This paper highlights the transformative shift in asset management practices within Bioresources, focusing on transitioning from reactive measures to proactive strategies for maintaining asset health. The reliance on reactive measures such as “Assets Out” boards, poor communication, manual job requests, and waiting for failures has been replaced by a proactive framework that prioritises asset condition inspections, automated job builds, and advanced dashboards to inform planning, maintenance and asset strategy decisions.

Key innovation has been the use of our Asset Health App and Dashboard. Real time capture of inspection data with automated notifications gives Bioresources bespoke data-driven insights into our assets. When we start to include further data sources (condition monitoring, service reports, etc) and using machine learning (either by AI or logic built by us) this will speed up analysis and the outputs will then go from Proactive to Predictive or the utopia of Prescriptive maintenance. This year, after several thousands of inspections, we will start to carry out FMECA (Failure Mode, Effect and Criticality Analysis)studies on our troublesome assets with our expert maintainers and suppliers to work on our “forever fixes” to eliminate or reduce future failures.

Placing each asset within the 5 stages of an asset life (Design, Install, Maintained, Potential Failure and Functional Failure) DIMPF has changed the lag measure of “Assets Out” into multiple lead measures. By aligning maintenance strategies with real-time data and future technological advancements, Bioresources is working on Data Driven Asset Management to become more efficient and reliable across all operations