Cannon Afros, a company of Cannon Group, which specializes in mixing equipment and dosing systems for polyurethanes and urethane elastomers, has developed and introduced OptiWise, a proprietary predictive maintenance system implementing industry 4.0 and Internet of Things (IoT) functions for the optimal operation of mixing heads and pumps, facilitating the optimal performance of foaming machines.

Predictive maintenance is a method that leverages condition-monitoring tools and techniques to determine the performance of a piece, or pieces of equipment while operating and contributing to a manufacturing process. An essential component necessary to implementing predictive maintenance is data collection which, when processed over time, helps differentiate what is normal and what could lead to a malfunction. The collected information is used to set up a machine learning algorithm that can detect anomalies, classify the faults, and thereby predict the condition of in-service equipment, or part of, to estimate when intervention is necessary.

“Cannon Afros is dedicated to continuous innovation and had already begun equipping PU foaming machines with data logging systems well before adding Industry 4.0 and IoT functions in 2017 when we launched the project focusing on predictive maintenance,” said Stefano Andreolli, Automotive Sales Manager at Cannon Afros. “Mixing heads and pumps are the most critical pieces of equipment for PU foaming machines and their failure can abruptly bring the production process to a halt, with costly results. The aims of OptiWise are to accurately detect and pinpoint potentially serious problems before indicators appear, so that maintenance can be scheduled just at the right time.”

In 2019, Cannon began developing its “Talking Head” – a patented high pressure mixing head reconfigured to accommodate more than a dozen of sensors to monitor status and performance during its life cycle. More recently, in 2021, Cannon pulled together a team of technicians, including data analysts, to probe and monitor the mixing heads and pumps’ critical parameters using continuous and periodic measurements, remotely via the cloud. With numerous machines connected to the cloud the learning model is continuously fine-tuned due to the voluminous data stream which renders the predictive maintenance algorithm wiser.

According to Cannon, all of its authorized customers can access OptiWise anytime, anywhere with an array of devices and via a simple dashboard can monitor how the dosing machine or machines are performing in real-time alerting them of any trending anomaly.

www.cannon.com

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