Speaker
Description
In the rapidly evolving landscape of industrial operations, Asset Performance Management (APM) has emerged as a pivotal framework for enhancing reliability, availability, integrity, and efficiency, while strategically managing the entire asset lifecycle. Aligned with the ISO 55001 standard, APM forms a critical part of the asset management system, enabling organizations to maximize value from physical and digital assets by focusing on asset risk, cost, and performance.
In parallel, the dramatic evolution of digital technologies such as IoT, Big Data, and Machine Learning has generated an abundance of data that can provide unrivaled understanding into asset health and performance. However, these advancements also introduced significant challenges in managing, analyzing, and generating value from vast datasets leading to the “fallacy of Big Data”, where excessive data collection can obscure actionable insights and strain resources.
This paper reviews how APM supports business processes to achieve the outcomes outlined in ISO 55001, while exploring common challenges and pitfalls of the Big Data fallacy. Drawing parallels with Asset Integrity Management (AIM), we advocate for a structured and methodological approach to data management through an APM lens, emphasizing the importance of identifying and containing asset risks and vulnerabilities. The approach also involves monitoring for compliance and effectiveness, while measuring risk spend efficiency. We will conclude by reviewing practical use cases and by offering insights into future trends and research directions.
