Use of R.S.M. for Design of Experiments and Optimization of Parameters in Milling Operations

N. L. Bhirud, R. R. Gawande


Experimentation is an important part of manufacturing
domain. If these experiments are planned experiments then,
the data can be converted into the empirical models, which
can be used for finding out the performance of the system
under different situations. It helps in planning and execution
of activities with optimized use of available resources. The
design of experiments is usually carried out by using methods
like full factorial design, fractional factorial design, Taguchi
design and Response surface design. In this paper, we have
reviewed the recent literature for the use of response surface
methodology (RSM) for milling operations. The aim of this
work was to study and present the recent literature in this
field. Initially, the use of RSM for modeling and analysis of
surface roughness is presented, followed by cutting
temperature, cutting force and other parameters. RSM is
found to be a very useful and powerful tool for design of
experiments and optimization of process parameters in milling
operations. It was used by many researchers for modeling and
analysis of surface roughness vibration amplitude, tool wear,
cutting temperatures, cutting forces and burr dimensions.
Hybrid analysis combining RSM with evolutionary algorithms
like genetic algorithms and simulated annealing was also
successfully employed.

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