Open AccessImproving the process performance of magnetic abrasive finishing of SS304 material using multi-objective artificial bee colony algorithm
Author(s) -
Sandip Baburao Gunjal,
P. J. Pawar
Publication year - 2020
Publication title -
engineering review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.198
H-Index - 11
eISSN - 1849-0433
pISSN - 1330-9587
DOI - 10.30765/er.1511
Subject(s) - abrasive , surface roughness , response surface methodology , process (computing) , mechanical engineering , multi objective optimization , materials science , process engineering , computer science , algorithm , engineering , composite material , machine learning , operating system
Magnetic abrasive finishing is a super finishing process in which the magnetic field is applied in the finishing area and the material is removed from the workpiece by magnetic abrasive particles in the form of microchips. The performance of this process is decided by its two important quality characteristics, material removal rate and surface roughness. Significant process variables affecting these two characteristics are rotational speed of tool, working gap, weight of abrasive, and feed rate. However, material removal rate and surface roughness being conflicting in nature, a compromise has to be made between these two objective to improve the overall performance of the process. Hence, a multi-objective optimization using an artificial bee colony algorithm coupled with response surface methodology for mathematical modeling is attempted in this work. The set of Pareto-optimal solutions obtained by multi-objective optimization offers a ready reference to process planners to decide appropriate process parameters for a particular scenario.