Książki

This book sheds light on the development of traditional and advanced optimization methods. Their use in various tradition and non-tradition manufacturing and machining processes for an improved manufacturability is reported. This includes key elements of implementing conventional statistical methods, multi-objective and multi-criteria decision-making methods and evolution of single and multi-target optimization techniques using soft computing to enhance production performance, efficiency and sustainability in manufacturing. The latest research in this area as well as possible avenues of future research are also highlighted.

Intelligent Manufacturing

Part I Optimization using traditional techniques (4 Chapters)

 

Use of traditional design of experiments techniques such as full factorial design, Taguchi, response surface methodology and mixed model design to optimize the various traditional and non-traditional manufacturing and machining processes.

Part II Multi-criteria decision making through soft computing and evolutionary techniques (4 Chapters)

This part of the book will cover multiobjective optimizations using soft computing techniques such as artificial neural network (ANN) and fuzzy logic, artificial intelligence (AI) based genetic algorithms (GA), PSO (Particle swarm optimization), GRA (Grey relational analyses), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and Hybrid methods.