"Our 'engineers in a box' continuously watch over your installations, send out alarms when things tend to go wrong and provide periodic reports indicating the present state and what preventive repair is required: the ultimate tool for risk reduction and maintenance optimisation!"
What are the stages
Hardware & other Data sources
Deriving valuable insights from a monitoring system starts from the data: identifying and locating the relevant data in existing databases or putting the right sensors on the right position and reading them out in the optimal way.
Installation & Commissioning
Push the button of Industry 4.0 by connecting to all relevant existing sources and installing the sensors + acquisition system onto your asset.
Continuously structuring, verifying and cleaning the incoming streams is an essential prerequisite to allow for a reliable and complete data pool, essential for a profound analysis process.
Analysis & Clear Reporting
Advanced insights are unlocked using algorithms based on physics as well as big data approaches. Surprises are avoided, standstills reduced.
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Often the most basic statistics are available but not visualised to key stakeholder, hindering them to make better informed decisions.
Using API connections from nearby weather stations, you can see what your outdoor asset is being influenced by.
How far has your asset traveled?
In combination with your operational data, monitor the activity of your asset by knowing how far it has traveled, with or without load, and track the evolution over time.
See the past and present events, related to specific types of parameters, which can help you plan and predict the next intervention.
All calculated automatically & continuously by our Virtual Engineers
Machine or installation health
Knowing that your machine is going to fail is essential. Our monitoring tools collect data all the time and our algorithms translate it into insights and predictions related to their state-of-health. When things threaten to go wrong, you receive a warning
We are not just looking at past failures and component failure catalogs. We are monitoring the actual data coming out of the actual installation or machine and translate this into predictions using physics, domain knowledge and a bit of AI where relevant.
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.
Factory information systems
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.