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针对存在设置偏差的小批量离散制造过程,研究了每次调整成本固定且调整存在随机误差情形下的质量控制问题。在建立过程状态空间方程模型的基础上,通过贝叶斯方法估计过程的未知参数,利用动态规划的方法得到了边界形式的过程最优调整策略。通过算例验证了所提出调整策略的有效性,并利用仿真对本文提出的调整策略与其他调整策略进行了比较分析,结果表明,本文提出的方法能够更好地减少过程总体质量损失。
Aiming at the small-batch discrete manufacturing process with setting deviation, the quality control problems with each adjustment cost fixed and adjusting for random errors are studied. On the basis of establishing the state space equation model of the process, the unknown parameters of the process are estimated by the Bayesian method, and the boundary optimal process strategy is obtained by using the dynamic programming method. An example is given to verify the effectiveness of the proposed adjustment strategy. The simulation results show that the proposed method can reduce the overall quality loss better.