Predictive maintenance is a concept that has often been more talked about than implemented. But as we see various strands of machine and system intelligence coming together in the trend known as ‘Industry 4.0’, more of the promise of predictive maintenance now looks capable of being fulfilled.
The challenge with predictive maintenance is timing. Its purpose is to detect failures in industrial equipment before they happen, so that maintenance can be done at exactly the right time. Not too late, as this can lead to equipment failure, potentially entailing long production downtimes and high replacement or repair costs. But also not too early. This is the problem with scheduled maintenance, which consumes time, resources and money for the inspection of equipment which is still in perfectly good condition.
To meet the demand for predictive maintenance capability, industrial equipment OEMs are now evaluating the technologies and component types required to capture machine data, analyse it and make it available to the user. Connected sensors are one such technology, to measure various physical properties such as temperature, acceleration, current, voltage and sound. The Future Sensor Solutions division of Future Electronics offers the expertise of technology specialists and a broad product portfolio to help OEMs implement advanced machine sensing systems.
The sensed data then need to be amplified and digitised before they can be handled by a microcontroller. Examples of components for such functions may be found in this issue of FTM, which is focussed on industrial systems: STMicroelectronics’ MEMS motion sensor on page 5 and current sensor on page 25, for instance, and the LPC43S57 microcontroller from NXP Semiconductors on page 29.
Beyond the hardware element of the design, I believe that the real key to successful predictive maintenance is proper analysis of the data captured by the sensors at the front end of the system. This may be done locally, or it may be aggregated in the cloud as so- called ‘big data’, where patterns emerging from huge populations of machines can be analysed. Here, data security is of crucial importance, a factor recognised by NXP in its design of the LPC43S57, which incorporates a hardware acceleration engine for AES data encryption.
With or without a predictive maintenance element, new industrial systems will continue to aim for new high levels of power efficiency and density, and to provide more and better forms of connectivity and intelligence. The latest and best components for these functions are featured here in FTM, from intelligent power modules and SiC diodes to wireless and wired transceivers and industrial connectors.
Fortunately, the specialists at Future Power Solutions and Future Connectivity Solutions are always on hand to help readers of FTM take advantage of the components and technologies featured here. Enjoy this issue of FTM, and please e-mail email@example.com for information about any of the parts featured.