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MASTA is involved in multiple European innovations programs to bring our customers products backed up by state-of-the-art concepts and technologies.

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Advance Predictive Maintenance

The APEMAN project develops a distributed edge-cloud Digital Twin model applicable to predictive maintenance of machines on the shopfloor. An edge device –  Integrated Sensing and Analysis Box (ISAB) is able to collect and analyse data using deep neural network models in order to monitor the machines and predict their failures. The ISABs deployed in a single installation analyse the data locally in real time and transfer it to the cloud to retrain and adapt the Digital Twin models according to the incoming data and events annotated by the operators. The system is based on the Apache tool chain of the MIDIH architecture and uses both levels of data processing – the Data-in-Motion is responsible for real-time analysis of incoming data directly on the edge devices, whereas the Data-at-Rest layer is used to validate and retrain the real-time models.

EFPF ExtraCash
Execution Tracking and Capacity Sharing

ExtraCash develop a solution supporting lot-size-one manufacturers in getting near real time insights into their production schedule and helping them to expose the order status, production capacity and machines capabilities to their existing and future customers. The solution is cloud-based with web-app deeply embedded in the EFPF framework and offered via the EFPF marketplace.


Capability- and Capacity- based Supplier and Customer Matching

CaCaMat facilitates matching of Fabrication-as a-Service providers in the metal industry with their customers requiring custom-made parts. Matching will make sure that the potential supplier has both the technological capability and capacity to deliver in minimal time. To this goal CaCaMat develops a semantic model describing the fabrication operations, capabilities of the machines and scheduling operations as well as three applications – intuitive creator of custom bent elements; suppliers side application for exposing the capabilities of the machine park, validating the design, and scheduling the production; and intermediary application matching suppliers with the customer. All the applications integrate with and communicate via the Market4.0 platform.


Material Transformation Tracking for Reduced Stress on Shopfloor

The project concentrates on improving well being of workers on the shop floor who need to deal with raw materials management. Our solution automates decision making on which material to take, how much materials to take not to overburden the worker and where to place materials remained after processing.


Product-Oriented Inline Quality Control for Maximum Efficiency and No Waste

Quality check is a main interest of PIQ-ME-NOW. We develop a solution in which the quality control results influence the manufacturers production schedules in real time, leading to improvements in effectiveness of the raw material consumption and number of defects.


Human Oriented Planning and Execution FOR Efficient MANufacturing

In the project we try to address hopes of the shop floor workers: hope for doing tasks which they have skills for, which match their preferences, are attractive to them and include individualized instructions.


Product-Oriented Energy and resources Tracking FOR Production Optimization
and Equipment Maintenance

The project addresses the Circular Manufacturing concept, in particular energy usage tracking, scrap tracking and reuse, as well as anomaly detection for predictive maintenance of the machines.


Single product Instance Shopfloor Traceability for Employee Reassurance and Support

Project SISTERS focus on improving the wellbeing of shop floor workers by introducing a traceability of products.


AI Manufacturing technologist ASSISTant for highly variable lot-size-one production

Our goal in this project is to facilitate a production technology input to the MOM system with use of the artificial intelligence.

EU Projects: Projects
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