AI for Predictive Maintenance

The move from Preventive to Predictive Intelligence

Introduction

Internet of Things means that today, every part of a system is capable of collecting and sharing data on how it is operating. Each data point can be measured, collated and analyzed using Machine Learning models, which can predict any aspect of the operation based on the acquired data.

In-depth simulations help understand the effects of missed or late deadlines, and remedial actions can help avert adverse situations. Going forward, Big Data driven analysis, is going to increase in prominence in optimizing processes and, an organization’s drive to grow will depend on this data and how they utilize it.

IoT and Machine Learning enable collection, prediction, and simplified predictive maintenance facilitating the Industry 4.0 revolution.

Predictive Maintenance

Maintaining machinery is cost effective when done timely. Predictive maintenance ensures the work doesn’t happen too soon or too late, optimizing machine run times.

Increase ROI on preventive maintenance by using Machine Learning models fine-tuned to business objectives helping significantly cut costs and business impact as a result of downtime.

What can Predictive Maintenance help you achieve?

Minimal downtime due to faults and breakage

Maintenance planning to curtail warranty costs

Optimize maintenance schedules

Data driven decisions - Upgrade, Repair, Replace

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Poor demand forecasting, unexpected downtimes, and inefficient workplace processes lead to resource wastage, extended production periods, low yields, and squandered revenue. Fixing this issue requires leveraging flexible technologies and adapting to market needs.

If you are looking to understand how your processes can change how you do business,

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