Study On Some Issues Of Statistical Process Control And Measurement System Analysis

The ideas of preventing defects in quality and seeking transcendence of quality have been embedded in quality management and production process. Prevent principle has been a core and kernel of modern quality management. SPC, as an important tool and technique, has a crucial part in whole production processes. Since Dr Shewhart invented the first control chart in 1920's, SPC has acquired remarkable effects in industrial production and quality improvement by developments and applications in these decades.Quality data, which are analyzed by traditional SPC, must satisfy hypothesis of independence. However, observation sequences are sometimes autocorrelation processes at a certain extent in modern high speed and automatic industry, which easily makes SPC omit alarms. SPC control charts judge processes in or out of control by the rule of points between UCL and LCL or not. As a result, SPC doesn't show how points are good or bad. And the judgment rule only depends on current measured data, which easily omits alarms of no random points between UCL and LCL.Statistical quality management and SPC are based on a mass of measured data. And meanwhile, measurement itself is a process. So it is necessary to analyze the measurement systems, which are used to measure process data. Moreover, the basis theory and methods of MSA are SPC techniques.For localizations and study actuality of SPC, Quality Control of autocorrelation process was studied based on integrated SPC and EPC, and Fuzzy Cluster Analysis was used to identify abnormal patterns of process. Stability analysis and applications of MSA were also studied in this thesis.The major contributions of this thesis are as follows:1. Statistical process monitoring and adjustment was studied, and statistical monitoring methods of autocorrelation processes were presented by means of state space model. EPC feedback adjustment was analyzed deeply, and the design methods of EPC controllers were generalized.2. Based on integrated SPC and EPC, Taguchi's Quality Loss was used to analyze autocorrelation process via feedback adjustment. And Taguchi's S/N was used as a property index to evaluate effects of Integrated SPC and EPC and different monitoring methods.3. Fuzzy Cluster Analysis was used to identify abnormal patterns of process and realize Quality Control of independence and autocorrelation processes.4. EWMA control chart was used to enhance effects of small fluctuation in MSA stability analysis. MSA was generalized to the test of invariable loading rate, and applications of MSA were studied in precision inspection of compression testing machine.In the end, perspectives of improvements of SPC and applications of MSA were given based on studies in this thesis.