Industry 4.0 Solutions

Quill’s comprehensive condition monitoring solution provides visibility and insights into machine utilisation and performance, regardless of location, helping producers of all types to maximise their yield by improving overall equipment effectiveness, extending the lifetime of critical machinery and reducing their maintenance and servicing costs.

What we do

Utilising the latest Internet of Things technologies combined with the power of cloud computing, Quill's connected factory solution collects and analyses important machine data such as vibration, temperature, torque, pressure, run time, power consumption and much more, providing users with a consolidated view of all machine data, via a web or mobile interface.

Real-time condition monitoring for critical production environments.

Why choose Quill

Quill's open architecture allows it to integrate with multiple data sources and third-party devices, making it suitable for almost any environment and allowing customers to leverage their existing investments by complementing these with Quill's rich insights to increase efficiency and productivity.


Quill enhances production operations by providing real-time visibility, dynamic alerting and actionable insights allowing plant managers to identify and resolve production line issues quickly.

Failure Prediction
& Service Optimization

Through predictive analytics and machine learning, Quill detects trends and anticipates impeding problems, optimising machine utilization by enabling preventative maintenance activities to be scheduled timeously.

Proactive Management

Working wth experts in the specific field of application, we are able to encapsulate expert knowledge to alerts customers when key metrics stray out of acceptable bounds.

Manage your risks and take control

Without the visibility and insights provided by Quill, your business is exposed to various downtime risks, all of which can negatively impact your bottom line:
Unplanned production downtime due to unforeseen machine outages.
Reputational damage due to missed deadlines.
Wastage and spoilt goods due to interrupted production runs.
Equipment damage caused by operator misuse.
Inefficient maintenance programs (under or over-servicing) due to lack of machine health insight.
High cost to repair and time to repair.
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