Have a continuous idea of availability, automatically as the platform combines different input streams and contextual information.

Based on the data collected and machine-learning based methods for determining the operational condition the performance is calculated.

Whenever values start to deviate, or data streams stop, warnings are sent. This avoids 'black holes' in the insights of the production line or assets.

Coupling to existing databases or using human input fields the product quality is linked to operational process parameters.

The Mean Time Till Failure is tracked continuously, for each asset covered the overall 'disturbance free' operation is displayed.

As events and operating conditions are automatically detected the Mean Time Between Failures is determined continuously, giving a good insight on where optimisation is possible.

Using all parameters cited above the Overall Equipment Effectiveness is determined, a major parameter for optimising asset management strategies and future investments, with a huge cost savings potential.

Such systems are crucial for obtaining operational excellence. When well managed they maximise efficiency and effectiveness. Automated data collection and advanced analysis makes this possible.