Maintenance 4.0: Seeing is believing
Do you ever wish you had x-ray eyes to see inside a machine to predict exactly when it will fail? The reality is probably a relentless routine of maintenance checklists and service inspections, together with time-consuming preventive procedures. Nevertheless, unexpected lapses in product quality and machine failures are still likely to happen. David Hannaby, Market Product Manager for SICK UK explains.
Too frequent reactive maintenance interventions and unplanned machine stoppages only add to the current squeeze on operating costs that all manufacturers are feeling at the moment. At such times, the received wisdom is to get on board with Industry 4.0 digital technologies. Manufacturers are encouraged to leverage “Maintenance 4.0” to extract greater added value. Yet, when times are hard, the temptation is to stick with what you know. So, is there a way to reconcile these apparently conflicting pressures?
Through sensors’ eyes
Engineers are discovering that the ability to visualise sensor data in new and surprising ways transforms it into a powerful resource to better understand the health of machines. Whether that is a series of graphs on a dashboard, an overview of the machine or plant, or an Augmented Reality representation, the principle is: the simpler the better.
The technology doesn’t have to be complex, time-consuming, intrusive or insecure. Progression can be incremental and relatively low risk. It could be as straightforward as managing a digital twin of all your assets along their entire life cycles. So, for example, our customers use the SICK AssetHub 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 smart phone.
Data from the heart of the machine
Most people are familiar with the ability of Smart Sensors to output diagnostic data and provide additional information, either about their own status, e.g. “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 also provide 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 fields 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
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, e.g. 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.
As part of these services, the SICK Monitoring Box facilitates digital integration and visualisation for SICK customers. It is not actually a physical box, 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. When enabled using pre-configured Apps running on SICK smart sensors, it 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. 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.
Smart watch monitoring
Take the simple example of machine operatives who receive fill-level warnings on their smart wristwatches using data from SICK 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 managed more efficiently.
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.
The vision is for SARA to work with any SICK sensor and with any data provider, technology and vendor independent.
Getting more from legacy assets
Seeing Maintenance 4.0 through the eyes of sensors offers a way to squeeze every last drop out of your legacy assets while embracing new digital technologies. This new transparency could be enabled on a smart watch 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. These systems therefore present a significant new opportunity to add commercial value through better condition monitoring and predictive maintenance, bringing benefits to Overall Operating Efficiency. The results can be both surprisingly simple, and truly transformative.