Awarded proposals

45 proposals submitted to the Type-A Open Calls have been evaluated and 10 of them were selected for funding. A total of €966k will be awarded to the winners.

Type-A Open Call at a glance

The KITT4SME Open Call has invited in its first round (Type-A) technical developers to describe solutions that address problems for EU SME manufacturers. The project awards the 1st round Open Call winners with up to €100k (1M€ in total) to align their solutions with the KITT4SME platform specifications and integrate them to the RAMP Marketplace.

The project received the impressive number of 45 high quality submissions which were put to the test by our panels of expert evaluators. Proposals were ranked according to their technical excellence, their perceived impact on the end-users (SME-manufacturers) and the clarity of their integration plans. 10 projects from around the EU have been selected for funding and they have been invited to start their activities from this March of 2022!

The awarded proposals

The top ranked 10 proposals from Italy, Spain, Greece, Slovenia, Germany and Portugal will be awarded with a total of €966k and 3 proposals from Italy and Turkey have been placed in the reserve list.

The selected projects are:

AI4SDW: AI FOR SAFE AND DECENT WORK: is an AI solution for human – machine interaction supported by a smart camera (HW- Box) equipped with the most advanced intelligent embedded system and powered by next generation AI native chip, that allow real time processing, assure privacy preservation and is cyber secure by design.

REORDINIS: Advanced Reconfiguration Optimization for Resource Distribution and Inventory Integration System: addresses the challenge of complex decision-making in production and inventory management. The solution consists of a set of AI technologies, namely simulation & search algorithms and knowledge-based models & queries, which optimize production plan (re)configuration and inventory management decisions to support operators and engineers.

OptiPLANT: Optimised Predictive Maintenance for Manufacturing SMEs through Automated ML: is a cloud-based system that empowers professional and non-professional data scientists to build high-quality predictive models for timely and optimised maintenance of the industrial machinery.

HE.Go.App: Health, safety and ErGonomics for the future human-centric factory, an integrated APPlication for increase factory safety and enhance social sustainability: a cloud-based solution based on a proprietary set of novel Artificial Intelligence-based algorithms able to recognize the workers’ gender, age, posture and movements in real-time from the video captured by every type of RGB cameras and monitor ergonomics to adapt both workspace and workload according to their personal profile, to inform about potential MSDs risks, to provide insights for improving the work environments.

XTREMESTREAM: Embedded machine learning of IoT streams to promote early detection of unsafe environments: proposes the development of an embedded Artificial intelligence solution for the early detection and screening of high-risk conditions in industrial environments, especially for gases emissions, volatile organic compounds and other environmental conditions as vibration, high temperatures and long-term high humidity exposure.

AI4MOS: Artificial Intelligence-based Multi-Objective Scheduling Optimization for Sustainable Manufacturing: aims to explore the integration of existing injection moulding machines and RAILES (Manufacturing Execution  System)  to  extract  data  during  the  process.  This data will then be used to create Artificial Intelligence models capable to optimizing the machine allocation according to the predicted energy and materials consumption.

THANOS: Throughput level controller based on fatigue monitoring and quality standards: aims at allowing manufacturing companies to deliver quality products to market faster than their competitors by delivering an AI-based quality control solution in partially automated production processes, that is where parts of the processes are automated and others are not, so that a strong dependence is found between the operators’ and the machines’ performances.

AIGreenWaste: AI technologies for green waste management: includes a decision support tool for plant operators based on simulations and scenarios developed by cognitive computing and  ML  solutions,  and  developed  using  the  data  from  a  plant  in operation.  

ExtruAI: Recommendation system for extruder steering based on artificial intelligence: focuses on supporting employees on the extrusion line in the food and plastics sector. In the event of quality deviations, the employee should be supported with recommendations for action in order to react quickly and optimally to variances in the process with new process parameters.

CNCSmart: CNCSmart – AI supported machine data acquisition and control: will predict real execution times of CNC part programs for metal-working industry cutting machines. It will use machine  learning  techniques  to analyse CNC  part programs  and  accurately  estimate  execution  times  based  on  historical  data  and  different  cutting parameters, like machine type, material type and thickness, operation and tools handling

Missed the Type-A open calls?

Stay tuned for the Type-B open calls, which will be announced in the second half of 2022! Type-B open calls will invite small teams of technology developers and their respective end-users, to deploy, test and tailor the solution to the end-users’ specific needs. Solutions will again be integrated to the KITT4SME platform and this time the entire flow of data – from shopfloor to AI – will make use of the KITT4SME proposition. New pilot experiments will complement the ones launched by the project to assess the value proposition from the end-user’s perspective.

Follow our webinars to know more as we build towards the launch date (summer of 2022)!


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