The ProaSense prototype will be examined and validated in two real use cases, each of them addressing a different application domain and different challenges of the project’s objectives.

Proactive manufacturing

Concerns an automatic production line focused on the development and production of lighting equipment. The company Hella Saturnus, Ljubljana (project partner) produces millions of headlamps and foglamps annually. This use case integrates data provided by hardware sensors (e.g., ambient sensors) and software sensors (e.g., quality assessment tools) and aims to predict potential failures in the production process (e.g., quality problems, scrap rate).

Example: Automatic calibration of a production machine if the ProaSense prototype predicts a potential increase in the scrap rate based on decreasing production quality and untypical noises from a machine.

More in the presentation by Hella (download).

More about ProaSense in Hella Newsletter (download).

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Proactive monitoring services

Will be investigated within the use case of an oil drilling service provider, MH Wirth (project partner), which provides oil field products, systems and services for the entire upstream value chain. The overall objective of this use case is to provide proactive monitoring services in a continuous drilling process. Data sources used within this use case are structured data sources (e.g., vibration, maintenance schedule, temperature, failures ) as well as unstructured sources such as natural language entries concerning productivity of drilling process and failures. Proactivity in this case is demanded as drilling operations are highly sensitive in terms of safety regulations, environmental issues and performance requirements. One of the main challenges within this use case is dealing with the extreme heterogeneity of events as well as the complexity relating to the capabilities required to deal sufficiently with processes and management of change.

Example: Continuous rig optimization, based on historical data collected from multiple wells and real-time data on maintenance and productivity at a specific well operation.

More in the presentation by MHWirth (download).

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