Fault cause determination method and device, equipment and storage medium

Abstract

The embodiment of the invention discloses a fault cause determination method which comprises the following steps: determining at least one fault and a corresponding fault possible cause, and establishing a quality root cause analysis chart; cause nodes in the quality root cause analysis graph are in one-to-one correspondence with possible causes of the fault; aiming at each fault, determining the point contribution rate of each cause node corresponding to the fault according to the quality root cause analysis graph, and sorting according to a sequence from large to small; and obtaining the fault possible cause corresponding to the cause node with the set digit before ranking as the generation cause of the corresponding fault. According to the fault cause determination method provided by the embodiment of the invention, the quality root cause analysis graph is established, the graph database algorithm is combined, and the point contribution rate of the cause nodes is calculated and sorted, so that the fault cause which has the greatest influence on the fault is determined, the digitalization of the workshop production and manufacturing process is realized, the industrial process and the complex relationship can be clearly described, an industrial neural network is formed, and the fault generation cause is analyzed accurately and reliably.

Description

technical field [0001] The present invention relates to the technical field of fault diagnosis, in particular to a fault cause determination method, device, equipment and storage medium. Background technique [0002] In the traditional industrial manufacturing field, the management of the workshop includes the maintenance of normal conditions and the handling of faults. The occurrence of such faults and the delayed resolution of faults will not only increase operating costs, but also seriously affect the work of employees. Efficiency and long-term development of enterprises. Therefore, the handling of fault events and the analysis of their causes are very important. In the actual production process, due to the heavy production tasks and high quality requirements, the complexity of the production process environment is greatly increased, and it is more likely to cause failures. [0003] The cause of failure events is traditionally judged by staff based on human experience, ...

AI Technical Summary

Problems solved by technology

In the actual production process, due to the heavy production tasks and high quality requirements, the complexity of the production process environment is greatly increased, and it is more likely to cause failures

[0003] The cause of failure events is traditionally judged by staff based on human experience, but for traditional manufacturing companies, the workshop production process is complex and unpredictable, and the cause of failure may be equipment, tooling, personnel It is obviously inefficient to judge the cause of the fault simply based on the experience of the staff, and it is impossible to effectively avoid the occurrence of similar faults.

In addition, in the current fault analysis, there is no clear connection between the generated faults and equipment, tooling, personnel, materials, processes, environment, etc., and they are scattered in the equipment or human brain, resulting in fragmented and independent distribution of existing industrial knowledge characteristics, and many rely on the experience of technicians, which brings inconvenience to industrial intelligent decision-making

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