【摘要】 建立了基于工序能力指数的零件选配优化模型,通过提高工序能力来相应地提高选配精度,从而使选配工序趋向柔性化,降低废品率,提高生产效率和装配质量。在降低选配工序成本的基础上,通过Markov链随机状态的过程描述了选配公差等指标,构建了选配精度、公差和工序能力指数间的工序能力指数最大及选配工序成本最小化的多目标约束模型,并使用序列无约束最优化技术SUMT对基于动态随机多目标规划的选配约束非线性模型进行优化求解,最后通过实例对该模型的有效性给予了验证。更多还原

【Abstract】 An optimization model of matching parts assembly based on process capability index was constructed to improve the precision of selective assembly accordingly by upgrading the process capability so as to make the assembly process be flexible, reduce the ratio of waste product, boost the productivity and quality of assembly and create more benefit for increment of product. Based on reducing the cost of matching assembly process, by way of process of Markov chain in the random condition, the tolerance index of matching assembly and others was described, the multi-object restriction primary model of maximal process capability index and minimal cost of matching assembly process among the precision of the assembly, tolerance and the process capability index were constructed. By using the sequential unconstrained minimization technique, this restriction model of matching assembly based on dynamic multi-object programming has been solved, and the model has been validated through a practical example.更多还原