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.
