Experimental investigation, prediction and optimization of cylindricity and perpendicularity during drilling of WCB material using grey relational analysis
Autor: | Saurin Sheth, P.M. George |
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Rok vydání: | 2016 |
Předmět: |
0209 industrial biotechnology
Engineering Correlation coefficient business.industry General Engineering Mechanical engineering Drilling Regression analysis 02 engineering and technology 021001 nanoscience & nanotechnology Coordinate-measuring machine Grey relational analysis 020901 industrial engineering & automation Machining Position (vector) Range (statistics) 0210 nano-technology business |
Zdroj: | Precision Engineering. 45:33-43 |
ISSN: | 0141-6359 |
DOI: | 10.1016/j.precisioneng.2016.01.002 |
Popis: | Manufacturing is always the heart of majority of industries. Drilling is an extremely important and an essential machining process which requires a lot of attention as in most of the cases it is required for assembly purposes. Majority of the holes produced during drilling are made with the help of Vertical Machining Centre (VMC) meant for pin- hole assembly. Though the tolerance is within limit, assembly problems arise due to the improper geometry of these holes. Various geometrical tolerances like cylindricity, circularity, perpendicularity and position errors are responsible for such assembly problems. This investigation is focussed on cylindricity and perpendicularity in the drilling of Wrought Cast Steel Grade B (WCB) material using SOMX 050204 DT insert. In this work, effect of machining variables like cutting speed, feed rate and depth of cut (canned cycle) are investigated and optimized using grey relational analysis (GRA). Reliable experiments are conducted based on a 33 full factorial, replicated twice. Second order regression models are developed for predicting cylindricity and perpendicularity. The models’ adequacy has been checked by calculating correlation coefficient. It shows that the developed models are well fitted for the prediction of responses within the specific range of input variables. |
Databáze: | OpenAIRE |
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