Interoperable Digital Twine Framework (IDTF)


The Department of Defense (DoD) often uses costly and difficult-to-repair systems and components, and replacement parts take a long time to develop and acquire. When the original equipment manufacturer or supply chain is unavailable, sustaining these systems becomes even more challenging. To model proposed designs and as-built components, 3D models need to be created from 2D drawings, specifications, and other artifacts, which is expensive and time-consuming. Over time, components degrade, and determining the type and extent of degradation is difficult, which could lead to catastrophic failure without warning.

“Digital drives Physical”

The project “Interoperable Digital Twin Framework (IDTF)” emphasizes its focus on creating a framework for digital twin technology that is interoperable with various platforms typically used by the Department of Defense. The word “interoperable” highlights the project’s goal of creating a flexible and adaptable system that can integrate with different components and systems, enabling better communication and collaboration among various teams involved in system sustainment activities like parts management and engaged production.

The IDTF project aims to leverage digital twin technology to create a virtual replica of defense systems, enabling better analysis and simulation of the system’s performance. The project’s focus on interoperability emphasizes the importance of creating a framework that can integrate with various components and systems, enabling better collaboration and communication between different teams involved in system sustainment.

Overall, the Interoperable Digital Twin Framework (IDTF) aims to provide the Department of Defense with an advanced system for sustainment, enabling faster and more efficient maintenance of defense systems.


The DIU (Defense Innovation Unit) is an end-to-end prototyping partner to bridge the gap between DoD and commercial companies.


Project Name: Digital Engineering and Manufacturing of Composite Structures

The Department of Defense (DoD) often relies on expensive, bespoke systems and components that are difficult to repair or replace. Often, uniquely-designed replacement parts take too long to develop and acquire. Sometimes, the original equipment manufacturer (OEM) or supply chain is unavailable, creating challenges for system sustainment.

In many cases, the government needs to model and simulate the form, fit, and function (i.e., aerodynamics, structural loading, and hardware integration) of proposed designs and as-built components within the context of larger systems. This requires 3D models to be converted from 2D drawings, specifications, and other artifacts, which can be expensive and time-consuming.

Additionally, due to operational use over time, components will naturally degrade. However, the type and extent of degradation (e.g., cracks and other structural deformations) are difficult or impossible to determine without time-consuming, hands-on engineering evaluations. Impending structural problems may lead to catastrophic failure without automatic warnings to operators and maintainers.


The DoD seeks commercial solutions that leverage interoperable digital twin technologies to rapidly design, manufacture, and monitor the health of large, molded composite structures. The service developed in the prototyping effort is intended to be an interoperable set of engineering and manufacturing processes. This service will decrease the cost and increase the delivery speed of various composite structures. The Defense Innovation Unit (DIU) will consider vendors who provide the full scope of services and best-in-class solutions for portions of the problem. Teaming arrangements may be encouraged.

The DoD will determine prototype success by testing and evaluating the design and manufacturing of large composite fan blades in an operational setting. Although the DoD problem is broader than this evaluation, successful completion within these parameters will assist in considering other efforts.

Solutions should address the following:

A. Digitizing Existing Technical Data:

  • Convert government-furnished designs, specifications, and other artifacts into technical data packages using digital engineering best practices for the foundations of an authoritative source of truth (digital twin).
  • Create holistic digital models that are interoperable with industry-standard software, including design, modeling, simulation, manufacturing, and operational monitoring tools.

B. Digital Engineering:

  • Build on pre-existing digital models to design a solution appropriate for the operational context.
  • Given a specified outer mold line (OML) geometry, loads criteria, interfaces, and other known specifications, the vendor should be able to create a 3D model-based definition (digital technical data package).
  • Design with materials and processes that are fully characterized for strength and fatigue resistance and can carry high dynamic loads.
  • Design with embedded sensing capability that supports requirements verification/validation and structural health monitoring.
  • Design to resist Foreign Object Debris (FOD) impact and allow in situ inspection and repair of moderate FOD damage.

C. Digital Manufacturing:

  • Leverage advanced technologies to rapidly manufacture the digital design into a molded composite structure.
  • Produce digital models that represent the as-built characteristics of each serialized part.
  • Integrate specified sensing capabilities into the final product.
    Minimize lead time and manufacturing cycle time.


Numorpho Cybernetic Systems (NUMO)’s premise is to solve the hard problem of automation using a blend of people, process and technology unified to provide the basis for innovation, optimization, and harmonization in product development, industrial processes, infrastructure (re)builds, transportation enhancements, and electric mobility products.

Our company specializes in process automation and is dedicated to revolutionizing the product launch process for businesses. We offer user-friendly, comprehensive tools to facilitate process automation, enabling companies to seamlessly transition to Industry 4.0 and beyond.

