A FNP Approach for Establishing the Optimal and Efficient Capacity Re-allocation Plans for Enhancing the Long-term Competitiveness of a Semiconductor Product

Abstract

Yield is undoubtedly the most critical factor to the competitiveness of a product in a semiconductor manufacturing factory. Therefore, evaluating the competitiveness of a product with its yield is a reasonable idea. For this purpose, Chen’s approach is extended in this study to evaluate the long-term competitiveness of a product based on its yield learning model from a new viewpoint – the trend in the mid-term competitiveness. Subsequently, to enhance the long-term competitiveness of a product, a fuzzy nonlinear programming (FNP) approach is proposed to optimize the effects of capacity re-allocation. A practical example is used to demonstrate the proposed methodology. Experimental results show that with an additional capacity of 8353 wafers per month, the long-term competitiveness of the product is maximized. Besides, the most efficient way is to allocate 6840 more wafers per month to the product. Further, considering the uncertainty in the long-term competitiveness with the fuzzy set approach is shown to be beneficial to the performance of the capacity re-allocation plan. These results are helpful in making capacity control decisions.