Importance of Machine Learning for Maintenance
The world has been using Industry 3.0 methods for continuous monitoring of their assets and act upon failures. The failures that occur in an industry 3.0 solution are not immediate, the failures happen at the last stage of a small anomaly and that is based on multiple factors which occurs over a period time and follows a certain pattern, which is very hard to identify using normal/traditional methods.
With the world changing in to smart ways to do maintenance, the organizations aim at savings which shall pay the cost for the maintenance. Therefore, Industry 3.0 is not sufficient to cater this needs for the savings.
Industry 4.0 and machine learning will help the organization to monitor continuously and predict the performance of an asset by recognizing the patterns for the failures and provide insights to the respective maintenance teams to act on the issue before the failure happens to avoid any loss on the production or operations. Which in turn increases the following benefits:
- Low cost of maintenance and operations
- Reduced Downtime
- 30% decrease in time to resolution
- Reduced energy consumption and much more…
Solving the issues in the field based on the predictions from machine learning is more important than predicting the failures. We would need skilled resources to understand the results from the platforms and solving the issues.
Some of the organizations are at risk, if the skilled resources are not available at the right moment. Prescriptive Maintenance, an advanced technology to provide insights on the failures with the right actions/steps to be carried out in chronological order based on the knowledge base generated over time by experts on solving similar kind of issues. The AI/ML algorithms will identify the right method for the issue and provide the right insights for steps to be followed, tools required, Permit to Work, Health & Safety, etc.
About the Author:
Arvind Dhanapal works with Intertec Systems as a presales consultant for IoT, and is an Expert in consulting, design and architect for IoT, IIoT and Industry 3.0 solutions.