We do this by looking at all aspects – Product Development, Smart Manufacturing, Information Technology, Operational Processes, and sustained Customer Enablement – using engineering, multi-physics, data-driven and AI-enabled inference engines. This helps unravel the complexity (the knowns and the unknowns), provide the right basis for the use cases and blueprinting, and evolve the solution and its sustainability.

Our Mantra is based on optimizing and harmonizing the 5 Ms of:

  • Make
  • Manage
  • Move
  • Market, and
  • Maintain

and our endeavor is to provide and end-to-end digital framework to accomplish process automation.

Founded in Chicago, IL in 2021, NUMO is a company whose vision is to utilize intelligent techniques to build smart, connected, and sustainable products by pushing the edges of engineering, technology, data management, AI, and cybernetics. We will be creating new ideation techniques, enabling Industry 4.0 (for smart connectivity and robotic automation), and adding to it the Industry and Services 5.0 (humancentric and sustainable products) framework for development, build and commercialization.


Our key objective for this project is to utilize our Digital Twine reference architecture to build a digital framework to manage all aspects of technical data to enabling the efficient engineering and manufacture of products. Utilizing our Digital Twine reference architecture, we will connect the dots between disparate enterprise systems to enable the pull-and-push of information by coordinating activities between people, process and platforms to achieve coordination, optimization and harmonization in processes end to end.

The Interoperable Digital Twin Framework (IDTF) address the need for a connected engineering and manufacturing platform that integrates various systems and processes to enable the creation of digital twins of complex systems.

The IDTF platform is designed to connect different engineering and manufacturing tools, enabling collaboration and data sharing across the entire product lifecycle. It provides a unified view of data from various sources, allowing engineers and designers to create and modify digital twins of complex systems in a more efficient and effective manner.

This platform addresses the need for a connected engineering and manufacturing platform that integrates various systems and processes, making it easier to create, maintain, and sustain complex systems over their lifecycles.


The diagram below depicts the end-to-end process comprising of upstream, midstream and downstream activities that make up the details of an engineering and manufacturing flow.

We divide the ecosystem into three streams:


  1. Upstream Processes – These are related to product development activities – define, design, material properties management and engineering simulation, and the management of the technical assets related to the product.
  2. Midstream Processes – These are related to manufacturing, procurement of materials and equipment, supply chain and shipment logistics.
  3. Downstream Processes – These are related to maintenance, support and service functions and optimizing the downtime in operations when parts need to be replaced.

Our Digital Twine reference architecture is a combination of Digital Threads and Digital Twins spanning across different enterprise systems. It is utilized to compose and blueprint use cases in smart manufacturing initiatives ranging from:

  • brown-field initiatives – retrofitting existing systems,
  • green-field initiatives – defining infrastructure from ground up, to
  • blue-sky initiatives – creating disruptive technologies.

to enable make, manage, move, market, and maintain (M5) activities in Industry 4.0 implementations.

Depicted below is the Digital Twine reference architecture modified for the needs of the Interoperable Digital Twin Framework.


The scope of the project is to map out the needs at every one of the connected dots to ascertain the basis for collaboration of the team, coordination of processes, and the integration of data between the different platforms.


In the development process up-stream, it is important that the various stages of design, prototyping and testing are done in a coordinated and synchronized manner. IDTF can be used to help with this by ensuring that the various steps are done in a consistent and repeatable manner.


  1. Planning – Planning can be correctly coordinated by automating the generation of test data and test cases.
  2. Design – Automation can help with the design process by automating the generation of code skeletons and testing scripts.
  3. Implementation – Automation can help with the implementation process by automating the generation of source code and test data.
  4. Verification – Automation can help with the verification process by automating the generation of test reports.


In production mid-stream, the use of IDTF can help to speed up the manufacturing process and improve the quality of the products. It can also help to identify and correct any problems that may occur during the production process.


  1. Procurement – Material and machine procurement and the creation of the right workforce
  2. Assembly – Automation can help with the assembly process by automating the assembly of products.
  3. Testing – Automation can help with the testing process by automating the testing of products.
  4. Packaging – Automation can help with the packaging process by automating the packaging of products.
  5. Shipping – Automation can help with the shipping process by automating the shipping of products.


For our connected parts and products down-stream, IDTF can be used to help manage and monitor the products and the various systems they are connected to. This data can then be used to improve the performance, predict failure and be proactive in maintenance and operations.


  1. Configuration – Automation can help with the configuration of products by automating the configuration of products.
  2. Activation – Automation can help with the activation of products by automating the activation of products.
  3. Monitoring – Automation can help with the monitoring of products by automating the monitoring of products.
  4. Maintenance – Automation can help with the maintenance of products by automating the maintenance of products.


