Project description
Smart ways to predict quality of manufactured product and processes
Measuring, predicting and controlling the quality of manufactured products, manufacturing processes and gathered data is key to ensuring zero-defect manufacturing – a quality concept of manufacturing with zero defects as well as eliminating any waste associated with defects. The EU-funded InterQ project is using artificial intelligence tools to assure optimised quality in smart factories. Specifically, it will focus on the process, product and data, so that quality can be traced across the supply chain. The project will also use digital twins to predict the final quality of the processes. As regards the reliability of the data collected, this will be checked in real time and based on historical and statistical analysis.
Objective
InterQ project proposes a new generation of digital solutions based on intelligent systems, hybrid digital twins and AI-driven optimization tools to assure the quality in smart factories in a holistic manner, including process, product and data (PPD quality). The broad vision of InterQ project will allow controlling the quality of a smart manufacturing environment in an end-to-end approach by means of a PPD quality hallmark stored in a distributed ledger. The concepts of InterQ will be applied in three high-added value industrial applications.
The main objective of InterQ project is to measure, predict and control the quality of the manufactured products, manufacturing processes and gathered data to assure Zero-Defect-Manufacturing by means of AI-driven tools powered with meaningful and reliable data. The project develops five modules:
1) Thanks to the InterQ PPD quality hallmark, the quality of the process, product and data are interlinked, integrated and time stamped. A hallmark will be created after each stage, and the quality will be traced across the supply chain. A trusted framework will be implemented using distributed ledger (InterQ-TrustedFramework module) to exchange quality information.
2) The InterQ-Process module of the project will obtain more meaningful process data for quality optimization. This data will be obtained using new sensors close to the tool and by AI-driven virtual sensors.
3) The project presents new solutions (InterQ-Product module) to predict the final quality of the processes using digital twins fed by experimental data and new digital sensors to measure the product quality.
4) The reliability of data will be checked in two layers: in real time and based on historical and statistical analysis of the data streams (InterQ-Data module).
5) Finally, InterQ-ZeroDefect module will use the reliable information about the process and product quality to improve the production for Zero-Defect-Manufacturing by means of AI-driven applications.
Fields of science
Keywords
Programme(s)
Funding Scheme
IA - Innovation actionCoordinator
20870 Elgoibar
Spain
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Participants (25)
00144 Roma
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1363 Hovik
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48170 Zamudio-Vizcaya
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Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
48170 Zamudio Vizcaya
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47008 Valladolid
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48170 Zamudio Vizcaya
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78190 Trappes
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20870 Elgoibar
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145 61 Athina
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
031214 Bucuresti
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
87600 Kaufbeuren
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
76275 Ettlingen
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
1811 Luxembourg
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
4020 Linz
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
33030 Camino Al Tagliamento Ud
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
69469 Weinheim
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
54500 Vandoeuvre Les Nancy
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48215 Iurreta
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
38240 Meylan
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
7034 Trondheim
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20600 Eibar Guipuzcoa
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64289 Darmstadt
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48940 Leioa
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4 Dublin
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1111 Budapest
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