Machine Learning for Maintenance Plans

With manufacturers and OEM’s delivering new equipment with advanced machine learning algorithms, why not take advantage of this in your SAP system. Assuming you have the “health factors,” or quantitative indicators to drive your maintenance plan, we have the “Maintenance plan” ready to receive your best prediction. We take your prediction determined through the relationship to usage, failure risk and any other training or dynamical decision rules being adopted, and trigger the work order on exactly the day you determined.

Or with advanced sensor and measuring equipment, you can predict equipment failures by analysing vibration and temperature sensor data, allowing proactive intervention to prevent costly downtime. Just send through your request, and the solution will automatically schedule the maintenance for you, automatically cascading all other scheduled maintenance into the future.

Traditional preventive maintenance, despite its good intentions, often misses the mark. Fixed (calendar based) maintenance schedules can be inflexible, leading to excessive maintenance that paradoxically increases downtime rather than reducing it. Predicting the most intense maintenance periods in advance is challenging, causing companies to face machine downtime during peak production requirements. Fortunately, predictive maintenance offers a more efficient and effective solution.

The limitations of fixed-schedule maintenance are clear. According to research by the ARC Advisory Group:

• up to 50% of maintenance funds allocated to predetermined schedules are wasted. Moreover, only 18% of equipment failures are related to age or use, while a staggering 82% occur randomly.

This contradicts the traditional belief that more frequent inspections result in less downtime.

Predictive maintenance uses data and advanced analytics to predict when equipment is likely to fail, allowing for maintenance to be performed just in time. This not only reduces unnecessary maintenance activities but also minimises unexpected downtime, improving overall efficiency and productivity. Embracing predictive maintenance can revolutionize your operations, saving time, money, and resources while enhancing operational reliability.