Smart Predictive Maintenance Framework SPMF for Gas and Oil Industry

Abstract

The O&G industry is facing big challenges which consequently raise the necessity for reforming its traditional business model and integrating digital disruptive technologies such as Digital Twins, Artificial Intelligence and Blockchain. A Digital Twin(DT) is defined as a dynamic intelligent digital replica/model of the physical system/process/service/people which enables just-in-time informed decision making and root-cause analysis using AI. DTs are implanted at different levels such as Equipment/Asset Level Twin, System Level Twin, System of Systems (SoS) Level Twin. This research introduces a novel framework which is based on a Smart Secure Digital Twin (S2DT) to bridge the development gap compared to other leading industries such as manufacturing and automotive. The proposed model relies on Tiny Machine Learning (TinyML) to implement edge intelligence and solve the problems of transfer latency and data overload and consequently achieves low carbon footprint. Edge Intelligence (EI) reduces energy consumption and enhances security and perspective maintenance. The Blockchain Technology is used to solve the privacy, and cybersecurity problems [4]. The Extended Reality (XR) will be used to ensure proper training of operators, and industry 5.0 to boost collaboration between human and machine. At the component level, security is maintained by integrated the locally generated intelligence on a blockchain to insure immutability, and enhance security.