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Product Owner Talks: Digital Twin and the Digital Thread


7 min read

Digital thread vs. digital twin technology ideas is the latest difference makers.

Increasing firm productivity begins with a high-level product review and its operations. External business consultants and in-house management attempt to assess the situation. They try to highlight the crucial areas that impede the effective development of a corporation. This method can’t be very effective because of the lack of quality real-time data and the inventiveness of visualization and analysis techniques.

Digital thread and digital twin are the foundations of a digital transition.

One of the most powerful solutions came in 2002 at a Society of Manufacturing Engineers conference in Troy. Dr. Michael Grieves introduced the “digital twin” concept. The idea unites sensor data, science, artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT).

What is Digital Twin?

The digital twin approach has become popular in recent years. The entire digital twin includes three key components: product, factory, and lifestyle. For example, it contains the whole data created during the original product design, the design bill of materials, the design concept, and the provenance of activities taken during the design process. That’s why using digital threads for design is not as common as using digital twins.

In engineering, digital twin means creating a virtual replica of the physical object of the product.

The new wave of IoT will allow this concept to remain intact during the next few years. According to Gartner research, 24% of enterprises with the Internet of Things (IoT) solutions in production or IoT initiatives use a digital twin prototype or twins. We need to mention that another 42% plan to use twins within the next three years.

The “digital twin” concept means digitalizing the product lifecycle management process. It opens up the exciting potential of digital twin work for advancement in the manufacturing and processing sectors.

What is Digital Thread?

What is a digital thread? A digital thread definition stands for comprehending the data-flow structure across various systems. R&D departments examine data flows and look for ways to help businesses leverage their operations. Maintenance experts predict issues, reduce downtime, improve customer service, manage crowds, and offer security. The three digital threads are twins as a dynamic model is helpful for the company’s maintenance of its connected machines and equipment units.

Companies are expanding their use of the digital twin and digital thread concepts. They start with the improvement of business processes and workflows. First, they consolidate all corporate data in one location: manufacturing processes, supply chains, and data warehouses.

Digital Thread Importance

The product development process is frequently split among walled teams and tools, increasing the risk of delivery delays, bugs, budget overruns, unsuccessful testing, validation, recalls, and other issues. To decrease these risks, end-to-end procedure visibility, which stands for digital thread software, is essential for greater cross-team collaboration and early identification of product management of defects.

To address this, corporations frequently seek to force everyone to use a single software platform, preceding their best-of-breed solutions. This solution is neither feasible nor realistic because a digital thread engineer is (and should continue to be) free to select discipline-specific tools that optimize their digital model and operations.

Digital Twin Architecture

The internal or external R&D team creates digital twins. Depending on the business’s goals, the digital twin concept can be applied directly to a product, process, or system. However, the architectural approach to system twins still consists of the following four steps:

  1. Model creation: The first step of model creation is analyzing the product and defining all its characteristics. Following that, they combine sensors with actual items and cover the process with various IoT devices before manufacturing, storing, distributing to the end user, and exploiting. These elements collect information about sizes, states, colors, and different physical performance criteria. After the data is transferred to the cloud-based platform, it offers the digital twin a wealth of constantly updated data. The model is created based on the input from the sensors. Experts establish a communication protocol to stabilize the interaction between the model and the actual product. The fundamental rule is that the model has bidirectional, real-time communication between the physical and digital processes.
  2. Experiment: At this moment, a business would already have a digital twin ready for experiments. R&D specialists have a list of hypotheses and improvements they want to check. They start by performing different experimental procedures. All the testing results are gathered in the data lake and ready to be processed and analyzed. The data can be processed either on-premises or in the cloud.
  3. Analyze: The next step, and one of the most essential, is analysis. Data scientists generate insights, make recommendations, and guide decision-making. They provide the business with a visual representation of the process. Then they highlight the differences in performance between the digital twin model and the analog physical world in one or more dimensions. Experts state areas that need investigation and alteration.
  4. Act: At this stage, a company should understand the steps needed to improve the product or the process. They have the digital twin with the necessary changes and improvements. C-Level has enough metrics and prediction information to approve the solution. If the advance is approved, the company starts to implement it. Otherwise, R&D teams will continue their investigations.

