Secured Cyber-Physical System for Distributed Additive Manufacturing of Metallic Aerospace Structural Parts

Navy STTR 24.B - Topic N24B-T025
NAVAIR - Naval Air Systems Command
Pre-release 4/17/24   Opened to accept proposals 5/15/24   Closes 6/12/24 12:00pm ET    [ View Q&A ]

N24B-T025 TITLE: Secured Cyber-Physical System for Distributed Additive Manufacturing of Metallic Aerospace Structural Parts

OUSD (R&E) CRITICAL TECHNOLOGY AREA(S): Integrated Network Systems-of-Systems; Integrated Sensing and Cyber;Sustainment

OBJECTIVE: Develop a cyber-secured, digital twin-based system for distributed Additive Manufacturing (AM) to ensure trusted/authenticated, intellectual property (IP)-protected, high-quality and reliable/repeatable metallic structural parts.

DESCRIPTION: AM is a melting and rapidly solidifying building process—layer by layer—from a Computer-Aided Design (CAD) 3 dimensional (3D) digital model. Besides its demonstrated values for low-rate production and making complex shapes, AM possesses great potential to be a transformational technology, generating parts just-in-time at the point of need with minimum logistic footprint. This organic capability could significantly improve readiness and aircraft availability for the Navy fleet. For mass production, AM also enables de-centralized/distributed manufacturing (vs. centralized), thereby minimizing backlogs, increasing output capacity/surge-on-demand, and thus making the supply chain more robust and agile. Despite all of the potential promises and benefits, AM still has not yet been widely accepted and implemented across industries due to three main obstacles that must be addressed and show more advancements: (a) data integrity, data rights/ownership and IP protection, (b) cybersecurity, and (c) (Local/Remote) Quality Control and Assurance.

As part of the Naval Product Lifecycle Management (N-PLM) system, Digital Thread (DTh) collects and integrates product-related data dynamically from multiple sources, and then bilaterally exchanges information across enterprises from concept development to disposal. Data associated with typical AM workflow includes CAD design models; detailed part specifications, materials and process specifications; Stereolithography/Additive Manufacturing File (STL/AMF) and G-Code files; machine-specific hardware and software/firmware; processing parameters such as part orientation and placement, energy power level, toolpath and scanning patterns; and so forth. Within the distributed/de-centralized manufacturing eco-system, the need for providing timely access, transmitting and sharing of valuable/proprietary information, and facilitating collaboration is essential among various groups both within the company, as well as outside, such as third-party suppliers. This activity requires proper protection, control, and management of shared trusted data transfer for accountability (tracking and traceability), and product quality assurance along with IP protection. Blockchain is a distributed ledger technology (DLT) that could provide seamless and efficient adaptation of a digital infrastructure such as secured keys for authentication to access the chain and trusted network for data exchange. It also provides immutability of records, which could safeguard sensitive manufacturing information against unauthorized manipulation and IP theft.

AM is considered to be a cyber-physical system (CPS) combining physical hardware with software systems, usually via online network. Researchers have demonstrated that AM process workflow to be susceptible and vulnerable to cyber-attacks on both cyber and physical systems ranging from altering the build file to side channel attack of the printing machine. Malicious attacks could not only degrade the part performance and reliability, but also could damage the machines and cause injury to the operators. The needs for an autonomous system to monitor, detect, and prevent cyber-physical attacks in (near) real-time is paramount for AM.

The AM process possesses a myriad of variabilities that could affect site-specific microstructures, material properties, surface roughness, dimension accuracy, and part performance due to feedstock, part geometries, build orientation, printing process parameters, heat treatments and post-print processing, and so forth. Digital Twin (DT) is a virtual dynamic clone of the AM process including in-situ monitoring, physics-based model, and closed-loop feedback control. Coupling DT with Artificial Intelligence/Machine Learning (AI/ML) and Big Data analytics, a DLT-enabled network could provide an effective and secured framework for (near) real-time quality control (QC) to assure process stability for repeatability and reliability of the printed parts. In addition to providing in-process visibility, a QC system could also be designed to detect the effects of cyber-attacks, such as part tampering.

The Navy seeks innovative technology solutions that are compatible/adaptable and integrated seamlessly (via Application Programming Interface (API)) with the existing N-PLM systems such as Siemens Teamcenter and PTC Windchill to protect AM system from cyber-physical attacks, prevent IP theft, and allow dynamic and low latency data access and transfer while assuring quality, repeatability/reliability, and manufacturing traceability of the printed parts.

PHASE I: Develop the system architecture and concept of operations for cyber-secured, DT-based distributive AM. Demonstrate the technical feasibility of the proposed concept/construct through working examples. The Phase I effort will include prototype plans to be developed under Phase II.

