AI REGIO | Regions and DIHs alliance for AI-driven digital transformation of European Manufacturing SMEs
01-10-2020
-30-09-2023
01-10-2020
-30-09-2023
01-01-2020
-31-12-2023
01-01-2019
-31-07-2022
01-10-2017
-31-03-2021
01-10-2017
-31-03-2021
Z-BRE4K will lead to the optimisation of the performance, avoiding waste due to malfunctioning machinery and increased energy consumption due to the presence of failures. the reduction of the electric costs is extimated by 10%.
The avoidance of defective production and overproduction will lead to a better efficiency in the use of materials.
01-10-2017
-30-09-2020
Production equipment uses a number of process resources to operate such as water, air, lubricants, other. In time maintenance activities wnabled by the SERENA predictive maintenance platfrom and optimising the scheduling of maintenance operations can have a significant impact on the consumption of such resources when the equipment is not in proper working condition.
01-10-2016
-30-09-2020
01-10-2022
-30-09-2026
By accelerating and upscaling the structuring process, the OPTIMAL project will increase the process efficiency and yield, which will allow for “first time right” fabrication of the required structures, lower consumption of resources, waste reduction, lower CO2 emissions, increase of productivity, and cost reduction.
01-01-2015
-31-12-2017
01-01-2015
-01-01-2018
01-10-2016
-31-03-2020
The solution provided byZ-Fact0r reduces the number of scrapped parts at different steps of the production process. The use of just the needed amount of raw materials is thus a consequence of applying Z-Fact0r, but it has manifold repercussions, as there is reduction of wear of equipment and tools by doing it right the first time. It also eliminates the duplication of auxiliary materials needed to produce the parts.
The Z-Fact0r platform, and the intensive monitoring of both product and process that accompanies it, has been key for the reduction of defective manufactured parts at the flute grinding process. Should similar solutions be implemented in the rest of machines at NECO premises with a defective rate reduction of around 25%, some 20.000€ could be saved by NECO yearly in the form of raw materials (outside-diameter-grinded High Speed Steel bars), which would instead require to be recycled. Furthermore, if the cutting angle happens to be wrong, the parts cannot be remanufactured and need to be scrapped.
01-01-2015
-01-01-2018
01-10-2016
-30-09-2019
01-09-2016
-31-08-2019
01-09-2012
-31-08-2016
01-10-2016
-30-09-2019
01-10-2016
-30-09-2019
01-10-2016
-30-09-2020
01-11-2011
-30-04-2015
01-11-2011
-31-10-2014
01-11-2011
-31-10-2014
10-01-2015
-30-09-2018
01-10-2016
-30-09-2019
10-01-2015
-30-09-2018
01-09-2015
-31-10-2019
10-01-2015
-30-09-2018
09-01-2015
-31-08-2018
12-01-2015
-31-05-2019
10-01-2015
-30-09-2018
09-01-2015
-31-08-2018
We will generate Objects closer to their nominal shape and thus less material will be removed by subtractive processes, and reduce energy consumption and indirectly CO2 emission
We will generate Objects closer to their nominal shape and thus less material will be removed by subtractive processes.
CAxMan aim at using less material by offering new shape design methods for efficient design of voids and cavities. CAxMan also address the design of better and leaner support structures (use of less material) based analysis addressing thermal stresses and distortions during the additive process.