We believe that three domains will be important in the future as we continue to strive to achieve the ultimate goal of a fully connected product and service continuum. Thus, for the IDTF we have divided it into the following domains:

  1. Platform Integration and Management: We need to be able to manage massive amounts of data from various sources, components, and devices seamlessly through the digital thread to realize the connected value stream through the product and service continuum.
  2. Intelligent Data Analytics: We need to be able to make sense of all the data that is being generated in order to make better decisions about what needs to be done with the product or service.
  3. Connected Services and Applications: We need to be able to provide new services and applications to our customers in order to improve their experience and get more value out of our platform.

The key here is to partner with the best of breed platform and solution providers to provide the basis for orchestrating the engineering and manufacturing process.


We have spent the past three decades in the engineering and technological domains of aerospace, automotive and other sectors. Over these years, we have developed strong relationships with cloud and platform providers, engineering solution companies, manufacturing tools providers and system integrators that we plan to leverage to provide an integrated solution using the IDTF.

Represented below is our strategy chess board depicting the companies, organizations and schools that we are partnering with to evolve our connected ecosystem for engineering and manufacturing.


Our approach at Numorpho Cybernetic Systems (NUMO) of making in the new is called Adaptive Engineering. Amidst the skewed distribution and use of people, process and technology in today’s enterprises, Adaptive Engineering proposes a direction to shift this imbalance towards people by bringing them in as process boundaries, appropriate use of tools to reduce technical debt and using customer insight feedback loops to align with human-need, desires, and aspirations. This is appropriate as we progress thru our industrial revolutions from Industry 4.0 (smart manufacturing) to Industry and Services 5.0 (human centric solutions).

We see engineering becoming more about data analytics and less about traditional engineering disciplines. We are already starting to see this trend with the rise of data science and the increasing use of machine learning and artificial intelligence in engineering. We believe that the future of engineering is about data-driven design and engineering. In the future, engineers will be able to use data to design and optimize products and systems in ways that were never before possible. The world of engineering is changing rapidly, and the traditional engineering disciplines are becoming less relevant. To be successful in the future, engineers need to be open to new approaches and technologies. They need to be able to use data to design and optimize products and systems in ways that were never before possible.


Engineering simulation is the process of using computer software to create a virtual model of a system or process, and then using that model to analyze, test, and optimize its behavior. This can include anything from analyzing the aerodynamics of a car, to designing a new medical device, to predicting the performance of a power plant.

The advantages of engineering simulation are numerous:

  1. Cost savings: Simulation can save time and money by allowing engineers to test and optimize designs before they are physically built.
  2. Improved design quality: Simulation provides engineers with a deeper understanding of how a system will perform, allowing them to make more informed design decisions.
  3. Risk reduction: Simulation can identify potential problems early in the design process, reducing the risk of costly mistakes or failures.
  4. Increased innovation: Simulation can enable engineers to explore new design concepts and optimize performance in ways that would be difficult or impossible with traditional methods.
  5. Faster time-to-market: By reducing the time required for physical prototyping and testing, simulation can help companies bring new products to market more quickly.
  6. Better collaboration: Simulation can facilitate communication and collaboration between team members, allowing engineers and designers to work together more effectively.

Composite Materials

Smart manufacturing involves the use of data and advanced technologies to optimize production processes, increase efficiency, and reduce waste. Additive manufacturing using composite materials can be integrated into this approach by enabling manufacturers to create customized products on demand, reducing waste through precise material usage, and improving overall quality control through advanced inspection and testing techniques.

By utilizing advanced technologies such as CAD Software, CAE simulations and 3D printers, manufacturers can create complex composite structures that are stronger, more durable, and lighter than traditional manufacturing methods.

A key component of IDTF will be enabling composite part manufacturing wherein our philosophy of “Born not Built” will be utilized to design, engineer and manufacture parts on demand, even enabling localized manufacturing in remote locations.

By partnering with forward thinking companies like Markforged, Hexagon Manufacturing Intelligence, 3Degrees and others, we will build a holistic framework for the future of manufacturing.

