Predictive Equipment Maintenance Trends

Unscheduled equipment downtime costs the industry $ 50 billion annually, according to research by Deloitte. To reduce the risk of unexpected breakdowns, companies are implementing predictive equipment maintenance algorithms.

Trend № 1. Application of thermography methods

Excessive heat can be an early sign of equipment damage or malfunction. The use of thermographic methods for non-destructive testing of equipment allows infrared scanners to detect deterioration and overheating of equipment, which usually goes unnoticed by visual inspection.

Regular equipment temperature checks can help companies save money on unforeseen equipment maintenance and repair costs. In addition, monitoring equipment temperature over time can detect potential failures and prevent unplanned downtime.

For example, a thermal imager allows you to display on the screen a picture of the distribution of the temperature fields of an object, which will help to find emergency elements even before they fail, carry out non-destructive testing and find equipment defects.

Trend № 2. Implementation of Plug And Play technology into equipment

Many companies still operate outdated equipment to solve their business processes, but modern automation requirements dictate the need to obtain states and data in real time, which in most cases is not implemented in outdated equipment. Plug and Play solutions have appeared on the market that start working immediately after power is applied and do not require complex configuration. These solutions provide real-time data on equipment health and alert engineers of potential problems.

Trend № 3. Predictive Maintenance as a Service

The trend of offering predictive maintenance as a service is gaining popularity. Equipment manufacturers can collect real-time machine health data from their customers, build a digital model based on this data, and then provide customers with customized service recommendations for a specific device. This service will enable customers to detect early signs of equipment failure and create an optimal maintenance schedule.