A METHOD FOR AUTOMATION OF THE PROCESS OF DETERMINING THE ROOT CAUSE OF STABILITY VIOLATION IN COMPLEX STOCHASTIC SYSTEMS
The analysis of the main cause of nonconformities, deviations and incidents in the activities of various companies is an integral part of the whole process of compliance with certain industry standards. At present, there are many different approaches, techniques and procedures for identifying the sources and root causes of inconsistencies. However, often in practice, the application of these techniques involves a number of difficulties due to the lack of tools that consolidate data, methods and resources used in the identification of inconsistencies and determination of the causes generating them. The article considers the approach to solving this problem by the example of automating processes for identifying nonconformities, and determining the method of data visualization. The sequence of stages for identification process of inconsistencies and their main causes are considered. Based on the existing mathematical tools for data evaluation and visualization, a method is provided for determining the key parameters for analyzing input messages that contain information about inconsistencies. The structural-functional scheme of the method is presented, including subsystems for determining the methods and parameters of the control, determining the conditions for breaking stability. The paper presents an algorithm for computer detection of the main cause of inconsistencies and deviations. As an example, there is a structural diagram, describing a chain of interrelated elements in the pharmaceutical industry. This example shows the matrix of the table inconsistency dependencies and their probabilistic values. Based on the results of the method study for identifying unstructured messages, an algorithm for semantic analysis has been developed, including the semantic data analysis and the classification. The generation of a scoring table allows a further semantic analysis of the message.