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.

This book highlights the need for studying multi-state models analytically for understanding the physics of molecular processes. An intuitive picture about recently solved models of statistical and quantum mechanics is drawn along with presenting the methods developed to solve them. The models are relevant in the context of molecular processes taking place in gaseous phases and condensed phases, emphasized in the introduction. Chapter 1 derives the arisal of multi-state models for molecular processes from the full Hamiltonian description. The model equations are introduced and the literature review presented in short. In Chapter 2, the time-domain methods to solve Smoluchowski-based reaction-diffusion systems with single-state and two-state descriptions are discussed. Their corresponding analytical results derive new equilibrium concepts in reversible reactions and studies the effect of system and molecular parameters in condensed-phase chemical dynamics. In Chapter 3, time-domain methods to solve quantum scattering problems are developed. Along side introducing a brand new solvable model in quantum scattering, it discusses transient features of quantum two-state models. In interest with electronic transitions, a new solvable two-state model with localized non-adiabatic coupling is also presented. The book concludes by proposing the future scope of the model, thereby inviting new research in this fundamentally important and rich applicable field.