- What are the risks of an Industry 4.0 solution?
- How is data managed at this moment in time?
- Can the end user manage the velocity, variety, volume and veracity of its current information flow?
- What would happen if this was tripled or quadrupled?
- How does it support integration across the value chain?
One risk is connected with security issues.
But organizing a data storage using the I4.0 principles gives more flexibility and the security part is a price to pay.
We've been developing an approach to design a data management system for measuring forecasting accuracy across many time series and across multiple horizons and forecasting origins. By following the I4.0 principles the following framework has been developed:
Conference Paper Data Formats and Visual Tools for Forecast Evaluation in Cyb...
The framework presented implements the so-called Forecast-value-added (FVA) analysis (see slide 6) while following the principles of interoperability, decentralization, real-time processing, service-orientation, and modularity.
Our general problem definition is given on slides 4-5. The I4.0 principles helped obtain a cross-platform solution for forecasting, which is simple to implement and learn, and fast in operation (applicable in production settings).
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