Electricity + Control July 2018

tant. Logged data from sensors and indicator lights installed on machines can help manufacturers cal- culate OEE and identify steps to improve the effi- ciency of their machines, processes, and people. Monitor and track performance When an operator ‘pulls the Andon cord,’ or acti- vates an alert, typically a light or display wired to the machine will only signal a stoppage or problem with the machine. It does not provide much insight into what is happening internally. Operators need to monitor machine slowdowns or disruptions manually and this often means additional man- hours and inefficiencies. IIoT-enabled alerts provide the local machine and remote status of each light module. Remote status indicators from wireless tower lights and other alert systems allow users to log trends in ma- chine uptime and cycle counts. Capturing this data helps plants determine maintenance intervals and make decisions about new machine investments. It also helps manufacturers to identify whether a machine or operator is causing a bottleneck. For example, operators may blame missed production goals on machine downtime, while maintenance personnel point to inefficient workers as the root cause. Plant managers can use real-time data collection to accurately verify whether delays were the result of machine downtime or operator inefficiency. For larger manufacturers with multiple plants, these trends can be transmitted to a central location and compared plant to plant to identify and replicate the successes of the highest-performing plants. Wireless sensor networks also provide ongoing insight into overall machine health. Real-time data feeds indicate abnormalities that may lead to fu- ture breakdowns. In the past, understanding mi- nor performance changes was difficult because technicians needed to perform device-level tests to understand machine health. Condition monitoring for predictive maintenance

Wireless sensor-based systems remove this barrier. For example, manufacturers can track in- creases in machine vibration, which is a key cause of machine maintenance issues. Machine vibration is often related to imbalanced, misaligned, loose, or worn parts. As vibration increases, so can dam- age to the machine. By remotely monitoring different machine com- ponents, plants can detect excess vibration before it causes unplanned downtime. Typical IIoT-en- abled vibration monitoring involves the use of a wireless vibration sensor that acts as a ‘check en- gine light’ for machines by measuring root-mean squared (RMS) velocity. RMS velocity provides the most uniform measurement of vibration over a wide range of machine frequencies. With condition monitoring solutions, such as those offered by Bannon, a machine learning al- gorithm establishes a vibration baseline for the machine. When a machine exceeds its threshold, the wireless temperature and vibration sensor can deliver information to the local user, to a centrally located wireless tower light or to a mobile device via an email or text message. The sensor also can send vibration and temperature data to a wireless logic controller or PLC for collection and analysis. The future of maintenance-related IIoT Remote monitoring capabilities will continue help- ing manufacturers to identify and remedy waste within their facilities. Advancements in integration capabilities will continue to minimise costs and lead times during IIoT implementations. The result: Manufacturers can quickly and easily gather the data needed to identify the root cause of production issues and implement measures to increase efficiencies and prevent future disruptions.

Real-time data feeds indicate abnormalities that may lead to future breakdowns.

Brandon Topham is a Director at RET Automation Controls.

Electricity + Control

JULY 2018

27