Contribution to the Optimization of Industrial Energy Efficiency by Intelligent Predictive Maintenance Tools Case of an Industrial System Unbalance

Abstract

Today's industry presents many challenges whose the competitiveness weighs heavily on productivity. The future industry or industry 4.0 requires a new way for organizing industrial processes and must integrate smarter maintenance tools capable of greater adaptability in production. This new organization must respond to competitiveness challenges to achieve customer expectations but with a short deadline to market and an optimized cost production in terms of energy consumed reduced breakdowns, etc. One of the failures encountered in the industry, object of our study, is the unbalance corresponds to a rotor imbalance, shaft … due to the non-coincidence of the principal axe of inertia and the inertia center with the rotation axis. Our contribution is to develop the main components surveillance of an industrial installation continuously and follow the evolution through quantifiable and qualifiable data which allows preventing a dysfunction before stopping the production. This surveillance uses very precise predictive maintenance technologies and can tracks parameters in real time: vibration, consumed energy and the various components temperature.