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中文摘要：
针对质量监控与调整中噪声信息对测量数据质量影响的问题，提出了一种基于统计过程控制（SPC）与工程过程控制（EPC）集成的制造过程质量监控与调整方法。建立了基于波动状态的统计过程控制与工程过程控制集成模型，实现了在质量监控的同时进行波动补偿。在质量监控阶段，首先采用Kalman滤波方法对含有噪声信息的测量数据进行滤波处理，估计得到波动状态，再依据滤波状态建立指数加权移动平均控制图进行质量监控，通过平均运行长度验证了该质量监控方法的性能。在质量调整阶段，基于波动状态对制造过程进行了调整。运用生产实例验证了方法的有效性和准确性。
英文摘要：
A quality monitoring and adjustment method based on the integration of SPC and EPC was proposed to solve the problems of quality control caused by noise in manufacturing processes. The integrated model of SPC and EPC based on variation state was built. Under the integrated framework, the methods of exponentially weighted moving average based on Kalman filter and process ad- justment based on manufacturing process state were put forward to monitor quality and adjust process variations. Quality offset compensation was achieved while monitoring quality by integrating SPC and EPC. At the stage of quality monitoring, the technology of Kalman filter was first adopted to smooth data and to reduce noise, and then control charts were built by the method of exponentially weighted moving average to monitor processes. Average run length was adopted to verify the performance of the proposed method. At the stage of process adjustment, the model of process adjustment was built for smoothed data, and the variation state estimated values were used to adjust process variation. An application sample was developed to illustrate the feasibility and validity of the proposed quality monitoring and adjustment method.
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