MADEin4 SIGNED
Metrology Advances for Digitized ECS industry 4.0
Total Cost €
0EC-Contrib. €
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0MADEin4 project word cloud
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Project "MADEin4" data sheet
The following table provides information about the project.
| Coordinator |
APPLIED MATERIALS ISRAEL LTD
Organization address contact info |
| Coordinator Country | Israel [IL] |
| Total cost | 127˙491˙472 € |
| EC max contribution | 29˙382˙452 € (23%) |
| Programme |
1. H2020-EU.2.1.1.7. (ECSEL) |
| Code Call | H2020-ECSEL-2018-1-IA-two-stage |
| Funding Scheme | ECSEL-IA |
| Starting year | 2019 |
| Duration (year-month-day) | from 2019-04-01 to 2022-03-31 |
Partnership
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Project objective
The metrology domain (which could be considered as the ‘eyes and ears’ for both R&D&I and production) is a key enabler for productivity enhancements in many industries across the electronic components and system (ECS) value chain and have to be an integral part of any Cyber Physical Systems (CPS) which consist of metrology equipment, virtual metrology or Industrial internet of things (IIoT) sensors, edge and high-performance computing (HPC). The requirements from the metrology is to support ALL process steps toward the final product. However, for any given ECS technology, there is a significant trade-off between the metrology sensitivity, precision and accuracy to its productivity. MADEin4 address this deficiency by focusing on two productivity boosters which are independent from the sensitivity, precision and accuracy requirements: • Productivity booster 1: High throughput, next generation metrology and inspection tools development for the nanoelectronics industry (all nodes down to 5nm). This booster will be developed by the metrology equipment’s manufacturers and demonstrated in an industry 4.0 pilot line at imec and address the ECS equipment, materials and manufacturing major challenges (MASP Chapter 15, major challenges 1 – 3). • Productivity booster 2: CPS development which combines Machine Learning (ML) of design (EDA) and metrology data for predictive diagnostics of the process and tools performances predictive diagnostics of the process and tools performances (predictive yield and tools performance). This booster will be developed and demonstrated in an industry 4.0 pilot line at imec, for the 5nm node, by the EDA, computing and metrology partners (MASP Chapter 15, major challenge 4). The same CPS concept will be demonstrated for the ‘digital industries’ two major challenges of the nanoelectronics (all nodes down to 5nm) and automotive end user’s partners (MASP Chapter 9, major challenges 1and 3).
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The information about "MADEIN4" are provided by the European Opendata Portal: CORDIS opendata.