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Optimization of the Burnishing Process for Energy Responses and Surface Properties

Nguyen, T.-T. and Cao, L.-H. (2020) Optimization of the Burnishing Process for Energy Responses and Surface Properties. International Journal of Precision Engineering and Manufacturing, 21 (6). pp. 1143-1152. ISSN 22347593

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Abstract

In the current work, the optimal factors are selected to achieve the improvements in the energy consumption (EB), power factor (PB), decreased roughness (DR) and improved surface hardness (IH) for the roller burnishing operation. The process inputs are the burnishing speed (V), the feed (f), and the depth (d). A hybrid approach comprising the principal component analysis and Technique for Order of Preference by Similarity to Ideal Solution was used to explore the weight values of burnishing performances and select the optimum parameters. Moreover, another optimization technique employing the response surface method and archive-based micro-genetic algorithm was adopted to identify the optimal outcomes in the continuous domain. The main findings showed the performances measured are primarily affected by the burnishing feed, depth and speed, respectively. The energy consumption and roughness are approximately decreased by 31.46% and 7.41%, while the power factor and hardness are improved by 17.47% and 43.09%, respectively, as compared to the general process. The outcomes and findings of the investigated work can be used for further research in sustainable design and manufacturing as well as directly used in the knowledge-based and expert systems for burnishing applications in industrial practices. © 2020, Korean Society for Precision Engineering.

Item Type: Article
Divisions: Faculties > Faculty of Mechanical Engineering
Identification Number: 10.1007/s12541-020-00326-8
Uncontrolled Keywords: Electric power factor; Energy utilization; Expert systems; Genetic algorithms; Hardness; Industrial research; Surface roughness; Sustainable development; Burnishing process; Continuous domain; Industrial practices; Micro genetic algorithm; Optimization techniques; Optimum parameters; Response surface method; Roller burnishing; Burnishing
Additional Information: Language of original document: English.
URI: http://eprints.lqdtu.edu.vn/id/eprint/9017

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