This book presents recently developed intelligent techniques with applications and theory in the area of quality management. The book consists of classical quality management topics dealing with intelligent techniques for solving the complex quality management problems.

Intelligent Decision Making Techniques in Quality Management: A Literature Review.- Intelligent Process Control Using Control Charts – I: Control Charts for Variables.- Intelligent Process Control Using Control Charts – II: Control Charts for Attributes.- Special Control Charts Using Intelligent Techniques: EWMA Control Charts.- Trends on Process Capability Indices in Fuzzy Environment.- An Integrated Framework to analyze the Performance of Process Industrial Systems Using a Fuzzy and Evolutionary Algorithm.- A Fuzzy Design of Single and Double Acceptance Sampling Plans.- Intelligent Decision Making Techniques in Quality Management: A Literature Review.- Multivariate Statistical and Computational Intelligence Techniques for Quality Monitoring of Production Systems.- Failure Mode and Effects Analysis under Uncertainty: A Literature Review and Tutorial.- QFD using Intelligent Techniques.- Process Improvement Using Intelligent Six Sigma.- Taguchi Method Using Intelligent Techniques.- Software Architecture Quality of Service Analysis Based on Optimization Models.- Key-Driver Analysis with Extended Back-Propagation Neural Network Based Importance-Performance Analysis (BPNN-IPA).

  This book presents recently developed intelligent techniques with applications and theory in the area of quality management. The involved applications of intelligence include techniques such as fuzzy sets, neural networks, genetic algorithms, etc. The book consists of classical quality management topics dealing with intelligent techniques for solving the complex quality management problems. The book will serve as an excellent reference for quality managers, researchers, lecturers and postgraduate students in this area. The authors of the chapters are well-known researchers in the area of quality management.  

Presents the theoretical and empirical framework for the use of intelligent decision making methods in the field of quality control and management broadly Introduces new intelligent solution approaches to the traditional problems in quality management Intelligent decision making methods such as heuristics, fuzzy logic, queuing theory, artificial neural networks are investigated for the solution of quality management and control techniques

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