Condition monitoring solution mitigates risks

22nd May 2020 By: Darren Parker - Creamer Media Contributing Editor Online

Manufacturers are exposed to various operational risks relating to the performance of their critical production equipment, all of which can directly impact the bottom line.

To help manufacturers mitigate these risks, software developer Quill has developed a dynamic, real-time condition monitoring solution that combines the latest industrial Internet of Things (IoT) technologies with the power of cloud computing.

Some of risks include unplanned production downtime caused by unforeseen machine outages, reputational damage because of missed deadlines, wastage and spoiled goods because of interrupted production runs, as well as inefficient maintenance programmes caused by insufficient machine health insight.

The latter, along with the risk of equipment damage caused by operator misuse, have the associated challenges of high costs of repair, and time lost.

The Quill condition monitoring solution aims to help users manage operational risks and maximise production uptime, while optimising preventative maintenance of critical factory equipment.

Using statistical analysis and machine learning from volumes of accumulated machine data, Quill can predict equipment failure before it happens, identifying the root cause with confidence.

The company states that its comprehensive, “cost-effective” condition monitoring solution is useful for manufacturers of all sizes.

It collects and analyses machine data, providing the clients with real-time visibility, dynamic alerting and actionable insights into machine health and performance, which enables them to take preventative action before production is impacted.

The customisable Quill dashboarding tools provide users with the ability to track multiple metrics over any period of time – such as vibration, temperature, torque, run time, power consumption – to detect trends, anticipate impending problems and proactively schedule maintenance activities in good time.