Process Optimization A Statistical Approach [Paperback]

This book covers several bases at once. It is useful as a textbook for a second course in experimental optimization techniques for industrial production processes. In addition, it is a superb reference volume for use by professors and graduate students in Industrial Engineering and Statistics departments. It will also be of huge interest to applied statisticians, process engineers, and quality engineers working in the electronics and biotech manufacturing industries. In all, it provides an in-depth presentation of the statistical issues that arise in optimization problems, including confidence regions on the optimal settings of a process, stopping rules in experimental optimization, and more.

This is an ideal textbook for students of experimental optimization techniques used in industrial production processes. It presents a detailed treatment of Bayesian Optimization approaches and it contains a mix of technical and practical sections.

PROCESS OPTIMIZATION: A Statistical Approach is a textbook for a course in experimental optimization techniques for industrial production processes and other noisy systems where the main emphasis is process optimization. The book can also be used as a reference text by Industrial, Quality and Process Engineers and Applied Statisticians working in industry, in particular, in semiconductor/electronics manufacturing and in biotech manufacturing industries.

The major features of PROCESS OPTIMIZATION: A Statistical Approach are:

• It provides a complete exposition of mainstream experimental design techniques, including designs for first and second order models, response surface and optimal designs;
• Discusses mainstream response surface method in detail, including unconstrained and constrained (i.e., ridge analysis and dual and multiple response) approlãD