The focus in this paper is to automatically design the air-bearing surface (ABS) considering the randomness of its geometry as an uncertainty of design variables. Designs determined by the conventional optimization could only provide a low level of confidence in practical products due to the existence of uncertainties in either engineering simulations or manufacturing processes. This calls for a reliability-based approach to the design optimization, which increases product or process quality by addressing randomness or stochastic properties of design problems. In this study, a probabilistic design problem is formulated considering the reliability analysis which is employed to estimate how the fabrication tolerances of individual slider parameters affect the final flying attitude tolerances. The proposed approach first solves the deterministic optimization problem. Beginning with this solution, the reliability-based design optimization (RBDO) is continued with the probabilistic constraints affected by the random variables. Probabilistic constraints overriding the constraints of the deterministic optimization attempt to drive the design to a reliability solution with a minimum increase in the objective. The simulation results of the probabilistic design are directly compared with the values of the initial design and the results of the deterministic optimum design, respectively. In order to show the effectiveness of the proposed approach, the reliability analyses by the Monte Carlo simulation are carried out. And the results demonstrate how efficient the proposed approach is, considering the enormous computation time of the reliability analysis.
Probabilistic Designs of Air-Bearing Surface on Manufacturing Tolerances
Manuscript received February 23, 2004; revision received August 9, 2004. Review conducted by: C.-P. Roger Ku.
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Yoon, S., and Choi, D. (February 7, 2005). "Probabilistic Designs of Air-Bearing Surface on Manufacturing Tolerances ." ASME. J. Tribol. January 2005; 127(1): 149–154. https://doi.org/10.1115/1.1828453
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