Brisbane, Australia
Predictive Maintenance (PdM) is an advanced maintenance approach that forecasts the probability of equipment failure by utilising machine learning, data analysis, and condition monitoring techniques. AI machine learning maintenance seeks to recognise potential issues early, enabling maintenance to be performed proactively before failures occur, instead of following a predetermined schedule or waiting for equipment to break down.
85 %
Improvement in downtime forecasting accuracy
50 %
Reduction in unplanned machine downtime
55 %
Increase in maintenance staff productivity
40 %
Reduction in maintenance costs
What is AI machine learning predictive maintenance?
AI machine learning predictive maintenance testimonial
“We are pleased to have partnered with the team on this corporate initiative to enable Predictive Maintenance (PdM) and improve operational efficiencies. The results and ROI were executed in a prompt manner and our users are thrilled with the ease of use of the PdM software product” – Aluminium Company
AI machine learning predictive maintenance is your journey to success
Businesses that rely heavily on assets suffer from unscheduled downtime. Your maintenance personnel are less productive because they are putting out fires instead of concentrating on what has to get done, and the consequent lost production cannot be made up.
AI machine learning predictive maintenance can;
- be applied simply to thousands of machines across multiple sites at scale
- support projects of all sizes
- use open APIs for easy integration of key systems, such as SAP, OSI Pi and more
- accelerate digital transformation throughout your organisation.
Predictive Maintenance allows your organisation to maximise resource allocation for growth and efficiency. To increase efficiency, reduce machine downtime, improve sustainability metrics and lower operational maintenance costs across locations and assets.
This powerful software application empowers maintenance staff by providing them with the tools, insights, and resources they need to perform their jobs more effectively, efficiently, and safely.