MIDIH Open Calls target the development of data driven applications, by IT SMEs as technology providers, and experiments in CPS/IoT by Manufacturing SMEs. Open Calls select new cross-border experiments to be executed and validated in real (additionally to the Lighthouse cases) or realistic (the Teaching Factories) industrial facilities.
The open calls aim at complementing functionalities around MIDIH reference architecture and performing experiments in CPS/IoT based on the components provided by the architecture. The experiments must cover one of the three main scenarios: Smart Factory or Smart Product or Smart Supply chain.
Two Open calls have been launched.
For the Open Call 1 (find more information here), which closed on June 29th 2018, we received 41 proposals submitted by manufacturing SMEs and technology providers from 14 countries. The evaluation process has been completed and 15 proposals were selected for funding. The summary of submitted and selected proposals is available in this report.
Here, the list of the 15 funded proposals can be found, divided by Technological topics which address technologies around the MIDIH architecture and Experimentation topics, having to cover one of the three main scenarios: Smart Factory, Smart Product or Smart Supply Chain.
Open Call 1 winner Experiments
|PeRsOnalised design by manuFactuIng LifEcycle feedback loop||Robot Optimization Platform in Real-Time||Dynaback the tshirt to alleviate back pain|
|Bouma's manufacturing 4.0||Manufacturing Industry Data-Driven Digital twin||3D recognition initiating IoT data for industrial training|
|On-site training of INdustrial workers using AR Technology||A Wearable Expert Augmented Reality System||Multi-tenant Active Deep Monitoring Platform for AVN Trust Management and Optimization|
|Manufacturing optimization with ARtificial INtelligence Advanced planning & scheduling||ENERgy Saving Platform Experimentation in ALuminium Melting Process Industry||Data driven experiment for Energy saving and quaLiTy Assessment|
|Energy Consumption Prediction Based on IoT and CI techniques||Analytics of sensor data of stock taking drones||Distributed Warehouse Management Experiment|