Evaluating and 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 through yield learning modeling in various ways. Subsequently, to enhance the long-term competitiveness of the product, capacity re-allocation is shown to be helpful. The effects are modeled. Finally, a fuzzy nonlinear programming (FNP) model is constructed to optimize the performance. A practical example is used to demonstrate the proposed methodology. © 2009 Springer Berlin Heidelberg.