SPC-EPC integration is an effective method to control the quality of products. Traditional integrated SPC-EPC methods are based on linear ARIMA time series model to describe the dynamic noise of the system. But linear models sometimes are unable to model complex nonlinear relationships. To solve this problem, a method using a kind of nonlinear time series model was presented, that is the threshold autoregressive model (TAR), to describe the dynamic noise of the system, and an MMSE controller based on this model was built and an integrated SPC-EPC control system was further built. Aiming at control failure in the form of step form that is common during the production process, the control result of this controller and integrated control method was analyzed first by examples and also compared with the result of linear controller. Next the result of this integrated method was verified and analyzed further by simulations. The final results indicate that this integrated SPC-EPC method based on nonlinear time series model is effective in controlling complex nonlinear systems which have assignable causes resulting in sustained shift.%SPC-EPC集成是一种控制和提升产品质量的有效方法,目前在传统SPC-EPC集成的研究中通常使用线性时间序列模型来描述过程的动态自相关关系,但线性模型难以对更加复杂的非线性自相关关系进行有效描述.针对这一问题,提出了使用一类非线性时间序列模型,即门限自回归模型(TAR)来描述系统的动态自相关关系,并依此建立最小均方误差控制器,并进一步建立SPC-EPC集成控制体系.针对在生产过程中常见的以阶跃形式存在的过程失控,首先通过例子研究了控制器在单独使用以及集成控制方法下的控制效果并且与线性控制器相应的结果进行了对比,之后通过模拟研究进一步验证和分析了这一集成控制方法的控制效果.结果表明,基于非线性时间序列的集成SPC-EPC控制方法可以针对含阶跃形式失控的复杂的非线性自相关过程进行有效的控制.
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