期刊
MATERIALS AND MANUFACTURING PROCESSES
卷 28, 期 7, 页码 835-841出版社
TAYLOR & FRANCIS INC
DOI: 10.1080/10426914.2012.718474
关键词
Machining; Nickel-based alloy; Particle swarm optimization; Residual stress
资金
- National Science Foundation [NSF-CMMI-1130780]
- Div Of Civil, Mechanical, & Manufact Inn
- Directorate For Engineering [1130780] Funding Source: National Science Foundation
In this study, physics-based simulations are utilized to predict the forces and residual stresses induced during machining, and the results were validated using the experimental measurements. Physics-based simulations also involve uncertainty in the predicted values that can be represented as expected value and variance of the predictions. These predictions are inputted to a multiobjective optimization methodology to select the optimal machining parameters where competing or conflicting objectives constitute hurdles in the decision-making of the manufacturing plans. The objectives are chosen as related to residual stress measurements and predictions. Multiobjective particle swarm optimization (PSO) procedure is employed in optimizing process parameters. Objectives are solved for minimizing tensile residual stresses on the surface, maximizing peak compressive residual stresses, and minimizing the variance of these variables in order to increase certainty in the predictions. The optimum machining parameters corresponding to this multiobjective optimization are represented in both objective function and decision variable spaces.
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