PHASE II: Expand the architectural design and complete application business model to incorporate business logic for all transactional data in the product life cycle. Demonstrate in cyber and physical environments the following:

1. AM version control and IP protection when distributing to external 3D print suppliers/customers, and implement seamless, secured management of Digital Thread (DTh) to ensure optimal AM part quality via:

(a) preserving the digital thread for tracking and tracing part life cycle,

(b) exercising printer controls to limit printing authorized amounts,

(c) exchanging machine parameters during the cycle runs along with any alarm data from the suppliers to the designated activity for quality buyoff and invoice processing,

(d) preventing mistakes associated with using wrong or outdated programs in forming a part,

(e) ensuring authorized personnel to have access to the DLT protecting IP and version control, and

(f) monitoring, detecting, and preventing cyber-attacks.

2. DT to provide a digital end-to-end simulated picture of AM steps (versus expected actual performance), including scan and design, build and monitor, test and validate, and deliver and manage steps.

PHASE III DUAL USE APPLICATIONS: Finalize the system development and application to plan and manage end-to-end AM management activity. Ensure usability for the end user. Perform final testing on a few representative aircraft parts to demonstrate the model’s ability to support Navy Fleet Readiness Centers (FRCs).

Commercial industries have a similar need for their AM product lines and issues concerning product life cycle data and IP protection. Hence this digital system might find wide use across a broad variety of industry sectors.

REFERENCES:

  1. Yampolskiy, M.; King, W. E.; Gatlin, J.; Belikovetsky, S.; Brown, A.; Skjellum, A. and Elovici, Y. "Security of additive manufacturing: Attack taxonomy and survey." Additive Manufacturing, 21, 2018, pp. 431-457. https://doi.org/10.1016/j.addma.2018.03.015
  2. Ahmad, R. W.; Hasan, H.; Yaqoob, I.; Salah, K., Jayaraman, R. and Omar, M. "Blockchain for aerospace and defense: Opportunities and open research challenges." Computers & Industrial Engineering, 151, 106982, 2021. https://doi.org/10.1016/j.cie.2020.106982
  3. Gupta, N.; Tiwari, A.; Bukkapatnam, S. T. and Karri, R. "Additive manufacturing cyber-physical system: Supply chain cybersecurity and risks." IEEE Access, 8, 2020, pp. 47322-47333. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9026901
  4. Mandolla, C.; Petruzzelli, A. M.; Percoco, G. and Urbinati, A. "Building a digital twin for additive manufacturing through the exploitation of blockchain: A case analysis of the aircraft industry." Computers in Industry, 109, 2019, pp. 134-152. https://doi.org/10.1016/j.compind.2019.04.011
  5. Diewald, E. P. "Additive OS: An Open-Source Platform for Additive Manufacturing Data Management & IP Protection." 2021 International Solid Freeform Fabrication Symposium, University of Texas at Austin. https://hdl.handle.net/2152/90634
  6. Yaqoob, I.; Salah, K.; Uddin, M.; Jayaraman, R.; Omar, M. and Imran, M. "Blockchain for digital twins: Recent advances and future research challenges." IEEE Network, 34(5), 2020, pp. 290-298. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9076112
  7. Al Mamun, A.; Liu, C.; Kan, C. and Tian, W. "Securing cyber-physical additive manufacturing systems by in-situ process authentication using streamline video analysis." Journal of Manufacturing Systems, 62, 2022, pp. 429-440. https://doi.org/10.1016/j.jmsy.2021.12.007
  8. Suhail, S.; Jurdak, R.; Matulevicius, R. and Hong, C. S. "Towards Situational Aware Cyber-Physical Systems: Securing Cyber-Physical Systems Through Blockchain-Based Digital Twins and Threat Intelligence." arXiv preprint arXiv:2105.08886. https://arxiv.org/pdf/2105.08886.pdf
  9. Suvarna, M.; Yap, K. S.; Yang, W.; Li, J.; Ng, Y. T. and Wang, X. "Cyber–Physical Production Systems for Data-Driven, Decentralized, and Secure Manufacturing—A Perspective. Engineering," Engineering, Volume 7, Issue 9, September 2021, pp. 1212-1223. https://doi.org/10.1016/j.eng.2021.04.021
  10. Sandborn, M.; Olea, C.; White, J.; Williams, C.; Tarazaga, P. A.; Sturm, L.; Albakri, M. and Tenney, C. "Towards secure cyber-physical information association for parts." Journal of Manufacturing Systems, 59,2021, pp. 27-41. https://doi.org/10.1016/j.jmsy.2021.01.003
  11. Joint Defense Manufacturing Council. "Department of Defense additive manufacturing strategy." Department of Defense, January 2021. https://www.cto.mil/wp-content/uploads/2021/01/dod-additive-manufacturing-strategy.pdf
  12. Cotteleer, M. J.; Goldenberg, S. S.; Wing, I.’ Alliyu, O.; Kania, S.; Mujumdar, V. and Sniderman, B. "Cybersecurity requirements for AM systems: New enforcement in DoD environments, and resources for implementation." Proceedings of the 2021 Workshop on Additive Manufacturing (3D Printing) Security, November 2021, pp. 49-60. https://dl.acm.org/doi/abs/10.1145/3462223.3485624
  13. Romero, D.; Wuest, T.; Harik, R. and Thoben, K. D. "Towards a cyber-physical PLM environment: The role of digital product models, intelligent products, digital twins, product avatars and digital shadows." IFAC-PapersOnLine, 53(2), 2020, pp. 10911-10916. https://doi.org/10.1016/j.ifacol.2020.12.2829
  14. Bonnard, R.; Hascoët, J. Y.; Mognol, P.; Zancul, E. and Alvares, A. J. "Hierarchical object-oriented model (HOOM) for additive manufacturing digital thread." Journal of Manufacturing Systems, 50, 2019, pp. 36-52. https://doi.org/10.1016/j.jmsy.2018.11.003
  15. Pang, T. Y.; Pelaez Restrepo, J. D.; Cheng, C. T.; Yasin, A.; Lim, H. and Miletic, M. "Developing a digital twin and digital thread framework for an ‘Industry 4.0’Shipyard." Applied Sciences 2021, 11(3), 1097. https://doi.org/10.3390/app11031097
  16. Mies, D.; Marsden, W. and Warde, S. "Overview of additive manufacturing informatics: "a digital thread"." Integrating Materials and Manufacturing Innovation, 5(1), 2016, pp. 114-142. https://link.springer.com/article/10.1186/s40192-016-0050-7
  17. Kim, D. B.; Witherell, P.; Lu, Y. and Feng, S. "Toward a digital thread and data package for metals-additive manufacturing." Smart and sustainable manufacturing systems 2017, 1(1), 75. https://www.astm.org/ssms20160003.html
  18. Adamenko, D.; Kunnen, S. and Nagarajah, A. "Digital twin and product lifecycle management: What is the difference?" Springer International Publishing. Product Lifecycle Management Enabling Smart X: 17th IFIP WG 5.1 International Conference, PLM 2020, Rapperswil, Switzerland, July 5–8, 2020, Revised Selected Papers 17, pp. 150-162). https://link.springer.com/chapter/10.1007/978-3-030-62807-9_13
  19. Bolbot, V.; Theotokatos, G.; Bujorianu, L. M.; Boulougouris, E. and Vassalos, D. "Vulnerabilities and safety assurance methods in Cyber-Physical Systems: A comprehensive review." Reliability Engineering & System Safety, 182, 2019, pp. 179-193. https://doi.org/10.1016/j.ress.2018.09.004

