Get Advanced Modeling and Optimization of Manufacturing PDF

By R. Venkata Rao

ISBN-10: 0857290142

ISBN-13: 9780857290144

ISBN-10: 0857290150

ISBN-13: 9780857290151

Advanced Modeling and Optimization of producing Processes provides a finished assessment of the most recent overseas learn and improvement tendencies within the modeling and optimization of producing approaches, with a spotlight on machining. It makes use of examples of varied production techniques to illustrate complicated modeling and optimization innovations. either simple and complex strategies are awarded for varied production strategies, mathematical versions, conventional and non-traditional optimization concepts, and genuine case experiences. the result of the applying of the proposed equipment also are lined and the e-book highlights the main helpful modeling and optimization techniques for attaining top approach functionality. as well as overlaying the complex modeling, optimization and environmental elements of machining tactics, Advanced Modeling and Optimization of producing Processes additionally covers the newest technological advances, together with fast prototyping and tooling, micromachining, and nano-finishing. Advanced Modeling and Optimization of producing Processes is written for designers and production engineers who're chargeable for the technical points of product cognizance, because it provides new types and optimization recommendations to make their paintings more uncomplicated, extra effective, and more advantageous. it's also an invaluable textual content for practitioners, researchers, and complicated scholars in mechanical, business, and production engineering.

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ACO was developed by Dorigo et al. [58] based on the fact that ants are able to find the shortest route between their nest and a source of food. This is done using pheromone trails which ants deposit whenever they travel as a form of indirect communication. When ants leave their nest to search for a food source, they randomly rotate around an obstacle, and initially the pheromone deposits will be the same for the right and left directions. When the ants in the shorter direction find a food source, they carry the food and start returning back, following their pheromone trails, and still depositing more pheromone.

Hence the quadratic programming problem can be solved by suitably modifying the linear programming technique. Sequential quadratic programming method developed by Schittkowski [45] is widely used method in manufacturing optimization as this optimization method has been considered to be an excellent approach for handling constrained optimization problems. 28 1 Overview The basic concept of sequential quadratic programming is quite simple. The approximation function, instead of the original non-linear function, is used for optimization.

4 Particle Swarm Optimization Particle swarm optimization (PSO) is an evolutionary computation technique developed by Kennedy and Eberhart [54]. It exhibits common evolutionary computation attributes as given below: • It is initialized with a population of random solutions, • It searches for optima by updating generations, and • Potential solutions, called particles, are then ‘‘flown’’ through the problem space by following the current optimum particles. The particle swarm concept was originated as a simulation of a simplified social system.

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Advanced Modeling and Optimization of Manufacturing Processes: International Research and Development by R. Venkata Rao


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