Funded Projects › FP7
POWER-OM · Power consumption driven Reliability, Operation and Maintenance optimisation
The normal strategy to keep production systems in good conditions is to apply preventive maintenance practices, with a supportive workforce “reactive” in the case of clearly detected malfunctions. This impact on quality, cost and in general, productivity. Added to this, the uncertainty of machine reliability at any given time, also impacts on product/production delivery times. It is known also that a worn-out mechanism has higher energy consumption.The use of intelligent predictive technologies could contribute to improve the situation, but these techniques are not widely used in the production environment. Often sensors and monitors required for the production environment are non standard and require costly implementations.Power-OM propose to use the electric current consumption monitoring and profiling, as an easy to implement condition based maintenance (CbM) technique, and manage it also as a way to improve the overall business effectiveness, under a triple perspective:• Optimizing maintenance strategies based on the prediction of potential failures and schedule maintenance operations in convenient periods and avoid unexpected breakdowns• Operation: Managing energy as a production resource and reduce its consumption• Product reliability: Providing the machine tool builder with real data about the behaviour of the product and their critical componentsThis universal solution should also be compatible with the added value information that could come from existing sources (control) and sensors used at the machine, and jointly this will preserve current and future investment in the field. The project will research also in the required infrastructure and new business model for maintenance services provider.Power-OM will be applied in machine tools, focussing on spindles and linear guides as responsible for the most common and cost-intensive downtimes. However the technology developed in this sense would have high potentials across other types of machines.
Consortium · 7 organisations
FUNDACION TEKNIKER
ES · €709,207
LULEA TEKNISKA UNIVERSITET
SE · €402,460
MARPOSS MONITORING SOLUTIONS GMBH
DE · €346,689
MONITION LIMITED
UK · €231,360
GORATU MAQUINAS HERRAMIENTA, SA
ES · €235,403
FAGOR AOTEK S. COOP
ES · €369,600
PREDICT SAS
FR · €356,575
Research fields
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