Web Based Artificial Intelligent Condition Monitoring System

Lead Participant: Monition Limited

Abstract

Condition Monitoring (CM) in industry identifies significant changes in a machines performance which could be indicative of developing faults. Many organisations use CM in some form however, according to Plant Services Magazine, current ‘rule’ & ‘case’ based CM is far from optimal since it remains problematic to combine & analyse the array of sensor data due to the variability in (1) the plant equipment; (2) systems componentry; (3) types of failure; (4) operating cycles; (5) operating temperatures; (6) lubrication; (7) & many other factors. As data & processing power becomes ever cheaper and more accessible remotely, there is an opportunity in developing the ‘next generation’ of CM technologies. According to Europe 2020 Factories of the Future report, modelling machine & process simulation is deemed the future tool for predictive maintenance. The application & fusion of Artificial Intelligence with current case & rule-based reasoning methods would allow for new & far superior CM solutions to be engineered. Benefits to end-user organisations include: (1) timely scheduling of maintenance increasing equipment reliability; (2) proactively taking actions to prevent & predict failure; (3) increase asset lifespan; (4) reduced downtime leading to 3-fold increase in production per line; & (5) provide at least 10% energy savings for 55% of all industrial users.

Lead Participant

Project Cost

Grant Offer

Monition Limited, Worksop £290,889 £ 203,622

Publications

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