Here are some of the salient points related to the work that our partners are doing that we will integrate into our methodology:

  • Markforged is the leader in additive manufacturing technologies for composites. Their current and future line of 3D printers facilitate precise parts manufacture using CAE simulations, precise “tool” pathing using Blacksmith, part of their Digital Forge philosophy that uses laser guided, AI driven mechanisms to produce quality products.
  • We have been working with Hexagon Manufacturing Intelligence Digimat and 10xICME toolkits to further the correct utilization of composite materials:
    • Digimat is the state-of-the-art multiscale material modelling platform focusing on the micromechanical modelling of complex multiphase materials such as plastics, composites, metals, and elastomers, revealing how they perform at part and system levels. Digimat bridges the gap between materials, manufacturing processes, and structural part performance to design innovative high-performance products while minimizing weight, cost and time-to-market.
    • 10xICME is setting the standard for Integrated Computational Materials Engineering with the strongest solution ecosystem in the world. It is developed alongside academia and industry experts and was released for use following further input from partners across our eco-system which led to the ‘fine tuning’ of the unique ten pillar methodology.
  • 3Degrees is an independent, technology-agnostic 3D Printing and Materials Science consulting company that help implement 3D Printing Solutions through practical insights and materials expertise via four pillars of practice:
    1. Develop and Test Materials
    2. Establish Production Capabilities
    3. Help Build Workforce
    4. Manage 3D printing data

Generative Design


Generative design is a process that uses computer algorithms to generate and evaluate a large number of design options, based on input parameters and constraints. It is a form of artificial intelligence that can optimize designs based on multiple criteria such as weight, strength, cost, and manufacturability.

In engineering simulations, generative design can be used to explore a wide range of design options and quickly identify the best design solutions based on the specified criteria. The process involves creating a virtual model of the system or component, defining the performance requirements and constraints, and then using algorithms to generate and evaluate thousands or even millions of design options.

Once the algorithm has evaluated the designs and identified the best solutions, engineers can use simulation software to further refine and optimize the designs. This approach can result in designs that are lighter, stronger, and more efficient than traditional designs.

Generative design can be particularly useful in complex engineering projects, such as aerospace or automotive design, where multiple performance criteria need to be optimized simultaneously. It can also be used to explore new design concepts and push the boundaries of what is possible in terms of performance, while still meeting the required constraints and specifications.


Simulation is a powerful tool for testing and optimizing designs in additive manufacturing, which is a process that builds up components layer-by-layer using a range of materials including plastics, metals, and ceramics. The complex geometries and material properties of additive manufactured parts make them difficult to test using traditional methods, but simulation can help overcome these challenges in several ways:

Predicting material behavior: Simulation software can predict the behavior of materials during the additive manufacturing process, such as how they will melt, solidify, and shrink, which can help engineers optimize the manufacturing process and avoid defects.

Identifying potential problems: Simulation can help identify potential problems that could occur during the additive manufacturing process, such as warping or distortion of the part, which can be corrected before the part is built.

Optimizing part design: Simulation can help optimize the design of additive manufactured parts by predicting how they will perform under different conditions, such as temperature or pressure, and identifying areas that may require additional support structures or modifications to improve strength or durability.

Reducing physical testing: Simulation can help reduce the amount of physical testing required to validate additive manufactured parts, saving time and costs while still ensuring the part meets performance requirements.

Enabling iterative design: Simulation can enable iterative design cycles, allowing engineers to quickly test and optimize multiple design options before selecting the best one for production.

Overall, simulation can enable more efficient and effective testing of additive manufactured parts, helping to ensure that they meet the required specifications and performance criteria.


The solution process will be broken down into the following phases as detailed below:


USE CASE – Remote Manufacturing Point of Need for the DoD

We are working on this for the Manufacturing Innovation Institutes in conjunction with:

  • MxD – The DoD funded organization whose thesis is enabling smart manufacturing, industrial cyber security and supply chain logistics.
  • Microsoft’s Industry solution for Defense and Intelligence to provide the bits and bytes of the foundation of the platform, and
  • Markforged providing their technology and expertise in 3D printing and their platform for distributed Additive Manufacturing.



Our goal is to enable engineering and manufacturing in the new paradigm of Industry 4.0:

  • to build out an exacting process manager,
  • to connect the dots in automation, and
  • to build a human-centric basis for our technological progress.

Using a blend of people, process and platforms, we plan to be prominent in the future of dynamic digital interactions with cyber-physical systems – be it industrial, infrastructure, transportation and/or mobility.

The Interoperable Digital Twin Framework will provide the basis for industrial processes to be better connected end-to-end and help facilitate new engineering designs using composite materials, Additive Manufacturing and smart IoT technologies coupled with data engineering and AI/ML to make the processes robust and resilient to constant changes.

For the DoD, the ITDF platform would enable better integration and collaboration across the product lifecycle, making it easier to design, manufacture, and sustain complex systems. By connecting various systems and processes, including those that leverage composite materials, Additive Manufacturing, and smart IoT technologies, the IDTF platform will enable the DoD to create more robust and resilient processes that can adapt to constant changes. The platform’s blend of people, process, and platforms will create a human-centric approach to technological progress, facilitating dynamic digital interactions with cyber-physical systems in various industries, including infrastructure, transportation, and mobility.


NI+IN UCHIL Founder, CEO & Technical Evangelist


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