Dr Petros Papapanagiotou

Senior Scala Engineer



Digitizing Industrial Workflow, Monitoring and Optimization

Digiflow is an Industry 4.0 project funded by EIT Digital. It focuses on the digitization, monitoring, and optimization of industrial workflows, with a combination of IoT sensors, Cloud infrastructure and our workflow technologies.

A slide deck with some of the aspects and outputs of the project for 2018 can be found HERE

We are working on a unique solution to enable manufacturing companies to better monitor their floors and provide decision support towards efficiency optimisation:

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The project involves the following partners:

For our part, as the WorkflowFM team, we provide our technology and expertise in workflow modelling, simulation, and analytics. More specifically, we are working on the following goals:

  1. Modelling and digitization of manufacturing workflows: This is primarily a process modelling activity with data collected from real manufacturing scenarios.
  2. Integration with IoT sensors: We are working towards workflow-based modelling by translating sensed movement data to workflow actions.
  3. Deployment on the cloud: This involves improvements in the core WorkflowFM engine to include persistence using Kafka and MongoDB, and accessibility through a RESTful API, in order to integrate with FBK’s and Reply’s infrastructures.
  4. Simulation and decision support: Our simulation tools can help test different scenarios in order to guide the decision making towards the most efficient setup at any given time. Using analytics from real IoT data, we can provide realistic simulations, in depth analytics regarding costs, delays, throughput and other metrics, and develop key insights for performance optimisation.

The WorkflowFM technology, combined with the state-of-the-art platforms of our partners can lead to a unique solution that helps optimise manufacturing workflows. We can provide real-time monitoring, help determine root causes of delays and inefficiencies, improve throughput, and reduce operational costs.