Multivariate product quality monitoring method oriented to digital workshop

Abstract

A multivariate product quality monitoring method oriented to a digital workshop includes the steps: building a quality information acquisition scheme suitable for the digital workshop; building a quality control and improvement model oriented to the digital workshop, and particularly performing multivariate process capacity analysis based on an improved principal component analysis method according to multiple quality characteristics of key processes of key products of a machining workshop; controlling and diagnosing multivariate product by the aid of principal component analysis technology to solve the problem that a multivariate statistical control chart difficultly diagnoses and positions process exception. The quality assurance capability of the key processes of the key products can be quantitatively evaluated by the workshop, and a source of a quality problem is timely positioned when the quality problem arises, so that further cost loss is avoided.

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...

AI Technical Summary

Problems solved by technology

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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