Please use this identifier to cite or link to this item: http://localhost:8081/xmlui/handle/123456789/11343
Title: PROCESS PARAMETERS OPTIMISATION OF ULTRASONIC MACHINING AND ITS EXPERIMENTAL VERIFICATION
Authors: NinAniy, Devnder
Keywords: MECHANICAL INDUSTRIAL ENGINEERING;PROCESS PARAMETERS OPTIMISATION;ULTRASONIC MACHINING;MATERIAL REMOVAL RATE
Issue Date: 2006
Abstract: Ultrasonic Machining (USM), as a non-conventional machining technique, has been providing necessary assistance in the machining of hard and brittle materials, whether electrically conducting or non-conducting. Though the material removal rate of the process is less, USM is superior to most other non-conventional machining techniques. This is because the process is independent of thermal or electrical properties of workpiece and does not thermally damage or introduce residual stresses in the workpiece. The objective of the present work was to optimize the process parameters like grain size, slurry concentration, power rating [frequency of vibration, amplitude of vibration being constant as per the allowable machine settings] for obtaining maximum Material Removal Rate using Genetic Algorithms. Genetic algorithms are search algorithms based on the mechanics of natural selection and natural genetics. They combine survival of the fittest among string structures with a structured yet randomized information exchange to form a search algorithm. The results have been given in the tabular form for various combinations of parameters like No. of Generations, Population Size, Crossover Probability and Mutation Probability. The Taguchi Method was used to plan the experiments and subsequent analysis. Experiments for process parameters on the quality of the hole drilled in ceramic tiles as workpiece by Ultrasonic Drilling. The parameters taken for this investigation were • Size of Abrasive Grains • Concentration of Abrasive Slurry • Power Rating of Machine • Thickness of work Material. The results of experiments and analytical results [from Genetic Algorithm] have been compared.
URI: http://hdl.handle.net/123456789/11343
Other Identifiers: M.Tech
Research Supervisor/ Guide: Jain, N. K.
metadata.dc.type: M.Tech Dessertation
Appears in Collections:MASTERS' THESES (MIED)

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