Data Management Foundation Of Digital Twin

Data Management Foundation Of Digital Twin

Digital Twin is trending. Unless you lived under the rock for the last few years, I’m sure you heard this combination of words – Digital Twin. What is Digital Twin, where it came from and how is this related to PLM?

The definition of Digital Twin is not mature in my view. There are tons of them online. Wikipedia gives you some “formal” idea such as the following. A very abstract and not clear in my view.

A digital twin is a digital replica of a living or non-living physical entity. By bridging the physical and the virtual world, data is transmitted seamlessly allowing the virtual entity to exist simultaneously with the physical entity.

Somewhat better definition from Forbes article

…a digital twin is a virtual model of a process, product or service. This pairing of the virtual and physical worlds allows analysis of data and monitoring of systems to head off problems before they even occur, prevent downtime, develop new opportunities and even plan for the future by using simulations.

I like Forbes’ better because it has the notion of a model and not necessarily connected to the 3D representation of the product and might not have it all (eg. in case of service).

Digital Twin is becoming a powerful term and it looks like manufacturing companies (but not only) are liking it a lot. PLM vendors are not standing aside and we can see a fully blown PLM marketing is re-shaping to absorb new “Digital Twin” name for PLM marketing. And this is something I’m concerned about.

My attention was caught by Jonathan Scott’s article  – How Does One Get Started with PLM and the Digital Twin? Read the article. The following passage raised a number of questions I wanted to bring up.

Product lifecycle management software and Digital Twin modeling have sort of an independent maturity at the moment. PLM has become fairly mature in terms of its core capabilities and what the vendors are offering. The adoption rate is where I think there’s still a huge spectrum and room for growth. And of course, then that relates to the level of maturity of digital tools in the market. Digital Twin is much less mature because it stands on the shoulders of PLM.

In all cases, you need some sort of virtual model on which you can overlay the sensor and performance data that comes back from the field. There is a lot of work being done there not just to figure out how you connect those two data [but how] you marry that with this low-volume data set that is the product record coming from PLM.

The article suggests that Digital Twin is standing on the shoulders of PLM, which as far as I understand means to use existing PLM infrastructure for Digital Twin(s) models. Here are a few thoughts on why it might be not a good idea.

1- PLM is not ready for complex models.

PLM data modeling is focused on engineering data and less ready to manage complex data models. The flexibility of most PLM systems is limited, data schemas are not easy to change, especially when you need to adapt it for different types of models.  

2- SQL data management.

Most of PLM solutions today are using relational SQL databases mostly focused on transactional data and can be sub-optimal to store a variety of data and models needed for Digital Twin. SQL databases might not scale or be sub-optimal for large volumes of modeling data.

3- Limited tenant model to access data from multiple organizations.

Digital Twin requires a variety of data shared between different companies (OEMs, service, customers). A majority of existing PLM systems is a single-tenant and might have a limitation with how access to the information can be organized.

What is my conclusion? In my view, Digital Twin concepts go much beyond data management used in current PLM platforms. Existing PLM platforms (most of them were developed 20+ years ago) can be sub-optimal as a foundation for Digital Twin from different standpoints – SQL database technology, data modeling principles, and tenant organization. Modern cloud data management services can provide a better technological stack, hosted differently and provide enhanced data modeling and logical data organization paradigm to serve as a foundation for Digital Twin. Just my thoughts…

Best, Oleg

Disclaimer: I’m co-founder and CEO of OpenBOM developing cloud-based bill of materials and inventory management tool for manufacturing companies, hardware startups, and supply chain. My opinion can be unintentionally biased.


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