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Computer-Aided.Design.Engineering.and.Manufacturing P7

Tham khảo tài liệu 'computer-aided.design.engineering.and.manufacturing p7', kỹ thuật - công nghệ, tự động hoá phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | Chinnam Ratna Babu Intelligent Quality Controllers for On-Line Parameter Design Computational Intelligence in Manufacturing Handbook Edited by Jun Wang et al Boca Raton CRC Press LLC 2001 17 Intelligent Quality Controllers for On-Line Parameter Design Ratna Babu Chinnam Wayne State University 17.1 Introduction 17.2 An Overview of Certain Emerging Technologies Relevant to On-Line Parameter Design 17.3 Design of Quality Controllers for On-Line Parameter Design 17.4 Case Study Plasma Etching Process Modeling and On-Line Parameter Design 17.5 Conclusion 17.1 Introduction Besides aggressively innovating and incorporating new materials and technologies into practical effective and timely commercial products in recent years many industries have begun to examine new directions that they must cultivate to improve their competitive position in the long term. One thing that has become clearly evident is the need to push the quality issue farther and farther upstream so that it becomes an integral part of every aspect of the product process life cycle. In particular many have begun to recognize that it is through engineering design that we have the greatest opportunity to influence the ultimate delivery of products and processes that far exceed the customer needs and expectations. For the last two decades classical experimental design techniques have been widely used for setting critical product process parameters or targets during design. But recently their potential is being questioned for they tend to focus primarily on the mean response characteristics. One particular design approach that has gained a lot of attention in the last decade is the robust parameter design approach that borrows heavily from the principles promoted by Genichi Taguchi 1986 1987 . Taguchi views the design process as evolving in three distinct phases 1. System Design Phase Involves application of specialized field knowledge to develop basic design alternatives. 2. Parameter Design Phase Involves .