Focusing on the importance of the application of statistical techniques, this book covers the design of experiments and stochastic modeling in textile engineering. Textile Engineering: Statistical Techniques, Design of Experiments and Stochastic Modeling focuses on the analysis and interpretation of textile data for improving the quality of textile processes and products using various statistical techniques. FEATURES Explores probability, random variables, probability distribution, estimation, significance test, ANOVA, acceptance sampling, control chart, regression and correlation, design of experiments and stochastic modeling pertaining to textiles Presents step-by-step mathematical derivations Includes MATLAB (R) codes for solving various numerical problems Consists of case studies, practical examples and homework problems in each chapter This book is aimed at graduate students, researchers and professionals in textile engineering, textile clothing, textile management and industrial engineering. This book is equally useful for learners and practitioners in other scientific and technological domains.

Optimization and decision making are integral parts of any manufacturing process and management system. The objective of this book is to demonstrate the confluence of theory and applications of various types of multi-criteria decision making and optimization techniques with reference to textile manufacturing and management. Divided into twelve chapters, it discusses various multi-criteria decision-making methods such as AHP, TOPSIS, ELECTRE, and optimization techniques like linear programming, fuzzy linear programming, quadratic programming, in textile domain. Multi-objective optimization problems have been dealt with two approaches, namely desirability function and evolutionary algorithm. Key Features Exclusive title covering textiles and soft computing fields including optimization and decision making Discusses concepts of traditional and non-traditional optimization methods with textile examples Explores pertinent single-objective and multi-objective optimizations Provides MATLAB coding in the Appendix to solve various types of multi-criteria decision making and optimization problems Includes examples and case studies related to textile engineering and management

Optimization and decision making are integral parts of any manufacturing process and management system. The objective of this book is to demonstrate the confluence of theory and applications of various types of multi-criteria decision making and optimization techniques with reference to textile manufacturing and management. Divided into twelve chapters, it discusses various multi-criteria decision-making methods such as AHP, TOPSIS, ELECTRE, and optimization techniques like linear programming, fuzzy linear programming, quadratic programming, in textile domain. Multi-objective optimization problems have been dealt with two approaches, namely desirability function and evolutionary algorithm. Key Features Exclusive title covering textiles and soft computing fields including optimization and decision making Discusses concepts of traditional and non-traditional optimization methods with textile examples Explores pertinent single-objective and multi-objective optimizations Provides MATLAB coding in the Appendix to solve various types of multi-criteria decision making and optimization problems Includes examples and case studies related to textile engineering and management

Artificial Intelligence in Textile Engineering explains Artificial Intelligence techniques from first principles in the perfect way for textiles materials scientists and engineers. Advances in Artificial Intelligence technology have made a substantial impact across the textiles supply chain, making products more efficient, flexible and reliable. In this book techniques such as artificial neural network, support vector machine, fuzzy logic, rough set, evolutionary algorithm, and hybrid intelligence systems are described with application to textiles. Readers are supported throughout with step by step mathematical derivations of AI techniques, case studies, as well as MATLAB codes, giving readers from different backgrounds the perfect entry to AI solutions.