risk. With a long history of fire accidents, the importance of automatic fire extinguishing equipment in semiconductor plants cannot be overstated. Therefore, regular maintenance and testing of automatic fire extinguishers can ensure normal function and, in the event of a real fire, swift elimination of the fire hazard. Under current working environments and practices, maintenance and testing of semiconductor equipment are contracted to outside vendors. The scale and state of this outsourcing is usually determined by prior experience and also by price quotations for the number of equipment to be serviced. Little attention is paid to the fact that working hours and difficulty in testing of the equipment are all relevant to overall cost. As a result, how decision-makers coordinate appropriate outsourcing operations for equipment maintenance while lowering cost is an important topic of discussion. This study attempts to investigate the assignment and dispatch of semiconductor equipment testing personnel. Another objective is to determine the minimum fiscal funds that should be paid to outside contractors, subject to certain limitations and conditions, for contract work. This may provide a reference for decision-makers making their outsourcing decisions. Furthermore, this paper seeks to conduct a trend analysis of sensitivity variables through a host of available parameters, so as to discover any unexpected result at the earliest possible time.
To verify the applicability and rationality of this model, this study uses a semiconductor plant in Hsinchu Science Park as a case study, and set parameters based on its operating conditions and basic information. By building a mathematical optimization model through integer programming, and utilizing Microsoft Excel 2010 to integrate data into LINGO software, computational results show optimized overall cost for outsourcing the testing of automatic fire extinguishing equipment to outside contractors. Furthermore, results from the optimized model can be contrasted and analyzed to the current model used by the plant, which is based on prior practical experience. Results show that the optimized model offers lower overall cost and higher efficiency as compared to the previous experience-based model. Therefore, we can conclude that the research model applied in this study can not only act as an important basis for reference, but can also be flexibly utilized to address the issue of outsourcing testing personnel for automatic fire extinguishing systems of semiconductor equipment.
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