Research On Business Process Optimization Based On Complex Event Processing In Industrial Big Data Environment

As a pillar industry in China,the process industry has outstanding problems such as low resource utilization rate,high energy consumption,poor product quality and high production cost.The development of enterprises faces severe challenges.With the development of industrial big data,under the background of the national strategy of“Made in China 2025”,the process industry has ushered in a new opportunity for“transformation and upgrading”.At present,various parts of industrial production have accumulated massive production and management data.How to exploit the potential value of massive data collected during the production process and how to optimize the allocation of management resources and market resources have become a hot topic in the research of current process industry.Business Process Optimization plays a key role in addressing masses of challenges the process industry faced.Due to the large industry gap in the process industry and the differences in the objectives,tasks and methods of business process optimization,this paper takes the froth flotation production process in the ore dressing enterprise as the application scenario.In the froth flotation production process,although a large number of advanced equipment are used to monitor the production process,the test data is often used for production status tracking or equipment failure warning;or the operator is provided with part of the production data to optimize the business process with the knowledge of experience.However,the flotation production business process is a complex and variable production process with multiple production parameters.It is difficult to achieve optimal control of business processes with manual experience.At the same time,the current flotation production process control often considers reference foam image data merely,ignoring the impact of collecting machine data from flotation equipment on the production process.In order to solve the problems in the foam flotation production process of mineral processing enterprises,this paper introduces complex event processing technology in the process of business process optimization.For the characteristics of foam flotation production process,the event model is constructed by using the controlled variation of the flotation production process and the foam feature data,and the multi-model data is integrated.The event model uses a complex event processing model to integrate multimodal data and use data to optimize the flotation production process.The data isthen used to optimize the flotation production process.The main work of this paper can be summarized as:(1)Analyzing the foam flotation business process,sorting out the mechanism relationship between flotation production parameters and foam feature changes,decomposing atomic events,and constructing a complex event processing model based on colored Petri nets.(2)Using the S-invariant analysis method,the proposed complex event processing model based on colored Petri nets is optimized and verified.(3)In order to verify the feasibility of the complex event processing model in the industrial big data environment,the Flink distributed computing framework was chosen to implement the complex event processing model,and finally we tested the complex event model distributed environment and stand-alone health through multiple sets of data.