Predictive maintenance boosts output while reducing downtime. Predictive maintenance analytics are revolutionising the maintenance process as part of Smart Manufacturing. Factory maintenance will no longer be reactive, time-consuming, and expensive as manufacturers embrace a more proactive predictive maintenance and condition-based monitoring paradigm. Instead, key issues will be predicted and prevented before they develop and result in downtime.
Why do you need it?
No matter how little, each breakdown is unprofitable for the company. One loose bolt causes faster wear and tear, a shorter lifespan for the equipment, and unexpected equipment downtime.
In this case, you incur more costs for recovery, your manufacturing quality suffers, you don't run a simultaneous device analysis, and the production process is opaque.
Utilizing innovations like big data, the Internet of Things, and machine-to-machine communication, industrial automation is a key component of the Industry 4.0 revolution.
How does it work?
Early warning indicators of machine failure are predicted by cloud software, ML/AI models, and IIoT sensors. Early identification lessens losses brought on by sudden unplanned maintenance and downtime.
Maintenance on machines is only performed when it is necessary. The point at which failure is most likely to occur. This saves several costs
The ROI of predictive maintenance programs has been shown to increase tenfold,
cost-reduction by 25%-30%,
breakdowns by 70%-75%, and
downtime by 35%-45%.