Development of an industrial cyber-physical platform for small series production using digital twins

Author:

Yablochnikov Eugeny I.1,Chukichev Artemiy V.1ORCID,Timofeeva Olga S.1,Abyshev Oman A.1,Abaev Grigory E.2,Colombo Armando W.3

Affiliation:

1. Faculty of Control Systems and Robotics, ITMO University, Kronverksky Pr. 49, bldg. A, Saint Petersburg 197101, Russia

2. PLM department, Bee Pitron SP, Ltd., Vilenskiy pereulok 4, Saint Petersburg 191014, Russia

3. Faculty of Technology, University of Applied Sciences Emden/Leer, Constantiaplatz 4, 26723 Emden, Germany

Abstract

The article describes an industrial cyber-physical platform for small series production using digital twins under development at ITMO University (Saint Petersburg, Russia). The platform is based on the following approaches: group technology, adaptive and selective assembling, and digital twin of production systems and processes. The article presents a mechanism for constructing a unified manufacturing process, and results of an integrated multiscale simulation of an injection moulding process. The issues of ensuring identification and monitoring of objects of the industrial cyber-physical platform are considered. Specific service applications required to implement the smart product concept are discussed. The combination of the considered technologies is used to create digital twins of production system objects. All humans that have different roles in the product value stream can interact with the industrial cyber-physical platform at the three levels, receiving support in performing their tasks. This article is part of the theme issue ‘Towards symbiotic autonomous systems’.

Publisher

The Royal Society

Subject

General Physics and Astronomy,General Engineering,General Mathematics

Reference39 articles.

1. Abdoune F, Nouiri M, Castagna P, Cardin O. 2021 Toward digital twin for cyber physical production systems maintenance: observation framework based on artificial intelligence techniques. In Service oriented, holonic and multi-agent manufacturing systems for industry of the future. SOHOMA 2020. Studies in computational intelligence (eds T Borangiu, D Trentesaux, P Leitão, O Cardin, S Lamouri), vol. 952. Cham: Springer.

2. Digitalized and Harmonized Industrial Production Systems

3. Azaiez S et al. 2016 Towards flexibility in future industrial manufacturing: a global framework for self-organization of production cells. In The 2nd Int. Workshop on Recent Advances on Machine-to-Machine Communication/Procedia Computer Science vol. 83 pp. 1268-1273.

4. Smart products development approaches for Industry 4.0’/Manufacturing Engineering Society International Conference 2017;Lopes NM;Procedia Manuf.,2017

5. Mitrofanov SP, Kulikov DD, Milayev ON, Padun BS. 1987 Technology of flexible production schemes preproduction (Russian: ). St. Petersburg, Russia: Mashinostroenie.

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