Tesla technologies for all manufacturing SMEs: explore the digital twin enablers

Read this article by our ambassador Marjorie Grassler

Change2Twin has just published a new position paper, “Enabling technologies for digital twins in manufacturing” to help manufacturers better understand the available technologies and their purposes.

Remember the first time you got inside a Tesla car? Before asking where the gear lever is, your eyes get instantly absorbed by the big screen showing where you are and, most importantly, what surrounds you. The first sensation is peacefulness, no excess just optimization. The inside of the car is simple, but beyond that simplicity, technologies are all over. Sensors collect reel time data to feed the digital simulation of the vehicle and prevent repairs and maintenance from happening. By using Digital twin technologies, Tesla company owner, Elon Musk has overcome one of the main barriers to adopting digital twins in the industry: the lack of understanding of the opportunities that recent technological developments provide.

5 examples of Digital Twin enabling technologies

The evolution of a technology can led to the deployment of another one. Here are 5 examples of Digital Twin enabling technologies:

  • Computer aided design (CAD) and image processing

Did you know that the first digital modelling was a Boeing 777 in the 1980’s? The evolution of CAD has meant a lot for Digital twins’ technology. According to the recent Change2Twin report many SMEs already have models of their products available in one form or another, which can be an ideal starting point for their digital twins: “3D models used in digital twins are often created during the design stage in a product development process and are created using computer aided design (CAD) software”.

  • Artificial intelligence

The Tesla car example, presented in the introduction, helps to understand the fundamental need to collect data and to use the power of artificial intelligence to improve the car: “In digital twinning, the main aims behind artificial intelligence are to embed expert knowledge in the digital twin, and to extract knowledge from the sensor data collected at the physical twin”. In the specific case of autonomous cars, it is crucial to guarantee the security of vehicle data transmission and to implement load-balancing scheduling for data transmission resources when considering safe driving of autonomous cars issue.

  • Cloud computing

Cloud computing is one of the key technologies that makes it possible to process data in a big data context as reported by Change2Twin position paper:

“One of the key benefits of cloud computing is that it offers flexible scalability of compute resources without SMEs having to invest in their own infrastructure, which can be useful considering the different computational requirements at different stages of digital twin implementations”.

“Enabling technologies for digital twins in manufacturing” – Change2Twin position paper

SMEs can benefit from lower costs, better profitability and faster time to market.

  • Low-code development platforms

Low-code platforms are types of visual software development environments that help to deliver digital transformative solutions faster by reducing the amount of coding. The Change2Twin report points out that it enlarges the access to a wide range of users: “This means that a wider range of stakeholders can make use of the digital twin, and it can be used for a wider range of purposes than initially envisioned.”

  • Blockchain

Blockchain is not only for cryptocurrencies. Manufacturing companies can also leverage the technology enhancing digital twin platform security and ensuring privacy. The position paper identifies those elements as fundamental for the Digital twin environment: “Blockchains provide a permanent decentralized historical record of information that is secure, traceable, and transparent; all of which are important in the digital twin context”.  

Enabling technologies for digital twins in manufacturing

In the new Change2Twin paper, Oliver Barrowclough, researcher in SINTEF Digital, explores the barriers for implementation of digital twins:

“We decided to extract the most important findings and offer them to smaller manufacturing companies, which see the need of a digital twin in their businesses but do not know exactly where to start.”

Oliver Barrowclough, researcher in SINTEF Digital and author of the paper “Enabling technologies for digital twins in manufacturing”

The paper goes through five basic technology categories: Geometric and physics-based modelling, Data-driven modelling & big data cybernetics, Infrastructure and platforms, Human-machine interface and Data management. The purpose was to focus on technologies which are most likely to be applied in the manufacturing branch.

At the end it also presents the growing Change2Twin technology and solution marketplace. In the previous position paper Change2Twin explored the barriers for implementation of digital twins. You can download the position paper “Enabling technologies for digital twins in manufacturing” from our website here.

Article by Change2Twin Ambassador Marjorie Grassler