Predictive maintenance techniques have changed over the years. With the increasing usage of AI and machine learning algorithms in predictive maintenance tools, now, businesses can accurately predict maintenance tasks. Advanced equipment such as artificial intelligence and robotics are generating more data than ever before. However, factories’ analytics capabilities have not caught up to this. Manufacturing companies discard 98% of all the data they can collect because they do not have the operational analytics capabilities to integrate that data into their operations.
Predictive maintenance is a proactive maintenance strategy that uses condition monitoring tools to detect various deterioration signs, anomalies, and equipment performance issues. Based on those measurements, the organization can run pre-built predictive algorithms to estimate when a piece of equipment might fail so that maintenance work can be performed just before that happens. Predictive maintenance can help to optimize the usage of organization’s maintenance resources. By knowing when a certain part will fail, maintenance managers can schedule maintenance work only when it is actually needed, simultaneously avoiding excessive maintenance and preventing unexpected equipment breakdown.
WHY YOU SHOULD ATTEND?
This Virtual Instructor-Led Training is designed based on ISO 17359:2011 Condition monitoring and diagnostics of machines. This training will help participants to understand the benefits and opportunity of applying PdM back in their organisation. Participants will also learn various range of equipment and PdM technique being used across industries. Case studies and example included in this training will bring to life the methods and components that will be discussed and dissected over the two days.
