Abstract
The design of rolling element bearings has been a challenging task in the field of mechanical engineering. While most of the real aspects of the design are never disclosed by bearing manufacturers, the common engineer is left with no other alternative than to refer to standard tables and charts containing the bearing performance characteristics. This paper presents a more viable method to solve this problem using genetic algorithms (GAs). Since the algorithm is basically a guided random search, it weakens the chances of getting trapped in local maxima or minima. The method used has yielded improved performance parameters than those catalogued in standard tables.
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Indraneel Chakraborty is currently with Massachusetts Institute of Technology and can be reached at indranil@mit.edu
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Vinay Kumar is currently with Mindtree Consulting, India and can be reached at vinayk@mindtree.com
