Capacity Planning For Sort Unit Of Semiconductor Fabrication

The semiconductor industry is getting more and more mature. Instead of only focusingon the product R&D and manufacturing technology upgrade, the industry has recognized theimportance of shortening the cycle time from product design, Customization and diversity,and how to rapidly respond to the market requirement. The manufacturing capacity planningis accordingly one of the key factors to achieve that goal.The capacity planning is one of the most important and challenging areas in thesemiconductor fabrication operations because of the complicated manufacturing process andthe dynamic operation environment. Work-in-product (WIP) profile is changing all the timebecause of the constraint of the equipment capacity are dynamically shifted based on toolstatus. An appropriate capacity planning will bring the right tools to the production line in theright time and million dollars saving as the consequence. It will also enable the cost reductionby reducing the consumption of the chemical/parts and enhance the productivity byoptimizing the resource such as tool set and manpower. Eventually it will help the companyto meet the customer’s satisfaction.This article will focus on the methodology of capacity planning for a SORT unit in thesemiconductor manufacturing factory. We setup a static capacity model considering theprocess flow and the equipment unit capacity. By optimizing the equipment maintenancecycle, improving the transfer speed of the sort prober, the equipment productivity is increasedby9%; we also maximize the overlap time between each individual operation to enhance theequipment utilization; We comprehensively consider the factor of quality, technologydevelopment, equipment capability and capacity, make the appropriate arrangement forequipment maintenance and engineering experiments. By doing all the improvement above,the sort equipment capacity was significantly increased from159.4wafers per week to228.2wafers per week, the improvement rate is43.1%during the factory full load period.Based upon the discrete type of system simulation technique, we programmed a dynamic WIP Forecast System (WFS). This system is to real-time simulating the WIP profile byconsidering the equipment current status. The factory used to take front-end wafer startvolume as the only input to calculate the Sort incoming WIP,(so called static Short-TermCapacity Model, STCM). WPS is more advanced in terms of the accuracy of the WIP forecast.The vibration can be easily controlled within15%. The dynamic system enables the pre-activecapacity optimization actions in order to maximize the output.The principles and methodology discussed in this dissertation have provided strongtheoretic support and practical examples. Certain enterprises have initiated implementationon these fundamentals, and started investment on the R&D of more advanced supply chainmanagement.