Many companies are building digital twins as a way to plan complex changes. However, research from Semmtech shows that a digital twin is only as good as its underlying data foundation.
Digital twins are virtual replicas of physical assets and systems that help model, simulate, monitor, analyze, and continuously optimize the physical world. As the external environment, customer preferences, and regulations evolve, digital twins can help companies build predictive models that can quickly track the evolution of changes to meet these demands.
Driven by advances in technology, the use of digital twins is becoming increasingly common in all sectors of industry, from engineering and construction to urban planning and even aerospace and defense.
However, creating a digital twin comes with challenges. First, you need accurate and insightful data that understands the physical limitations of your assets and how users interact with them. From there, you can use digital twins to explore the impact of transforming those assets.
“The challenge is that data is often stored all over the place,” warns Semmtech consultant Bram Bazuin. “Otherwise, the correct information will be spread across multiple applications, making it difficult to answer important questions that require data combinations. Large amounts of scattered information can be overwhelming and unproductive. There is a gender.”
Aiming for interoperability
Semmtech is an expert in helping you succeed with your digital twin. The company has a track record of integrating information through open standards and building the data foundation for digital twins.
Based on the company’s experience, Semmtech has determined that one of the main risks of digital twin projects is their reliance on specialized software applications that each contain a specific piece of asset information. The result is often multiple fragmented representations of a single asset.
“Creating the best digital twin of a physical asset requires connecting all relevant applications and real-world asset information,” says Bazuin. “Technical compatibility is required. These systems must be able to process the same data formats and store or reference information from other applications.”
According to Bazuin, the ability to reliably create interoperable digital twins depends on three things. First, all involved stakeholders must have a common understanding of the concept. They must also bridge any conflicts between what the client wants and what the contractor prefers to ensure compliance with project specifications.
Second, relevant technical capabilities must be enabled to integrate the diverse partial representations into a coherent digital model. For example, you can link real-world sensor measurements to specific stone blocks in a 3D model. Finally, whatever application you use, you need to be able to easily share asset information with external organizations and enable seamless updates.
advantage
With the right mechanisms in place to capture and deliver data to an enterprise’s digital twin, enterprises can benefit from guaranteed accurate results. According to Buzzin, this includes “better understanding and management of physical assets, increasing efficiency and enabling informed decision-making.”
At the same time, the insights gained from digital twins can be monetized for other market operators looking to see how similar changes to their assets take shape. “has the potential to generate new revenue streams.”
Yet, accounting for outdated, scattered, or meaningless asset information within an organization can waste valuable time and resources. In this case, reaching out to a partner who can help you leverage easy-to-use tools that address your evolving asset information requirements can help ensure future success.
Semmtech is one such partner and frequently works to help enterprises adopt data-driven twinning. In particular, the company offers “comprehensive services ranging from enterprise IT strategy and domain-specific consulting to end-to-end implementation,” Buzzin concludes.
Buzzin himself is a well-known figure in the world of digital twins of physical assets. Specifically, he leads the Building Digital Twin Association’s Ontology and Interoperability Working Group.
