id: 05570913
dt: a
an: 05570913
au: Lin, Yu-Cheng; Chen, Toly; Li, Kun-Tai
ti: Evaluating and enhancing the long-term competitiveness of a semiconductor
    product.
so: Chien, Been-Chian (ed.) et al., Next-generation applied intelligence. 22nd
    international conference on industrial, engineering and other
    applications of applied intelligent systems, IEA/AIE 2009, Tainan,
    Taiwan, June 24‒27, 2009. Proceedings. Berlin: Springer (ISBN
    978-3-642-02567-9/pbk). Lecture Notes in Computer Science 5579. Lecture
    Notes in Artificial Intelligence, 242-251 (2009).
py: 2009
pu: Berlin: Springer
la: EN
cc: 
ut: 
ci: 
li: doi:10.1007/978-3-642-02568-6_25
ab: Summary: 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.
rv: