Intelligent quality systems / Duc Truong Pham and Ercan Oztemel
- 作者： Pham, D. T
- 其他作者：
- 其他題名：
- Advanced manufacturing series (Springer-Verlag)
- Advanced manufacturing
- 出版： London ;New York : Springer c1996
- 叢書名： Advanced manufacturing
- 主題： Intelligent control systems , Quality control
- ISBN： 3540760458 (Berlin : hardback : acid-free paper) :: NT$2527
- 書目註：Includes bibliographical references and indexes
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讀者標籤：
- 系統號： 005079052 | 機讀編目格式
館藏資訊
Although the tenn quality does not have a precise and universally accepted definition, its meaning is generally well understood: quality is what makes the difference between success and failure in a competitive world. Given the importance of quality, there is a need for effective quality systems to ensure that the highest quality is achieved within given constraints on human, material or financial resources. This book discusses Intelligent Quality Systems, that is quality systems employing techniques from the field of Artificial Intelligence (AI). The book focuses on two popular AI techniques, expert or knowledge-based systems and neural networks. Expert systems encapsulate human expertise for solving difficult problems. Neural networks have the ability to learn problem solving from examples. The aim of the book is to illustrate applications of these techniques to the design and operation of effective quality systems. The book comprises 8 chapters. Chapter 1 provides an introduction to quality control and a general discussion of possible AI-based quality systems. Chapter 2 gives technical information on the key AI techniques of expert systems and neural networks. The use of these techniques, singly and in a combined hybrid fonn, to realise intelligent Statistical Process Control (SPC) systems for quality improvement is the subject of Chapters 3-5. Chapter 6 covers experimental design and the Taguchi method which is an effective technique for designing quality into a product or process. The application of expert systems and neural networks to facilitate experimental design is described in this chapter.