KEYWORDS: Additive Manufacturing; Digital Thread; Digital Twin; Cyber-Physical System; In-situ Monitoring; Blockchain


** TOPIC NOTICE **

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The DoD issued its Navy 24.B STTR Topics pre-release on April 17, 2024 which opens to receive proposals on May 15, 2024, and closes June 12, 2024 (12:00pm ET).

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Topic Q & A

5/13/24  Q. Is the use of digital twins a requirement, or will other solutions to ensure real-time quality control be considered?
   A. The objective statement of this topic specifies that it is seeking a “digital twin-based system for distributed Additive Manufacturing (AM)”. The topic description does provide some guidelines as to what defines a digital twin, but ultimately it is up to the bidder to decide whether their particular solution “to ensure trusted/authenticated, intellectual property (IP)-protected, high-quality and reliable/repeatable metallic structural parts” is digital twin-based.
5/03/24  Q. Is the customer only looking for a blockchain-based solution?
   A. No. It’s up to the bidder to propose.
5/03/24  Q. Is the customer only interested in a DLT-based solution?
   A. No. It’s up to the bidder to propose.
5/03/24  Q. What measures do you currently have in place to monitor, protect and protect against ?
   A. It’s up to the bidder to propose.
5/03/24  Q. How do you currently ensure the traceability and reliability of printed parts?
   A. It’s up to the bidder to propose on how to ensure the traceability and reliability of the printed parts.
5/03/24  Q. How do you currently manage and secure sensitive manufacturing data, including CAD design models, part specifications, and process parameters?
   A. It’s up to the bidder to propose.
5/03/24  Q. What specific functionalities do you require from the new solutions to seamlessly integrate with your current systems?
   A. It’s up to the bidder to propose.
5/03/24  Q. How do you envision the integration of new solutions with your existing Naval Product Lifecycle Management (N-PLM) systems such as Siemens Teamcenter and PTC Windchill?
   A. It’s up to the bidder to propose.
5/03/24  Q. Are you primarily focused on low-rate production, complex shape fabrication, just-in-time part production, or mass production?
   A. Yes to all.
5/03/24  Q. What is your current workflow for additive manufacturing (AM)?
   A. Up to the bidder.
5/03/24  Q. Are there any specific issues related to data integrity, cybersecurity, or quality control that you're encountering?
   A. Up to the bidder.
5/03/24  Q. Does the solution have to interface with the physical AM machine?
   A. Yes.
5/03/24  Q. Are we replacing any existing data storage systems?
   A. It’s up to the bidder.

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