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Industrial Internet platform accelerates the pace of digital transformation in petrochemical industry

2025-01-28 Update From: SLTechnology News&Howtos shulou NAV: SLTechnology News&Howtos > Internet Technology >

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Industrial Internet platform accelerates the pace of digital transformation in petrochemical industry

The integration of China's industrial Internet and the real economy continues to deepen, which is moving from the concept advocacy to the vertical ploughing stage. Recently, we conducted a survey on the petrochemical industry, and found that there are some pain points in the petrochemical industry, such as opaque equipment management, difficult process knowledge inheritance, low level of coordination between the upstream and downstream of the industrial chain, high pressure on production safety, and so on. There is an urgent need to speed up the pace of digital transformation based on the industrial Internet platform, and more information is in the vibrating chain.

We suggest that petrochemical enterprises should take intelligent management and control of equipment and collaborative optimization of production as the starting point to improve the digital level of equipment management, production management, supply chain management, safety management, energy saving and consumption reduction, and accelerate the transformation of the petrochemical industry to the direction of full-process intelligence. Specific recommendations include:

The first is to strengthen the underlying data analysis to promote edge cloud coordination. In the aspect of edge data acquisition, data acquisition tools such as sensors, drones, cameras and 3D scanners are installed, and ubiquitous sensing technology is used to collect multi-source equipment, heterogeneous systems, operating environment, personnel and other data in the fields of oil field geological exploration, drilling, exploitation, transportation, refining, petrochemical and sales, so as to realize a comprehensive perception of the operation status of oil fields, transportation pipelines and refining and chemical plants. In the aspect of edge data analysis, machine learning and deep learning algorithms are deployed in crude oil production devices, key refining and chemical plants, and key nodes of transportation pipelines, and the analysis engine is integrated on the edge controller to realize automatic adjustment and optimization of the device. in the model, data, service three aspects to achieve edge cloud cooperation, more information is in the vibrating chain.

The second is to sort out the knowledge of refining process and develop the industrial model. Focusing on equipment management, we focus on the running condition monitoring model, remote fault diagnosis model and predictive maintenance model of key equipment in refining and chemical industry. Focusing on refining and chemical production, we focus on the simulation and optimization model of refining and chemical process, polymer reaction model, heat exchanger network optimization model, utility system optimization model, energy system optimization model and production quality control model. Focusing on supply chain management, this paper focuses on the research and development of crude oil import supply chain disturbance mitigation model, supply chain flexible operation model, supply chain equilibrium coordination model, cost and risk balance model, planning and scheduling model and so on. Around safety management, research and development of fire and explosion accident risk early warning model based on multi-source safety data fusion, high risk equipment monitoring and fault early warning model, hazard monitoring and early warning model, emergency resource management model, safety emergency scheduling model.

Third, R & D industry solutions to promote typical applications. In terms of equipment management, we will focus on developing and popularizing state monitoring, remote fault diagnosis and predictive maintenance solutions for key refining and chemical units to improve the management level of refining and chemical plants. In the aspect of refining and chemical production, focus on the research and development of refining and chemical production equipment process simulation, intelligent laboratory, operation management optimization, production quality control and other solutions to achieve refining and chemical production optimization. In the aspect of supply chain coordination, it focuses on the research and development of supply chain coordination solutions within petrochemical enterprises and between enterprises, so as to realize the optimization of the whole process of petrochemical supply chain, rational use of resources and optimization of value. In the aspect of safety management, we focus on the research and development of safety supervision solutions for refining and chemical production, dynamic monitoring of pipeline leakage, accurate location of drilling failure points, and emergency command solutions, so as to realize early warning of refining and chemical production risks. for the real-time detection and accurate location of the leakage of long-distance oil and gas pipelines, more information is available in the vibrating chain.

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