A sensor’s eye view of Maintenance 4.0

David Hannaby, market product manager for presence detection at SICK UK, highlights the role of sensors in ‘Maintenance 4.0’.

Manufacturers all over the UK are squaring up to higher operating costs as a result of inflationary pressures and energy price hikes. That means everyone from the maintenance technician to senior management is tightening their grip to protect and optimise their plant and machinery and get the most efficient operation.

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. Manufacturers are told that signing up for a so-called ‘Maintenance 4.0’ will deliver greater added value – and that they can’t afford to lag behind.

So, is there a way to reconcile these apparently conflicting pressures? At SICK, we see digitalisation through the eyes of sensors. That teaches us 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.

Reality check

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

In Maintenance 4.0, data from sensors is enabled through networked connectivity and software, either locally on site or in the cloud, to give people the power to visualise trends and identify patterns. So, they can better understand the health of their machines, and can predict what will happen next.

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 data in ways that provide fresh insights. The technology doesn’t have to be a complex, time-consuming, intrusive or insecure. It can be incremental, low-risk and transformative.

Data from the heart of the machine

Most people are now familiar with the ability of Smart Sensors to output diagnostic data and provide additional information, either about their own status – for example: “Does my screen need cleaning?”, or their process performance: “How many times have I detected something?” Even this simple data can lead to more informed maintenance interventions.

But, because sensors are often positioned right in the heart of machinery, they can provide additional insights over and above their function. Take the SICK MPS-G position sensor, for example. It is used to detect the position of the piston in small cylinders. However, it also provides comprehensive diagnostic data via IO-Link on the piston velocity, cylinder stroke, magnetic field strengths, temperature, vibration, and acceleration. These values can help to track the performance of a pneumatic drive, as well as the service status of the machinery.

SICK has also developed a condition monitoring sensor for servo motors. When added as an extension to a SICK EDS/EDM25 motor feedback encoder, the sHub provides temperature, vibration, position and speed data. So critical mechanical failures, such as ball bearing damage or motor imbalance, can be detected early to pre-empt machinery downtime.

Real-time condition monitoring

While these two examples have specific applications, the recent launch of SICK’s MPB Multi-Physics Box Condition Monitoring Sensor 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, for example via an IoT gateway device, to deliver the data securely. Most importantly, you need the ability to integrate, visualise and analyse the data exactly where and when you need it. SICK’s IntegrationSpace is our distribution channel for a modular portfolio of digital tools, services and cloud-based applications that enable users to do this.

Monitoring Box

As part of these services, the SICK Monitoring Box is an important platform that facilitates digital integration and visualisation for SICK customers. Although it only received its full global launch in October 2022, the Monitoring Box has already been tried and tested in all kinds of customer operations, from manufacturing and logistics to ports, transport systems or waste management facilities.

The Monitoring Box is not a physical box at all, but it does enable 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 Monitoring Box provides transparent data monitoring through an intuitive, browser-based dashboard for desktop or mobile devices.

Configure the SICK Monitoring Box, and transparent information about the health of your machines is just a few short steps away. Depending on your requirements, information such as operating hours, wear, temperature, energy usage or level of contamination, is turned into a valuable resource.

Crucially, the Monitoring Box also affords users the power to predict, for example 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.

Maintenance programs to keep your 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.

We are already seeing how early adopters are gaining unexpected insights. For example, using SICK’s monitoring app for its FTMg multifunctional flow sensor, our customer was able to identify energy cost savings from compressed air usage. By tracking consumption over time, compressed air energy losses were also easier to spot and correct. 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 manage peak loads.

Switching data to visual

Our customers have discovered that the ability to visualise data in the right format for them is the crucial part of the journey in transforming data into a powerful resource. Whether that is a series of graphs on a dashboard, or an overview of the machine itself, the principle is: the simpler the better.

It could be as straightforward as managing a digital twin of all your assets along their entire life cycles. So, the SICK AssetHub presents 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 smart phone.

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. Now that’s a reason for embracing the digital transformation.