A multivariate product quality monitoring method for digital workshop
A quality monitoring and multivariate technology, which is applied in the fields of product multivariate quality monitoring, process capability analysis and quality problem diagnosis of machine-processed product manufacturing quality, and can solve problems such as low operability, heavy workload, and economic losses of enterprises
Active Publication Date: 2018-03-16
XI AN JIAOTONG UNIV
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However, with the continuous improvement of the manufacturing level and the continuous improvement of people's quality requirements, this method of controlling single variables has exposed some problems.
In the actual workshop manufacturing process, the various processes and quality characteristics are not all independent of each other, they are often related, and simply monitoring them separately will definitely bring certain errors to the quality control of the workshop
In the digital processing workshop, these errors will bring greater economic losses to the enterprise
In order to take into account the correlation between variables, K.S.Chen, W.L.Pearn and P.C.Lin proposed to use the correlation diagram between variables for further monitoring. The disadvantage of this method is that when there are many variables to be monitored, the correlation The number of graphs increases too fast, the workload is heavy and the operability is not great
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[0069] Such as Figure 5 As shown, a switch manufacturer needs to mill a blind hole on the surface of a switch part in the process of processing a switch part. This process has four specific parameter requirements, as shown in Table 1. Multivariate quality control and diagnosis research was carried out for the four quality characteristics in Table 1, and the measurement data of the four quality characteristics are shown in Table 2. Based on 50 sets of sample data T collected on the workshop site for the four quality characteristics of diameter, depth, distance 1, and distance 2 2 Control charts and MEWMA control charts such as Figure 6 , Figure 7 shown.
[0070] Compare and observe the T of the milling process 2 control chart and MEWMA control chart, we can easily find that at T 2 Control chart, sample 37 is about to exceed T 2 The upper control limit, but not exceeded; in the MEWMA control chart, sample 37 obviously exceeded the upper control limit of the control char...
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A multivariate product quality monitoring method for digital workshops. Firstly, a set of quality information collection schemes suitable for digital workshops is constructed; Multivariate process capability analysis based on improved principal component analysis method was carried out for multi-quality characteristics; for the problem that multivariate statistical control control charts are difficult to diagnose and locate process abnormalities, it is proposed to use principal component analysis technology to realize multivariate quality control and diagnosis; the invention can make the workshop Quantitatively evaluate the quality assurance capabilities of key processes of key products, and locate the source of quality problems in a timely manner when quality problems occur, thereby avoiding further cost losses.
Description
technical field [0001] The invention belongs to the technical field of quality control in the processing and manufacturing process of mechanical products, and in particular relates to a product multivariate quality monitoring method for digital workshops, which is a process capability analysis and quality problem diagnosis for the manufacturing quality of machine-added products based on the principal component analysis method Technology. Background technique [0002] Statistical process control (SPC) refers to the method of applying mathematical statistical analysis theory to monitor and control product quality in the production process. It is an important technology in quality control and an effective guarantee tool for obtaining qualified product quality. It is also a process performance monitoring and The basis for process anomaly diagnosis. Traditional SPC technology utilizes the standard Shewhart control chart, which can monitor whether the process is in a stable state...
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IPC IPC(8): G06Q10/06
Inventor 许艾明高建民陈琨于艳鹏杨志明
Owner XI AN JIAOTONG UNIV