The digital twin and digital thread are both slowly becoming part of the manufacturing technology ecosystem. However, while the digital twin already has use cases, the digital thread is more of a goal than a reality today.
The digital twin is a digital representation or model of a product, process, or system that mirrors a company's machines, controls, workflows, or systems. Its value is its ability to take real-world data about an object or process as inputs and produce outputs that are predications or simulations of how the object or process will be affected by those inputs.
Digital twins therefore enable performance testing to provide information and data about any potential problems before end products are physically produced – also known as virtual commissioning. This enables engineers to diagnose operational, design, and other problems and test proposed repairs or maintenance before applying it to the physical twin.
Building a digital twin is complex, and there are currently no standardized platforms in the market. Commercial products have been developed by some of the largest companies in the field, however, including GE, Siemens, and IBM.
The Digital Thread
The digital thread can be defined as the communication network or framework that connects all assets in a manufacturing process in an integrated, seamless flow of data across the value chain and links every phase of a product life cycle – from design, sourcing, testing, and production to distribution, point of sale, operation, and service – providing a single reference point for design, engineering, and manufacturing.
Because manufacturers are challenged with managing complex and far-flung supply networks, there is great value to be captured from an integrated digital thread linking every part of a network; a single product may have hundreds of individual components or assemblies sourced from dozens of suppliers. A fully integrated digital thread is a goal more than a reality for manufacturers today, however.
Standardizing and integrating all the disparate sources and types of data in a typical manufacturing plant is enormous. There many distinct types of equipment — lathes, mills, plastic injection molding, AM, laser cutters, robotics, etc. — and depending on the mechanisms available for acquiring data from those systems, the data points can be very diverse. Data points can even differ by the family, make, and model of the machine using the control as well as the version of the software running on that control.
Data gaps are therefore the key challenge to the digital thread because any gaps undermine the integration of the thread. Each manufacturer will face its own set of hurdles in terms of data standardization and integration given its specific equipment and processes. This will be a challenge for both technology and software providers as well as manufacturers.
Read AMT’s full white paper on the digital twin and digital thread here.