Mismatch circuit aging modeling and simulations for robust product design and pre-/post-silicon verification

Author(s):  
Hyewon Shim ◽  
Yoohwan Kim ◽  
Jongwook Jeon ◽  
Yongsang Cho ◽  
Jongwoo Park ◽  
...  
Technometrics ◽  
1996 ◽  
Vol 38 (3) ◽  
pp. 286-287
Author(s):  
Henry W. Altland

Author(s):  
Masataka Yoshimura ◽  
Koichi Sasaki ◽  
Kazuhiro Izui ◽  
Shinji Nishiwaki

Product design optimizations usually require the optimization of not only all performance characteristics, but also the robustness of certain performance characteristics. Obtaining optimum design solutions is far from easy, since this requires evaluations of numerous related characteristics that usually have complicated and conflicting interrelationships. Some of these characteristics can include variations of one type or another, such as manufacturing process variations, variations pertaining to the environments where the product is used, variations in how long-term use affects certain product characteristics, and so on. The difficulty of obtaining optimum design solutions is thus compounded by the need to carry out specific optimizations that provide sufficient robustness to safely accommodate anticipated ranges of variations. This paper expands the hierarchical multiobjective optimization method based on simplification and decomposition of characteristics so that optimizations can be concurrently conducted for both performance characteristics and maximization of robustness against characteristic variances. A principal cause of variations in performance characteristics is variations in the contact conditions of joints, and the utility of the proposed robust product design optimization method is demonstrated by applying it to machine-tool models that include joints.


Author(s):  
Kevin Otto

Abstract Tuning variables represent factory floor manufacturing adjustments commonly used to correct variational noise errors in a product. Some examples are voltage supply adjustments, adjustable links and screws, or shims. This paper presents methods to determine the increased performance and robustness when using different possible manufacturing adjustments. All possible potential tuning adjustments that exist in a design are identified. Given this, the tuning variable model can be used to calculate the reduced product variation when using any of the potential tuning adjustments, including none at all. This process can be used to help select which product variables should be adjusted, based on the increased robustness to noise and the increased difficulty in manufacture. Doing so allows for more robust product performance at reduced manufacturing expense, by allowing the potential adjustment on many different possible variables. This is better than always adjusting the source of the manufacturing errors, which can be expensive.


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