TY - JOUR
T1 - On the alleviation of imminent technical and business challenges of long-lasting functional digital twins
AU - Zeb, Akhtar
AU - Kortelainen, Juha
AU - Rantala, Tero
AU - Saunila, Minna
AU - Ukko, Juhani
N1 - This work was supported by the DigiBuzz Research Project, funded by Business Finland1 under grant n:o 4437/31/2019 and the participating organisations.
PY - 2022/10/1
Y1 - 2022/10/1
N2 - In this article, we discuss the technical and business risks associated with long-lasting functional digital twins, and describe different strategies for their alleviation. Functional digital twins are based on physics-based simulation models and are operated alongside the life cycle of their physical counterparts. These simulation-based digital twins are built using a simulation software. The problems with most of the commercial modeling and simulation tools are their black box nature and storing data in protective formats, leading to poor interoperability. Since the digital twins of certain assets need to be operated for a long period, even for several decades, there is a possibility that the computing infrastructure, i.e., the computing hardware and software, may not remain the same throughout the product or system life cycle. The computer hardware and operating systems are usually third-party components with limited choices for their users, whereas the selection of simulation tools is more flexible and the designer can choose from, for example, commercial, open-source, or in-house solutions. To avoid substantial costs or business disruption, the digital twin providers must be able to reproduce the underlying simulation models with up-to-date tools and adopt alternative solutions whenever needed. The findings of the study are presented in the form of propositions throughout the article.
AB - In this article, we discuss the technical and business risks associated with long-lasting functional digital twins, and describe different strategies for their alleviation. Functional digital twins are based on physics-based simulation models and are operated alongside the life cycle of their physical counterparts. These simulation-based digital twins are built using a simulation software. The problems with most of the commercial modeling and simulation tools are their black box nature and storing data in protective formats, leading to poor interoperability. Since the digital twins of certain assets need to be operated for a long period, even for several decades, there is a possibility that the computing infrastructure, i.e., the computing hardware and software, may not remain the same throughout the product or system life cycle. The computer hardware and operating systems are usually third-party components with limited choices for their users, whereas the selection of simulation tools is more flexible and the designer can choose from, for example, commercial, open-source, or in-house solutions. To avoid substantial costs or business disruption, the digital twin providers must be able to reproduce the underlying simulation models with up-to-date tools and adopt alternative solutions whenever needed. The findings of the study are presented in the form of propositions throughout the article.
KW - Business risk
KW - Data model
KW - Digital twin
KW - File format
KW - Modeling
KW - Simulation
KW - Standard
UR - http://www.scopus.com/inward/record.url?scp=85130091276&partnerID=8YFLogxK
U2 - 10.1016/j.compind.2022.103701
DO - 10.1016/j.compind.2022.103701
M3 - Article
SN - 0166-3615
VL - 141
JO - Computers in Industry
JF - Computers in Industry
M1 - 103701
ER -