LightMe Impact

The target of the LightMe proposal is to set up and operate a fully sustainable ecosystem related to the upscaling of materials and products of lightweight metal matrix composites. The Ecosystem will be represented by a Non Profit Organization (NPO) that will be founded in Month 20 of the project and will act as the Single Entry Point. The NPO will have the mandate by the members of the Ecosystem to sign contracts. Via an amendment the NPO will be proposed to be a partner of the consortium.
The core partners of the ecosystem have divided the development on the ecosystem in two pillars: Excellence and Sustainability.

Open and upgraded facilities at the EU level … easily accessible to users across different regions of Europe;

LightMe ecosystem will provide open access to industrial partners, including SMEs to PL related to casting, AM and SPS as well as to advance characterization techniques, modelling & simulation software, environmental assessment and consultancy on standardization and regulatory aspects (including nanosafety) for upscaling concepts related to lightweight metal matrix nanocomposites.

Attract a significant number of new SME users;

SMEs play a fundamental role in investment and innovation in Europe. Despite macroeconomic challenges such as weak domestic demand, difficult access to finance and lingering economic uncertainty, they continue to be an essential part of the productive sector.
Besides globalisation, SMEs face a number of other challenges such as increasing digitalisation, rising energy prices and competition from non-European, low labor cost countries, which require sensible investment and innovation strategies. LightMe ecosystem will cover this need offering an open access innovation environment, in which SME will be able to proceed in technological innovation in a fast and low cost way.

At least 15% improved industrial process parameters and 20% faster verification of materials performance for highly promising applications;

Currently the daily production optimization is manually performed based on the experience of the human operators controlling the production process. This is a highly complex task, where a large number of controllable parameters all affect the production in some way and must be adjusted to find the best combination.
The process control systems to be developed within LightMe will overcome this issue, by developing a data driven models based approach, which can largely improve the process efficiency, allowing to find complex, non-linear patterns in data, and transform them into models, which can be applied to fine-tune the process parameters, improving them by at least 20%, while strongly improving the quality of products.

At least 20% improvement in industrial productivity, reliability, environmental performance, durability, and reduction of life-cycle costs of these materials;

Optimization of the production process will be performed via a machine learning based control approach, developing models to link the key process parameters with the final properties, durability and environmental performance of the new materials, thus allowing the identification of the best combination of process parameters able to optimize the characteristics of the materials.
Data driven models based control, combined with fast characterization methods, will allow better error tracking, increase production rate and equipment lifetime, reduce scrap, production and life-cycle costs.

Machine learning has in fact already demonstrated to be able to increase production capacity by 20%, while lowering material consumption rates by 4% and downtime by 20%. The potential impact on the customers of LightMe will be huge, as they will have access to an ecosystem able to maximize the performances of their products, while ensuring high industrial productivity.

At least 15% indirect reduction in energy consumption across sectors using lighter materials in their products and processes

Advanced materials are essential for boosting the fuel economy of modern automobiles while maintaining safety and performance. A 10% reduction in vehicle weight can result in a 6%-8% fuel economy improvement.
Taking as example the automotive industry, the strength of Al sheet panels is approximately same as that of steel body panel, while its density is the 1/3 of steel. Its lower stiffness can be improved with the integration of NPs and thus, main steel parts of cars can by replaced by Al MMnCs. Mg is 33% lighter than Al and 75% lighter than steel. Taking into account the overall mass of an average car, use extended use of Al and Mg nanocomposites can lead to a reduction of ~30% in the mass and consequently to ~20% of energy consumption. Similarly, other important sectors of transportation (aviation and rails) can have significant positive environmental impact.