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 non-linear programming 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 16 780 wafers per month, the long-term competitiveness of the product is maximized. Also, the most efficient way is to allocate 14 500 more wafers per month to the product. These results are helpful in making capacity re-allocation decisions.
|Number of pages||9|
|Journal||Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture|
|State||Published - 1 Aug 2010|
- capacity re-allocation
- non-linear programming