36 n SENSORS February 2025 www.drivesncontrols.com Using sensors to capture IoT data from existing machinery There is a wide variety of sensors that support di erent types of data collection, enabling manufacturers to track metrics related to productivity, consumption, wear and other factors. Common sensors include: n Proximity sensors used for counting These devices can capture each part being produced, or track the amount of material going into a machine. Comparing these metrics can help to understand scrap and losses. n Current and pressure sensors Current sensors can monitor machine speeds and tooling forces. Pressure sensors capture similar information for hydraulic-based machines. They can help to determine setup, tooling expectations and machine norms. Variations from base measurements can indicate issues a ecting quality or maintenance. n Vibration sensors These measure the size and frequency of vibrations in equipment and can help to detect imbalances and other issues to predict maintenance needs. Additionally, vibration measurements can provide “signatures” for good parts and healthy machines. Data from sensors can be captured by PLCs or dataloggers which convert the data into a usable format and make it accessible to shopoor networks. Newer smart IoT sensors can be access networks directly without needing intermediary devices. The information can be sent to a server that supports the OPC (Open Platform Communications) standard. OPC or other software may be needed to calibrate the data to match a machine’s own values. From there, the information can be fed into a manufacturer’s ERP (enterprise resource planning) and/or MES (manufacturing execution system) software to populate real-time reports with data. The software maintains both current and historical data, making it possible to analyse this information from the perspective of quality, eciency and other key metrics. Manufacturers typically use the captured data to: n collect information for end-of-shift reporting to determine whether the material used matches the number of parts expected to be produced; n track counts in work centres to assist in production planning; n match work orders to what’s running in the machine to update inventory consumption; n compare how many cycles have been completed with the number of parts made, to understand the scrap being produced; n determine downtimes; and Smart machines can provide manufacturers with invaluable data. But buying a new machine just for its IoT capabilities can be hard to justify. A less costly approach is to add sensors to capture real-time data from existing equipment. Lynn Loughmiller, a software engineering manager at DelmiaWorks, explains how this works. Adding sensors to existing machinery can help to gather real-time data for IoT applications
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