Reliability, availability, and maintainability (RAM) modelling are an essential tool for ensuring the optimal performance of plant systems. RAM modeling is an established approach used to analyze the performance of existing physical systems using data and statistics gathered from historical performance.
However, with the availability of digital twin technology as well as IoT and Data Analytics tools, there is potential to further enhance plant improvement efforts. Digital twin creates a virtual model of a system that can be used to simulate and test different scenarios. By integrating RAM modeling and digital twin, plant practitioners can obtain a more comprehensive understanding of system performance, reduce downtime, optimize maintenance schedules, and improve overall system reliability and availability.
This presentation will discuss the key principles, techniques, benefits, and challenges of RAM modeling and digital twin, and explore how practitioners can leverage both approaches to future-proof plant improvement efforts.