Demystifying the Digital Thread and Digital Twin Concepts (Manufacturing Operations Management Talk)

The concepts of the digital thread and digital twin have been spearheaded by the military aircraft industry and their desire to improve the performance of future programs by applying lessons learned through these digital technologies in current and upcoming programs. However, these concepts and technologies are gaining interest beyond the aerospace and defense industry and are converging with the digital manufacturing and cyber-physical system goals of Industrie 4.0 and Smart Manufacturing.

In the Industrie 4.0 roadmap, a cyber-physical system refers to the digital representation of a physical system used to communicate properties and live status to other cyber-physical systems and applications in future smart factories. Smart Manufacturing strives to orchestrate and optimize business, digital and physical processes across smart factories and the entire product value chain. As system architects evaluate these initiatives, it makes sense that these similar digital connectivity goals start converging into a single framework strategy for manufacturing systems.

The digital twin refers to a digital model of a particular asset that includes design specifications and engineering models describing its geometry, materials, components and behavior, but more importantly it also includes the as-built and operational data unique to the specific physical asset which it represents. For example, for an aircraft, the digital twin would be identified to the physical product unit identifier which is referred to as the tail number. The data in the digital twin of an aircraft includes things like tail number specific geometry extracted from aircraft 3D models, aerodynamic models, engineering changes cut in during the production cycle, material properties, inspection, operation and maintenance data, aerodynamic models, and any deviations from the original design specifications approved due to issues and work arounds on the specific product unit.

The digital thread refers to the communication framework that allows a connected data flow and integrated view of the asset’s data throughout its lifecycle across traditionally siloed functional perspectives. The digital thread concept raises the bar for delivering “the right information to the right place at the right time”.

Expected Benefits

The benefits expected from having a digital twin for each product unit include:

Assessment of a system’s current and future capabilities during its lifecycle
Early discovery of system performance deficiencies by simulating results way before physical processes and product are developed
Optimization of operability, manufacturability, inspectability, and sustainability leveraging models and simulations applied during the entire lifecycle of each tail number
Continuous refinement of designs and models through data captured and easily crossed referenced to design details

A Digital Thread is expected have the following benefits for manufacturers:

Improve product quality by avoiding mistakes in manual translations of engineering specifications along the product value chain
Improve the velocity of new product introductions (NPI) and the communication of engineering changes along the product value chain
Increase the efficiency of digitally capturing and analyze data related to product manufacturing
Allow manufacturers to deliver new services to customers along with physical product leveraging the digital data now available on the product

The digital thread should provide a formal framework for controlled interplay of authoritative technical and as-built data with the ability to access, integrate, transform and analyze data from disparate systems throughout the product lifecycle into actionable information. The product lifecycle includes: Design, Procurement, Test & Evaluation, Production, Field Operation, and Sustainment Services. The digital thread and digital twin include as-designed requirements, validation and inspection records, as-built data, as-flown data, and as-maintained data.

As-Is and To-Be Scenarios

The As-Is handover between departments:

Design 3D model thrown over the wall from Product Engineering to Manufacturing Engineering
Manufacturing Engineering creates 2D drawings from 3D models and hands over to Quality and Suppliers
Conformance requirements are thrown over the wall from Quality to Production
The product unit is thrown over the wall from Production to customer and sustainment cycle without any data on the specific unit beyond the original design
Production archives as-built to records for auditing purposes

The desired To-Be scenario with a digital thread:

3D model linked to visuals for production process instructions are created by Product Engineers working together with Manufacturing Engineers
Product characteristics are linked to 3D models and extracted directly out of designs into conformance requirements
Conformance requirements are linked to manufacturing process and inspection instructions
As-built data is delivered by Production along with product unit to customer and available for sustainment services to continue evolving the unit’s data during operation and maintenance services
Product design changes follow the same data flow and automatically update downstream models, references and instructions.

Interesting Use Cases

Today we must take the experts to the physical product unit to help troubleshoot issues where they are found. Tomorrow, with a digital twin, we could have experts in different locations looking at the same digital representation of the actual product unit. The Material Review Board (MRB) processes for nonconformance and deviations could be improved by involving more experts remotely and leveraging simulations to figure out the impact to the overall product performance before rework deviations are approved.

During sustainment services, maintenance technicians can receive direct support with the latest and most accurate information on the state and condition of the equipment. Data from smart connected equipment would be aggregated, analyzed and transformed into actionable information for the maintenance staff. Technicians can focus on trouble-shooting the issues at hand rather than performing lengthy diagnostics processes at every service visit.

Potential Challenges

Can people responsible for upstream lifecycle functions understand and accommodate the needs of people in downstream functions for the overall better outcome to the entire program? Will feedback mechanisms be put in place to ensure we continue to improve the upstream processes that serve the downstream processes?

We have already seen concepts like design-for-manufacturing well adopted by industry. The concepts of the digital twin can be viewed as evolutionary and a natural progression on that type of thinking beyond the manufacturing process.

Can vendors see beyond their desire to hold a segment of the market hostage to their formats and products? Could they endorse open data exchange standards where needed to facilitate multi-vendor participation in the digital thread?

Can manufacturers, hardware, and software vendors move forward when many are overwhelmed trying to meet short term improvement goals promised to customers and shareholders?

The digital thread and digital twin concepts have been proposed as incremental steps and leading companies are moving forward with these initiatives. Only time will tell but the potential benefits of the digital thread and digital twin seem obvious. The vendors that endorse and provide these types of connectivity techniques could end up being favored by the market in the long term over vendors with proprietary closed solutions.

References

[1] Global Horizons Final Report: United States Air Force Global Science and Technology Vision - AF/ST TR 13-01, United States Air Force, 2013