Innovative maintenance tools and approaches for manufacturing equipment
Today's manufacturing industries employ technologies that manage and control equipment maintenance. But these solutions, designed to help determine the condition of in-service equipment and to forecast when maintenance should be performed, have performance drawbacks. Correct failure prediction has yet to be achieved by traditional or even modern procedures. The EU-funded SUPREME (Sustainable predictive maintenance for manufacturing equipment) project introduced solutions to enhance the prevention of unexpected production equipment failures in order to reduce downtime, repair costs and energy consumption. Project partners developed and applied cutting-edge signal and data processing tools for predictive maintenance and energy consumption reduction. They also improved and developed new maintenance tools. The developed solutions based on intelligent technologies led to the creation of an advanced predictive maintenance approach that provides correct failure prediction and optimal maintenance operation planning. This integrated method enhances productivity, cuts machine downtime and boosts energy efficiency. The SUPREME team successfully demonstrated the developed predictive maintenance tools at a paper mill in France. The predictive maintenance method greatly reduces the remaining risk, resulting in overall savings of up to 20 % yearly compared to preventive maintenance strategies. In addition, the potential savings in energy consumption are about 5 %. SUPREME helped to achieve improved productivity, safety, security, cost and energy efficiency for equipment condition monitoring techniques. It should boost the paper industry's competitiveness while keeping jobs in Europe.
Keywords
Manufacturing equipment, SUPREME, predictive maintenance, energy consumption, machine downtime
