Predictive maintenance & condition monitoring
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 to predict what will happen next. But these do not have to be complex IT
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Maintenance 4.0: Switching sensors to visual
Smart sensors are combining with digital services to open windows for operators to both ‘see’ and ‘understand’ what is going on inside their machines to improve service and maintenance, explains David Hannaby, SICK UK market product manager for presence detection.
systems or big programming projects. New insights are achievable in very practical ways, using simple, ready-to-use and even bolt-on services. 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 does not have to be a complex, time-consuming, intrusive or insecure. It can be incremental, low-risk and transformative. Most people are now 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. And, because sensors are often positioned right in the heart of machinery, they can provide additional insights over and above their function. 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 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.
DATA FROM THE HEART OF THE MACHINE Take the recent launch of SICK’s MPB Multi- Physics Box Condition Monitoring Sensor, which 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
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The SICK sHub turns servo motors into a source of data for real-time condition monitoring
October 2022 Instrumentation Monthly
igitilisation is providing new levels of transparency for operators to understand and interpret the data that sensors produce. In Maintenance 4.0, data from
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