Abstract
The design of rolling 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 chart 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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 649-659 |
| Number of pages | 11 |
| Journal | Engineering Optimization |
| Volume | 35 |
| Issue number | 6 |
| DOIs | |
| State | Published - Dec 1 2003 |
| Externally published | Yes |
Keywords
- Genetic algorithms
- Optimum mechanical design
- Rolling element bearings
ASJC Scopus subject areas
- Computer Science Applications
- Control and Optimization
- Management Science and Operations Research
- Industrial and Manufacturing Engineering
- Applied Mathematics
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Cite this
Chakraborty, I., Kumar, V., Nair, S. B., & Tiwari, R. (2003). Rolling element bearing design through genetic algorithms. Engineering Optimization, 35(6), 649-659. https://doi.org/10.1080/03052150310001624403