By David Hannaby, market product manager for presence detection at SICK UK
Manufacturers 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, providing new levels of transparency for operators to understand and interpret the data that sensors produce.
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. We can then represent that data in ways that allow operating personnel at all levels to get health checks in real time and to see historic data in new ways.
We are now seeing the first 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, quite literally, bolting on a real-time, continuous condition monitoring sensor to many different machines, including motors, pumps, conveyor systems or 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-configured thresholds. By considering previously disparate sets of data together, new insights are gained. As a result, changes in performance are detected early and maintenance work can be planned based on real data.
Monitoring Box
New digital services platforms are also enabling plug-and-play condition monitoring to assist with preventative and predictive maintenance of sensors, machines, processes and plants. They can be adapted for all sorts of operating requirements to provide live status feedback and historical analysis supporting more effective maintenance and optimised efficiency.
When enabled using pre-configured 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 have the power to predict e.g. to help to calculate, based on real measurement values, when a particular component or device is nearing the point of failure, so that it can be replaced before it leads to down time.
We are already seeing how early adopters are gaining unexpected insights. For example, using SICK’s monitoring app for its FTMg multifunctional flow sensor, one of our customers has identified 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 efficient, improving compressor control and managing peak loads.
Augmented Reality
In a completely different way, Augmented Reality offers an exciting, and surprisingly simple, visualisation of data from sensors. New developments in the technology are enabling sensor data to be merged with a camera picture and the results displayed on a smart phone.
SICK’s first development is SARA, the SICK Augmented Reality Assistant. SARA has enabled simple troubleshooting and configuration of LiDAR sensors on Automated Mobile Robots. Diagnosis and correction of machine downtime, such as a field infringement, can be done ‘on the spot’ without the need to connect 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 afforded added flexibility, 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 unnecessary time and costs, and increasing machine availability. Intervals between service visits can be optimised, machine stoppages avoided, and new efficiencies identified. Better condition monitoring and predictive maintenance benefits Overall Operating Efficiency and leads to more commercial added-value and.
