Open AccessDPART – A DIGITAL TWIN FRAMEWORK FOR THE MACHINING DOMAIN
Author(s) -
Philipp Ganser,
Tommy Venek,
Viktor Rudel,
Thomas Bergs
Publication year - 2021
Publication title -
mm science journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.195
H-Index - 10
eISSN - 1805-0476
pISSN - 1803-1269
DOI - 10.17973/mmsj.2021_11_2021168
Subject(s) - enabling , key (lock) , computer science , domain (mathematical analysis) , process (computing) , machining , manufacturing engineering , realization (probability) , digital manufacturing , industrial internet , digital transformation , turbofan , internet of things , engineering , mechanical engineering , embedded system , world wide web , computer security , automotive engineering , operating system , mathematics , psychotherapist , psychology , mathematical analysis , statistics
Todays’ heterogeneous manufacturing environments and isolated manufacturing elements hinder the realization of a complete and data consistent digital twin. Against this background, an increased connectivity based on the Industrial Internet of Things (IIoT) might be the future key enabler for the digital twin. However, it requires each domain to transfer, rearrange and rethink their individual data solutions in a framework that is IIoT-ready. This paper presents an IIoT-based implementation of a digital twin framework for machining, enabling the creation of a complete and data consistent digital twin throughout process planning, manufacturing and quality assurance. Different use cases are introduced based on the example of a blade integrated disk for modern turbofan engines.