Abstract
Testing tools used by semiconductor foundries are very expensive, the cost in each ranges from tens of millions to hundreds of millions. Optimal use of the equipment for the test industry will be a very important topic. When testing tools used for testing in semiconductor foundries crash, or when preventive maintenance and parts replacements are required, the maintenance cost redundant, lowering of the machine usage rates, reduced lifespan, and losses due to product defects may occur as a result. This may further delay shipment of the product to the customer and have productive effects on the business reputation.There has not been much in-depth discussion of preventive maintenance in Ic Testing house, especially the performance of Time Based Maintenance (TBM) and Condition Based Maintenance (CBM) strategies on the production and maintenance systems. The difference between TBM and CBM strategies causes different maintenance times, resulting in different product manufacturing overall cycle times; further affecting the product production lifecycles and order fulfillment rates. Also, TBM and CBM methods, order in which machine tools are maintained, human resource distribution, and other maintenance strategy issues are not investigated during integrated product manufacturing and maintenance for effects in system performance; it is also a topic not fully investigated.Therefore, this research evaluated the TBM and CBM methods, maintenance work displacement, and assignment of maintenance personnel. With these three factors, a semiconductor foundry production and maintenance effectiveness performance system is established to enable strengthening of a company’s production and maintenance goals while increasing the competitiveness of the business. For example, based on the average usage rates by maintenance personnel, the company should select the fourth strategic combination (grey system, SMT, fully rounded personnel) with 68.56% as the must optimal selection.This research applies the system simulation method to learn that the standard human resource for machine tools should be 6 personnel, 2 personnel less than the 8 personnel used by the company used by this case study. So by apply this case study method, 2 personnel can be reduced, resulting in a savings of 1.008 million dollars (36 thousand * 14 (months) * 2 personnel = 1.008 million dollars).