Periodic Reporting for period 1 - MetaFacturing (Data and METAdata for advanced digitalization of manuFACTURING industrial lines)
Reporting period: 2023-01-01 to 2024-06-30
By leveraging on the integration of different technologies and data elaboration models, metaFacturing will contribute to tackle the following challenges:
1. Advanced manufacturing processes: addressing the ever-changing needs of society and offering the potential of opening new markets
2. Economic sustainability and smart manufacturing: combining high-performance and quality with cost effective productivity, realising reconfigurable, adaptive and evolving factories capable of small-scale production in an economically viable way
3. Digital virtual and resource-efficient factories
4. Customer-focused manufacturing and social sustainability: integrating human skills with technology
5. Environmental sustainability of manufacturing: reducing resource consumption and waste generation
In such industrial context, and focusing on the metal industry, targeting at casting and welding, metaFacturing aims at:
1. Developing a widely applicable digital twin (DT) based process setup and control framework to enable cooperative analysis by process chain stakeholders within the manufacturing processes
2. Developing a data fusion system for production lines, to leverage on the potential of DTs for the resolution of complex problems, integrating different sensors
3. Developing automatic process parameter optimization methods representing the target manufacturing processes (i.e. casting and welding)
4. Creating a material characterization system to extract representative continuum material information for the materials used in the manufacturing
5. Validating the system in realistic conditions, prepare it for market uptake and define the corresponding business model
1. Advanced manufacturing processes: addressing the ever-changing needs of society and offering the potential of opening new markets
2. Economic sustainability and smart manufacturing: combining high-performance and quality with cost effective productivity, realising reconfigurable, adaptive and evolving factories capable of small-scale production in an economically viable way
3. Digital virtual and resource-efficient factories
4. Customer-focused manufacturing and social sustainability: integrating human skills with technology
5. Environmental sustainability of manufacturing: reducing resource consumption and waste generation
In such industrial context, and focusing on the metal industry, targeting at casting and welding, metaFacturing aims at:
1. Developing a widely applicable digital twin (DT) based process setup and control framework to enable cooperative analysis by process chain stakeholders within the manufacturing processes
2. Developing a data fusion system for production lines, to leverage on the potential of DTs for the resolution of complex problems, integrating different sensors
3. Developing automatic process parameter optimization methods representing the target manufacturing processes (i.e. casting and welding)
4. Creating a material characterization system to extract representative continuum material information for the materials used in the manufacturing
5. Validating the system in realistic conditions, prepare it for market uptake and define the corresponding business model
At the current stage of the project, the consortium has identified and outlined the requirements for the developments within the metaFacturing project, divided into operational, functional and usability requirements. Next, the key standards that the metaFacturing framework must adhere to have been identified. Furthermore, the measures for the validation of the project results in the end of the project have been defined, with specific key performance indicators (KPIs) for each use case (UC). For the UC casting two high pressure die casting (HPDC) parts from the actual production at LTH were chosen for the final validation. For the UC welding a vehicle battery housing serves as part for the final validation.
The first phase of the project focuses on data availability, data collection and requirements, as well as setting the baseline for the lab and industrial use cases (welding and casting). As such, no results beyond the state of the art are currently available.