The digital concept is nourished by the Deming Cycle that the leaders and customers of the market use. Digital thread and digital twin are the basis for constant product and process improvements.

Digital Twins Solution Providers

IT leaders have started to create solutions that simplify the implementation of digital twins. Here are two of the most compelling examples:

  1. Azure Digital Twins. Microsoft believes IoT is the key to corporate transformation, and 88% of firms believe IoT is vital to their success. As a result, they are actively developing Azure Digital Twins as a system that merges cloud, IoT, edge computing, AI, and mixed reality. They simplify combining Azure Virtual Machines, Managed Disks, Azure Cosmos DB, and HockeyApp to get raw data from trials. Azure Databricks and HDInsight allow you to evaluate the data by generating “spatial intelligence” graphs. The solutions are both durable and scalable. Microsoft recognized the importance of IoT and how it can also empower organizations. Since then, it has become one of the leading providers of digital twin solutions for small companies and enterprises.
  2. IBM. There is no need to introduce this multinational information technology company. International Business Machines Corporation was born in the USA and has since spread to over 170 countries worldwide. IBM announced new lab services for Maximo. They want to bring augmented reality (AR) into asset management. They partner with DAQRI, a leading augmented reality vendor for industrial use. The IBM Lab introduces visual and voice features for workforces. They use Natural Language Processing, ML, and AI sets. The deployment is made possible by DAQRI Smart HelmetTM, which allows a company to see its assets in a new light and immediately access essential data.

Digital Twins Cases:

Let us give a few examples of how digital twins help a virtual model of real business success.

  • Kaeser and the modifications to their business model: Using digital twins has enabled Kaeser to migrate from product to service sales. They changed their payment plan from a fixed rate to a fee based on air consumption. Kaeser teams installed their equipment with monitoring devices. It offers real-time data on its condition and performance. The company has cut commodity costs by 30% and onboarded 50% of the significant vendors using digital twins.
  • GE Health Innovation Village: GE is another world-leading company that doesn’t need any extra introduction. General Electric focused on healthcare technology. They opened the Health Innovation Village in Helsinki at the end of 2014. This incubator helps healthcare startups create innovative products and services. They use wireless technologies, sensors, apps, and cloud services. The startups are covering technology innovations that feed into many aspects of healthcare. These aspects are comfort for premature babies, monitoring, and maintaining fitness. Implementation of the GE digital twin solutions has enabled heartbeat, blood pressure, respiration, and other information to be streamed into the cloud. Then the software analyzes it, alerts doctors to anomalies and looming crises, and creates innovation models.

The Future of Digital Twin and Digital Thread

Which one is better? Digital twin vs. digital thread: these digital models offer endless possibilities, independently or together. More opportunities to generate business results will emerge as more industrial businesses use these technologies.

Companies across the world are staying ahead of digital disruption. They use the digital twin and digital thread approaches in their product development. It gives access to real-time feedback and measurement results:

  • The computation power of big data
  • The versatility of the analytics technologies
  • Flexible storage
  • Greater possibilities within the aggregation area
  • Integration with canonical data

It’s imposing, so let’s see where the digital thread, digital twin, and digital representation of other technologies lead.


Why use Digital Thread?

Using digital thread is the best way to limit the risk of poor product outputs while maintaining engineering autonomy and efficiency.

How Digital Twin and Digital Thread Can Help?

Future operational models such as data, income streams, and connections will greatly benefit from digital twins, digital threads, and other technologies.

What is the Benefit of Digital Twin?

The two similar objects are not always identical to digital twins. Digital transformation can help users study or determine the condition of an object by requesting the information, and actions expressed through the digital twin affect its physical counterpart.

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