Reliability and Integrity of Safety Critical Elements (SCE) and Productivity Critical Elements (PCE), which are fundamental objectives of Asset Management Systems (AMS), are improved significantly when applying Artificial Intelligence (AI) tools to a wide range of data sources.
Integration of data from sources such as Process Control Network (PCN), Computerized Maintenance Management Systems (CMMS), laboratory analyses, testing and inspection reports, among others, allow quick identification of Process Safety opportunities.
Asset Management Optimization Process (AMOP) is designed to review and improve effectiveness of the these data sources, before implementing comprehensive digital platforms.
The robustness of such data foundation has an important strategic role for digital transformation, while real time predictions of SCE´s failures represent a more immediate tactical objective.
AMOP in combination with Ai-RElia-BDt support both of these objectives.