Predictive maintenance is based on using the right tools and techniques to measure the key maintenance indicators of an asset. In the following, Hexagon Asset Lifecycle Intelligence presents five of the most common analytical methods for predictive maintenance.

1. vibration analysis: Vibration analysis is carried out on rotating machines that work with kinetic energy and emit a measurable amount of vibration. Sensors are first used to determine a fundamental vibration. Based on the data collected by these sensors, subtle changes can be detected and used to plan upcoming repairs.

2. acoustic monitoring: In acoustic monitoring, sensors are also used to record the noise profile of a machine. An AI is then trained to recognize when sounds deviate from this profile. These sensors are very well tuned to noise and can detect when parts of the machine are loose or not lubricated.

3. infrared spectroscopy: Infrared analysis measures the temperature of equipment and allows problems such as overheating of machinery to be identified, which can lead to equipment degradation and injury to employees. Leaking seals can also contribute to energy loss and higher costs.

4. oil analysis: Oil analysis involves analyzing the lubrication of a machine. Lack of lubrication or loss of its integrity can lead to unplanned breakdowns and excessive downtime for any machine that uses oil. If companies can plan oil changes intelligently, production downtime is reduced to a minimum.

5. machine learning: Machine learning (ML) is an important part of predictive maintenance as it intelligently and automatically recognizes when maintenance is required. AI and ML are involved in most predictive maintenance strategies as they enable the automation of monitoring that previously had to be done manually. With a modern, AI-powered asset management solution, maintenance schedules are adapted to individual assets.

Predictive maintenance can create a major advantage for companies - but only if the right technology is used for the right system. A selection process is therefore essential beforehand to ensure that it really adds value.