Manufacturing optimization through intelligent techniques

著者

    • Saravana, Rajendran

書誌事項

Manufacturing optimization through intelligent techniques

R. Saravana

(Manufacturing engineering and materials processing, 70)(A CRC Press book)

CRC, Taylor & Francis, 2006

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注記

Includes bibliographical references and index

内容説明・目次

内容説明

Effective utilization of equipment is critical to any manufacturing operation, especially with today's sophisticated, high-cost equipment and increased global competition. To meet these challenges in the manufacturing industry, you must understand and implement the myriad conventional and intelligent techniques for different types of manufacturing problems. Manufacturing Optimization Through Intelligent Techniques covers design of machine elements, integrated product development, machining tolerance allocation, selection of operating parameters for CNC machine tools, scheduling, part family formation, selection of robot coordinates, robot trajectory planning and both conventional and intelligent techniques, providing the tools to design and implement a suitable optimization technique. The author explores how to model optimization problems, select suitable techniques, develop the optimization algorithm and software, and implement the program. The book delineates five new techniques using examples taken from the literature for optimization problems in design, tolerance allocation; selection of machining parameters, integrated product development, scheduling, concurrent formation of machine groups and part families, selection of robot co-ordinates, robot trajectory planning and intelligent machining. All the manufacturing functions described have been successfully solved by Genetic Algorithm. Other intelligent techniques have been implemented only for solving certain types of problems: simulated annealing; design and scheduling, particle swarm optimization and ant colony optimization; tolerance allocation and tabu search; as well as machining parameters optimization. After reading this book, you will understand the different types of manufacturing optimization problems as well as the conventional and intelligent techniques suitable for solving them. You will also be able to develop and implement effective optimization procedures and algorithms for a wide variety of problems in design manufacturing.

目次

MANUFACTURING OPTIMIZATION THROUGH INTELLIEGENT TECHNIQUES CONVENTIONAL OPTIMIZATION TECHNIQUES FOR MANUFACTURING APPLICATIONS Brief Overview of Traditional Optimization Single Variable Techniques Suitable for Solving Various Manufacturing Optimization Problems (Direct Search Method) Multivariable Techniques Suitable for Solving Various Manufacturing Optimization Problems (Direct Search Methods) Dynamic Programming Technique INTELLIGENT OPTIMIZATION TECHNIQUES FOR MANUFACTURING OPTIMIZATION PROBLEMS Genetic Algorithm (GA) Simulated Annealing (SA) Ant Colony Optimization (ACO) Particle Swarm Optimization (PSO) Tabu Search (TS) OPTIMAL DESIGN OF MECHANICAL ELEMENTS Introduction Gear Design Optimization Design Optimization of Three-Bar Structure Spring Design Optimization Design Optimization of Single-Point Cutting Tool OPTIMIZATION OF MACHINING TOLERANCE ALLOCATION Dimensions and Tolerances Tolerance Allocation of Welded Assembly Tolerance Design of Over Running Clutch Assembly Tolerance Design Optimization of Stepped Clone Pulley Tolerance Design Optimization of Stepped-Block Assembly OPTIMIZATION OF OPERATING PARAMETERS FOR CNC MACHINE TOOLS Optimization of Turning Process Optimization of Multi-Pass Turning Process Optimization of Face Milling Process Surface Grinding Process Optimization Optimization of Machining Parameters for Multi-Tool Milling Operations Using Tabu Search INTEGRATED PRODUCT DEVELOPMENT AND OPTIMIZATION Introduction Integrated Product Development Total Product Optimization - Design for Life Cycle Cost (DLCC) Case Illustration Proposed Methodology GA Illustrated Conclusion SCHEDULING OPTIMIZATION Classification of Scheduling Problems Scheduling Algorithms Parallel Machine Scheduling Using Genetic Algorithms Implementation of Simulated Annealing Algorithm MODERN MANUFACTURING APPLICATIONS Implementation of Genetic Algorithm for Grouping of Part Families and Matching Cell Selection of Robot Coordinate Systems Using Genetic Algorithm Trajectory Planning for Robot Manipulators Using Genetic Algorithm Application of Intelligent Techniques for Adaptive Control Optimization CONCLUSIONS & FUTURE SCOPE Index

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