Asset Performance 4.0 Hybride Conferentie
Asset Performance 4.0 is een hybride conferentie en beurs voor iedereen die bezig is met digitalisering en nieuwe technologieën in onderhoud, asset management en operations. Het event vindt plaats van 26 tot 28 oktober in Antwerpen en online. Alle presentaties gaan door in het Engels.
Ook het project Circulair Onderhoud wordt er voorgesteld aan de hand van 2 cases:
Woensdag 27 oktober om 11:00 uur: Prepared for a datadriven future?- Mischa Beckers (HZ University of Applied Sciences)
A data driven and risk based approach often go hand in hand when dealing with smart maintenance and operations. Using an asset management framework including functional decomposition, FME(C)A, criticality analysis etc. may lead to a set of components that need (immediate and) most attention. Analytics helps in getting insight in current status of components, relating behavior to observed consequences and is preferably used for predicting future behavior and status. However, what does that insight actually tell you, is the observed relation really significant and how to interpret a prediction model? Both the availability and the amount and quality of data have an effect on this. Next to that, the objective of using Analytics, such a binary or multiclass classification (failure or failure classes), regression (lifetime or failure time) or probability estimation (survival analysis) is dependent on the type of data that is available.
By means of several real-life examples we unravel some of the underlying basic principles and best-practices. Among these examples are:
- RIOBASE, prediction of failure and classification of damages for sewer pumping stations and piping using both sensor and process data and inspection robot videos/images
- COMPI, remaining useful lifetime prediction for valves in process industry using both process, maintenance and sensor data
- CAMPIONE, survival analysis for predicting useful lifetime prediction for heat pumps in buildings when only process data is available
- AURTUB, classification of erosion categories for wind turbine blades using 3D laser scans