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https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/6657
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DC Field | Value | Language |
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dc.contributor.author | S. Deva Prasad | - |
dc.contributor.author | K. Chandra Shekar | - |
dc.date.accessioned | 2024-02-27T05:59:11Z | - |
dc.date.available | 2024-02-27T05:59:11Z | - |
dc.date.issued | 2020 | - |
dc.identifier.uri | http://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/6657 | - |
dc.description.abstract | Productivity and quality in production/manufacturing have great concerns in competitive global market manufacturing units mainly focuses on these in relation to the process and product developed subsequently. Electrical Discharge Machining process, even now it is an experience process, wherein still the selected parameters are often far from the maximum, and at the same time selecting optimization parameters is costly and time-consuming affair. Material Removal Rate during the process has been considered in this work as a productivity estimate with the objective to maximize it, also have better surface roughness, taken as important output parameter, in the process. These two opposite objectives have been simultaneously satisfied by selecting an optimal process environment, optimal parameter setting. In this work, objective function is obtained using Regression Analysis and tested for optimization using Genetic Algorithm technique. The model is shown to be effective MRR and Surface Roughness shown improved when used optimized machining parameters. | - |
dc.publisher | Manufacturing Technology Today | - |
dc.title | Optimization Study of Process Parameters using Genetic Algorithm in EDM | - |
dc.vol | Vol 19 | - |
dc.issued | No 5-6 | - |
Appears in Collections: | Articles to be qced |
Files in This Item:
File | Size | Format | |
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Optimization study of process parameters using genetic algorithm.pdf Restricted Access | 4.43 MB | Adobe PDF | View/Open Request a copy |
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