FEATURE Sensors
Feature sponsored by
Visualising maintenance through
sensors’ eyes M
anufacturers are told that signing up for so-called ‘Maintenance 4.0’ will deliver greater added value. But,
when times are hard, the temptation is to stick with what you know. Seeing digitalisation through the eyes of sensors teaches us you really can squeeze every last drop out of your legacy assets while embracing new digital technologies. That’s because smart sensors are combining with digital services to open windows for operators to both see and understand what is going on inside their machines.
Reality check Starting with a sensor’s eye view means you begin from the ground up. We can ‘plug in’ eyes and ears wherever they are needed, to unlock previously-hidden data, then represent it in ways that allow operating personnel at all levels to get health checks in real time and also check historic data. We are now seeing the fi rst examples
emerging of visualisation and augmented reality tools that can reveal surprising new insights, just by presenting the data from sensors in an appropriate visual format. It could be a simple as literally bolting on a real-time, continuous condition monitoring sensor to many diff erent machines, including motors, pumps, conveyor systems and fans. The SICK MPB Multi-Physics Box Condition Monitoring Sensor measures vibration, shocks and temperature. It can be set up to alert when measured values exceed pre-confi gured thresholds. By considering previously disparate sets of data together, new insights are gained, to detect changes in performance early and plan ahead maintenance work.
Monitoring box
New digital services platforms are also enabling plug-and-play condition monitoring to assist with preventative and predictive
22 December/January 2023 | Automation
By David Hannaby, Market Product Manager for presence detection at SICK UK
maintenance of sensors, machines, processes and plants. They can be adapted for all types of operating requirements, to provide live status feedback and historical analysis supporting more eff ective maintenance and optimised effi ciency. When enabled using pre-confi gured apps
running on SICK smart sensors, the SICK Monitoring Box provides transparent data monitoring through an intuitive, browser- based dashboard for desktop or mobile devices. Depending on your requirements, information such as operating hours, wear, temperature, energy usage or level of contamination, is turned into a valuable resource. Crucially, users can predict through calculation based on real measurement values when a particular component or device is near its point of failure, so that it can be replaced before it leads to downtime. We are already seeing how early adopters are gaining unexpected insights. For example, using SICK’s monitoring app for its FTMg multifunctional fl ow sensor, one of our customers has identifi ed energy cost savings from compressed air usage. By tracking consumption over time, compressed air energy losses are also easier to spot and correct. The visualised data makes it easy for the production team to identify ways of making start-up and shutdown processes more energy effi cient, improving compressor control and managing peak loads.
Augmented reality In a completely diff erent way, augmented
reality (AR) off ers an exciting and surprisingly simple visualisation of data from sensors. New developments in thiss technology allow sensor data to be merged with camera images, displaying the results on a smart phone. SICK’s fi rst development is SARA, the
SICK AR Assistant, which has enabled simple troubleshooting and confi guration of LiDAR sensors on automated mobile robots. Diagnosis and correction of machine downtime, such as a fi eld infringement, can be done ‘on the spot’ without needing a PC. Sensors and sensing systems are the building blocks of Maintenance 4.0. By unlocking real-time and historical data, maintenance and production teams are aff orded added fl exibility, adaptability and responsiveness that saves routine service and reactive maintenance hours, and maximises machine availability. Accurate data can be integrated to deliver new insights and achieve transparency through visualisation. As a result, decisions are based on real data, in real time, saving time and costs and increasing machine availability. Intervals between service visits can be optimised, machine stoppages avoided and new effi ciencies identifi ed. Better condition monitoring and predictive maintenance benefi ts overall operating effi ciency and leads to more commercial value-add.
CONTACT:
SICK (UK)
www.sick.co.uk
automationmagazine.co.uk
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