Sensors get the picture in maintenance 4.0


Digitalisation is providing new levels of transparency to understand and interpret the data produced by sensors, writes David Hannaby, SICK UK market product manager for presence detection.

Do you ever wish you had x-ray eyes to see inside a machine or crystal ball to predict exactly when it will fail? The reality is more likely to be a relentless routine of maintenance checklists and service inspections, together with time-consuming preventive procedures. There are still unexpected quality lapses and machine failures. Reactive maintenance visits are too frequent, and additional machine stoppages are unavoidable.

Engineers are discovering the ability to visualise data from sensors in new and surprising ways that can eliminate some of these inefficiencies. In what is being referred to by some as Maintenance 4.0, sensor data becomes a valuable resource that gives operators the power to see trends and identify patterns. Whether interpreting a series of graphs on a dashboard, an overview of the machine or plant, or an augmented reality representation, people can better understand the health of their machines, and predict what will happen next.

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.

This new transparency could be enabled on a smartwatch of an operative patrolling a shop floor, just as much as it allows for easier monitoring by a management team in the company headquarters on the other side of the world.

The technology doesn’t have to be complex, time-consuming, intrusive or insecure. It can be incremental, low-risk and transformative. But it does present a significant new opportunity to add commercial value through better condition monitoring and predictive maintenance, bringing benefits to Overall Operating Efficiency.

Even simple data can lead to more informed maintenance interventions. Most people are familiar with the ability of smart sensors to output diagnostic data and provide additional information, either about their status, e.g. ‘Does my screen need cleaning?’ or their process performance, ‘How many times have I detected something?’

Data from the heart of the machine

But, because sensors are often positioned right in the heart of machinery, they can also provide insights over and above their function. The recent launch of SICK’s MPB Multi-Physics Box Condition Monitoring Sensor, for example, offers an opportunity, quite literally, to bolt on real-time, continuous condition monitoring to many different machines, including motors, pumps, conveyor systems or fans.

The SICK MPB 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.

Getting visibility to the data from your machines is just the first step to taking proactive, rather than reactive, service and maintenance decisions. You also need the connectivity, e.g. via an IoT gateway device, to deliver the data securely. Most importantly, you need the software to integrate, visualise and analyse the data exactly where and when you need it.

SICK’s IntegrationSpace is its distribution channel for a modular portfolio of digital tools, services and cloud-based applications that enable users to do this. It could be as straightforward as managing a digital twin of all assets along their entire life cycles. For example, accessing an asset hub to see a feature-rich and interactive view of all sensors, systems and other devices: useful information that’s right at the fingertips of a maintenance operative from a smartphone.

Monitoring Box

Monitoring Box facilitates digital integration and visualisation for SICK customers. It is not actually a physical box but rather an important digital services platform that enables plug-and-play condition monitoring to assist with preventative and predictive maintenance of sensors, machines, processes and plants. It 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 software provides transparent data monitoring through an intuitive, browser-based dashboard for desktop or mobile devices. Depending on the user’s requirements, information such as operating hours, wear, temperature, energy usage or level of contamination is turned into a valuable resource.

Crucially, users are afforded 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 downtime.

Maintenance programs to keep devices and systems in good condition can be inferred based on diagnoses, statistics and predictions. This makes it possible to carry out inspections, repairs and maintenance in a quick and tailored way, and to plan servicing more reliably.

SICK is already seeing how early adopters are gaining unexpected insights. For example, using a dedicated monitoring app for its FTMg multifunctional flow sensor, a customer was able to identify energy cost savings from compressed air usage. The visualised data made 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. By tracking consumption over time, compressed air energy losses were also easier to spot and correct.

In another example, packaging machine operatives receive fill-level warnings on their smart wristwatches using data from distance sensors monitoring the magazine stack height. Meanwhile, all the data collected can be visualised and monitored on a dashboard by management personnel. Instead of having to undertake routine inspections, some operators have been deployed to other tasks, and the operation is managed more efficiently.

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 smartphone.

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.

Getting More from Legacy Assets

When times are hard, the temptation is to stick with what you know. Yet the received wisdom is to get on board with Industry 4.0 digital technologies in ways that are disruptive and transformative. Seeing Maintenance 4.0 through the eyes of sensors offers a way to reconcile these apparently conflicting pressures. So, you really can squeeze every last drop out of your legacy assets while embracing new digital technologies. The results can be surprising and truly transformative.


About Author

Comments are closed.