Development of an Optimum Design Methodology of Cylindrical Roller Bearings Using Genetic Algorithms

In the design of cylindrical roller bearings, the long life is the one of the most important criterion. Bearing standards define the design space available to a designer for deciding internal geometries of the bearing. Based on the rated speed and loading conditions, the design has to satisfy constraints of geometry and strength. An optimum design methodology is needed to achieve this objective. Since the fatigue life is directly proportional to the basic dynamic capacity, for the present case it has been chosen as objective function. It has been optimized by using a constrained non- linear formulation with real- coded genetic algorithms. Design variables include four geometrical parameters: the bearing pitch diameter, the diameter of the roller, the effective length of the roller, and the number of rollers. In addition to these another five design constraint constants are included, which indirectly affect the basic dynamic capacity of cylindrical roller bearings. The five design constraint constants have been given bounds based on the parametric studies through initial optimization runs. The effective length of the roller is taken corresponding to the standard roller diameter, which has standard discrete dimensions. There is good agreement between the optimized and standard bearings in respect to the basic dynamic capacity of the bearing. A constraints violation study has been performed to assess the effectiveness of each of the constraints. A convergence study has been carried out to ensure the global optimum point in the design. A sensitivity analysis of various geometric design parameters has been performed to see changes in the basic dynamic capacity of the bearing, and results show that no geometric parameters have adverse affects.