Process parameter selection for optical silicon considering both experimental and AE results using Taguchi L9 orthogonal design
| Autor: | Yuan-Chieh Cheng, Adekunle Moshood Abioye, Khaled Abou-El-Hossein, Abdalla A. S. Abbas, Muhammad Mukhtar Liman, Lukman N. Abdulkadir |
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| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Materials science Mechanical Engineering Rake Mechanical engineering Condition monitoring 02 engineering and technology Process variable Industrial and Manufacturing Engineering Computer Science Applications Taguchi methods Rake angle 020901 industrial engineering & automation Machining Acoustic emission Control and Systems Engineering Surface roughness Software |
| Zdroj: | The International Journal of Advanced Manufacturing Technology. 103:4355-4367 |
| ISSN: | 1433-3015 0268-3768 |
| Popis: | Optical industry has since been employing the use of ultra-high precision machining (UHPM) to manufacture wide range of optical products. One of the major materials used for producing optical product is optical silicon. However, improving surface quality of the product within 10 nm Ra has remained a research focus. Surface roughness during optical silicon turning which is an important quality determinant depends on factors such as feed rate, depth of cut, cutting speed, nose radius, clearance, and rake angles. To achieve required/targeted quality characteristic, there is need for appropriate selection of these process parameters. Therefore, to create a manufacturing industry that is autonomous, a reliable monitoring system for increased production needs to be developed. This research discussed process parameter selection through variation and application of acoustic emission monitoring technique for obtaining optimal surface roughness in ultra-high precision turning (UHPT) of optical silicon using the Taguchi L9 design. The result obtained showed 100% similarity between the experimental and acoustic emission prediction and the superiority of cutting speed over both nose radius and rake angle. |
| Databáze: | OpenAIRE |
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