FEATURE SENSORS & SENSING SYSTEMS
THE ROADMAP TO IOT SUCCESS WITH LEGACY
MANUFACTURING EQUIPMENT
Smart machines can provide manufacturers with invaluable real-time insights into shop floor productivity, inventory, and potential quality and maintenance issues. For some companies, however, buying new
machinery to harness the Internet of Things (IoT) may be hard to justify. An effective option to IoT success is to add sensors to existing equipment and start capturing real-time data at a fraction of the cost. Lynn Loughmiller, software engineering manager at DELMIAWorks, comments
A
dding sensors to existing equipment is an effective and cost effective way to harness the potential of the Internet of Things (IoT).
A number of sensors are available that support different types of data collection, enabling manufacturers to track metrics related to productivity, consumption, wear and other factors. Five commonly used sensors are: • A proximity sensor is used for counting. One sensor may capture each part produced. Another may track the feet of material going into the machine. Comparing those two measures can help to understand scrap and percentage of loss.
• Amperage and pressure sensors work similarly. Amperage sensors can measure machine speed and force of tooling. Pressure sensors capture similar information for hydraulic-based machines. Having a standard base of amperages and pressures for each part can determine proper setup, tooling expectations, and machine norms. Meanwhile, variations from base measurements can indicate issues affecting part quality or equipment maintenance.
•A vibration sensor measures the amount and frequency of vibration in a machine or equipment. Those measurements can help detect imbalances and other issues to predict maintenance needs. Additionally, a vibration base measurement can provide a machine signature for good parts and a healthy machine.
• A flow meter can be added to a device to track whether it is applying the necessary amount of lubricant to the material, which
can impact product quality.
CAPTURING SENSOR DATA IN SOFTWARE Data from sensors is captured by a programmable logic controller (PLC) or a data logger. The device can then convert the data to a usable computer format and make it accessible to the shop floor network. Newer smart IoT sensors can be made directly available to the shop floor network without intermediary devices. Once accessible to the network, the information is usually sent to a server that supports the Open Platform Communications (OPC) standard for industrial communications. The 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 enterprise resource planning (ERP) and/or manufacturing execution system (MES) software to populate various real-time reports with the data. Both current and historical data are maintained in the software, making it possible to analyse this information from the perspective of quality, efficiency and other key metrics. Manufacturers typically use data captured by the software to: • Collect information for end-of-shift reporting to help determine if the material is equal to the number of parts that the team anticipates producing.
• Track counts in a work centre to assist in production planning.
• Match the work order to what’s running in the 48 DESIGN SOLUTIONS NOVEMBER 2024
machine to update inventory consumption. • Compare how many cycles have been completed versus parts made to understand the scrap being produced.
• Determine downtimes for each work centre. • Look for out-of-limit processes for quality control.
HARNESSING REAL-TIME MONITORING The most powerful use of sensors comes from combining the real-time data they generate with real-time production and process monitoring functionality that is integrated with the MES and ERP systems. Real-time production monitoring helps bring meaning to the counts from sensors by capturing production cycles that can take mere milliseconds and displaying averages, such as X amount of product per minute. Counts in ERP and MES software also support automated workflows, such as materials orders, inventory updates, production scheduling, and other shop floor and accounting processes. When combined with statistical analysis,
real-time production and process monitoring can help establish parameters for performance, wear, etc., as well as track and flag when production cycles and processes measured by machine sensors head outside an acceptable range. The data can be used by an MES for scheduling production, ensuring quality, and performing preventative maintenance, among other processes. The metrics or key performance indicators
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