Multi-objective optimization in CNC turning of S45C carbon steel using Taguchi and grey relational analyses
There are various types of machining process that have been introduced long time ago and yet still be used until now. From time to time, researchers have never stop in seeking for an improvement for these processes in every aspect. One of the famous machining processes that are commonly used is tur...
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| Format: | Thesis |
| Language: | English |
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| Online Access: | http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/61880/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/61880/2/Full%20text.pdf |
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| Summary: | There are various types of machining process that have been introduced long time ago and yet still be used until now. From time to time, researchers have never stop in seeking for an improvement for these processes in every aspect. One of the famous machining processes
that are commonly used is turning process. Interestingly, the optimization of single
performance measures has been successfully reported by many of the researchers.
However, the multi-objective optimization is more difficult and challenging to be studied
due to its complexity. This is because an improvement of one performance measure may
lead to degradation of other performance measure. In response to that, the study of multiobjective
optimization in CNC turning of S45C carbon steel by using Taguchi and Grey
Relational Analysis (GRA) method has been reported in this study. Based on grey
relational analysis, a grey relational grade (GRG) is computed to optimize the machining
parameters of CNC turning process with multiple performance measures which is surface
roughness, material removal rate (MRR), tool wear and power consumption of the machine.
In this study, two important parameters have been selected, namely spindle speed and feed
rate while the depth of cut was set at fixed value. A design of experiment methodology was
employed to determine the relationships between machining parameters with the
performances measures. Through this method, the best setting parameter was found at
spindle speed of 3000 RPM and feed rate of 0.2 mm/rev and results from ANOVA shows
that spindle speed is the main contributor to the change of performance measures with
almost 70% contribution. The findings from this study will benefit in term of knowledge
between the machining parameters with the performance measures. |
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