DIGICOGS: DIGital Twins for Industrial COGnitive Systems through Industry 4.0 and Artificial Intelligence
| Reference number | |
| Coordinator | Mälardalens Universitet - Akademin för innovation, design och teknik, Västerås |
| Funding from Vinnova | SEK 4 998 388 |
| Project duration | April 2020 - November 2023 |
| Status | Completed |
| Venture | Strategic innovation programme for process industrial IT and automation – PiiA |
| Call | PiiA: Digitalization of industrial value chains, autumn 2019 |
Important results from the project
The objective of DIGICOGS is to provide a digital twin that combines sensor information, AI and machine learning and big data analytics that underpin the new wave of the cognitive system.
Expected long term effects
Developed a DT for PTU manufacturing which is tested in industrial settings and provide good results to analyse the impact of materials on pinion and ring gear. Classification and prediction algorithms are developed for machine chip classification and chip-type prediction in control processes. There are several results have been achieved such as a report on ‘use-case, state of the art and survey analysis’; a survey paper on ‘Machine Learning Based Digital Twin in Manufacturing’; ‘Heuristic Approach for Cognitive Digital Twin Technology A Technical Report’.
Approach and implementation
För att uppnå målet överväger digicogs 4 arbetspaket WP1: Krav och industriella fallspecifikationer för digitala tvilling- och kognitiva system; WP2: Digital representation av verkliga tillgångar genom dataficering; WP3: Datautvinning och kunskapsupptäckt i digital tvilling; och WP4: Lärande och resonemang i prediktiv modellering för industriella kognitiva system. Resultaten presenterades i 6 tidskrifter, 8 konferensbidrag och en teknisk rapport.( http://www.es.mdu.se/publications?scope=id_project_549)