Modeling a predictive maintenance management architecture to meet industry 4.0 requirements: A case study. Issue 1 (24th December 2020) - Nordal, Helge; El‐Thalji, Idriss
Abstract: Industry 4.0 is the latest paradigm of industrial production enabling a new level of organizing and controlling the entire value chain within a product life cycle by creating a dynamic and real‐time understanding of cross‐company behaviors. It is expected to have a considerable impact in the oil and gas (O&G) sector by revolutionizing current predictive maintenance and operation optimization. There are several challenges to be overcome before the Industry 4.0 vision is achieved: a standardized reference architecture, a business model, robust services, and products are all lacking. This paper develops a reference architecture for an intelligent maintenance management system that complies with Industry 4.0 visions and requirements. The industrial needs were derived from stakeholders and use case scenarios using a case study methodology. Systems engineering methods were applied to transfer the needs of the existing maintenance management system into a desired functional architecture. The new and upgraded requirements are predominantly related to advanced data analytics, resulting in new and modified functions within the traditional "Reporting" and "Analyses" modules. A more complex maintenance program is created through interfaces between various enabled data categories (historical records, real‐time measurements of performance and health, expert‐just‐in‐time). The study points to the changes required in the classical O&G maintenance management process to comply with Industry 4.0 vision and requirements.