In April 2024, MxD (Manufacturing x Digital) hosted the 2024 MBE & QIF Summit which was jointly organized by NIST and the DMSC (Digital Metrology Standards Consortium). The event was attended by nearly 200 individuals and featured over 30 technical sessions along with a factory automation tour at the MxD facility.
The Model-Based Enterprise (MBE) Summit was attended by leaders who have begun deploying digital modeling technologies in earnest to realize the benefits of a Model-Based Definition (MBD) and were eager to share their challenges and successes in the four years since the last MBE Summit. NIST’s Rosemary Astheimer led the call for presentations, organized technical content, and acted as Master of Ceremonies for the event. NIST’s Allison Barnard Feeney presented the architecture of ISO 10303, known as the STandard for the Exchange of Product data (STEP), then focused on ISO 10303-242:2022Model-based 3D engineering (AP 242), widely-used for communicating engineering design and manufacturing information between lifecycle software systems and for long-term archiving. She described the current capabilities in AP 242, detailed new capabilities for edition 4, and described related NIST research results. She emphasized the importance of standards in leveling the playing field for small-to-medium sized enterprises, aiding interoperability of software implementations, and fostering innovation.
The QIF Summit focused on the Quality Information Framework (QIF, ISO 23952:2020) used to manage quality inspection data. Current efforts to develop the next QIF release were presented. DMSC leaders held an interactive session to develop a roadmap for future DMSC standards, enhancements, and activities.
The advantages of MBD are well-established and organizations are developing rich MBDs. Many presenters discussed the challenges that smaller manufacturers face when attempting to support large OEMs and the DOD, organizations eager to embrace the benefits of an MBE. The large leap to model-based technology can be overwhelming and expensive for the small businesses of less than 20 employees that make up 75 % of the approximately 240,000 manufacturing firms in the U.S. MxD introduced the audience to resources available to assist small manufacturers with cost subsidies, training opportunities, and engagement in MxD projects to demonstrate the benefits of digital methods.
There is still a great deal of data being exchanged outside the closed-loop utopia the digital thread promises, as discussed during two panel sessions. One panel addressed the urgent need to address traceability of data throughout the product lifecycle and in long-term data retention. The second panel encouraged industry to take a more aggressive approach to adopting existing MBE capabilities. Both panels sparked dynamic discussions between panelists and attendees.
Plans for MxD to host the MBE Summit in April 2025 are underway and will be announced when dates are confirmed. The 2024 Summit presentations are now available for download from the 2024 NIST MBE & QIF Summit event page.
On 6-7 March 2024, NIST conducted the Named Data Networking (NDN) Community Meeting 2024 as a hybrid event, held at NIST’s National Cybersecurity Center of Excellence in Rockville, MD, and online. The meeting, organized by NIST’s Lotfi Benmohamed and Davide Pesavento and external colleagues, is held annually and brings together researchers in the NDN community, which seeks an evolution from today's host-centric Internet architecture to a data-centric network architecture. Industry participation at this event included C-3 Comm Systems, Dell Technologies, OpenCommons, Operant Networks, Peraton Labs, and Tata Communications.
Researchers presented on a range of NDN-related issues, including:
Emerging Applications: Researchers discussed the important roles of names in developing applications running over NDN, how to support interoperability of secure web objects that is protocol- and application-independent, and how to leverage NDN principles for providing better foundations for hypermedia applications in the future web.
NDN for AI: Researchers demonstrated how a NDN-based data-centric collective communication can be used as the first building block of NDN for AI.
Analyzing NDN and MQTT Performance for Industrial IoT (IIoT) Scenarios: Researchers reported that IIoT environments would benefit from a decentralized communication pattern, to support publishers and subscribers in a many-to-many asynchronous data exchange, which NDN provides.
Traffic Measurement on the Global NDN Testbed: NIST researchers discussed their traffic measurement work, which resulted in the first non-synthetic dataset of NDN traffic traces, captured directly from the actual routers of the NDN testbed, and made available to the research community.
NDN 2024 Community Meeting panel sessions also addressed the following topics:
Building an Open-Source Ecosystem Around NDN: This panel brought together experts from industry and academia to discuss the exciting opportunities and unique challenges associated with the transition of NDN from an academic research project to an Open-Source Ecosystem that needs to be nurtured and managed.
From Local-First to Fully Decentralized Applications: Panelists discussed challenges in building secure, resilient, easy to use, and deployed codebase with well-defined API to facilitate new generations of decentralized applications.
Present and Future of Network Security Framework: As network security remains one of the biggest challenges on the Internet, panelists discussed the scope of today’s network security solutions, and the potential for a comprehensive security framework for future security needs.
In April 2024, NIST researcher Dr. M. Sharp published a Manufacturing Extension Partnership (MEP) blog post, NIST Explores AI-Enhanced Monitoring in Manufacturing Processes, which has engaged both MEP members and broader public stakeholders. Building from this success, Dr. Sharp is coordinating with MEP to develop an upcoming series of similar blog posts to bring further attention and community interactions on this important topic.
In a world where precision, reliability, and efficiency are paramount, manufacturing processes must evolve to take advantage of new capabilities based on Artificial Intelligence (AI). In this inaugural post, Dr. Sharp delves into the realm of AI-enhanced monitoring in manufacturing and describes how NIST is working to more actively support this domain.
For this effort, NIST needs access to high fidelity, broad scope manufacturing data streams that mimic the faults, flaws, and eccentricities that are the staple of real-world manufacturing. Thus, the Industrial Artificial Intelligence Metrology and Management (IAIMM) team collaborated with a NIST Cybersecurity for Operational Technologies team to modify and update the Collaborative Robotic Operations Workcell (CROW) to make a robust and broad scope source of data feasible on a benchtop setup.
CROW was created to facilitate the evaluation of solutions across entire manufacturing systems, from digital communications, to product quality and human interactions. CROW is a multistage manufacturing operation, featuring robotic arms orchestrating the production and evaluation of continuous cyclic product streams. Equipped with 10 major physical components, including collaborative robots, conveyor belts, inspection cameras, and a suite of sensors and digital loggers, CROW provides a comprehensive platform for testing and refining AI-driven solutions in a safe, controlled environment. Anomaly detection and process error prevention are some of the challenges CROW will address by enabling creation and evaluation of tools and procedures to detect and mitigate issues before they escalate.
Through open-access data produced by CROW, researchers, developers, and manufacturers will be able to harness domain-appropriate data streams for the development and testing of AI-enhanced industrial technologies, including development of best practices and standard operating procedures. As stakeholders navigate the intricate landscape of manufacturing, the NIST team is looking to promote collaboration, standardization, and trust. For collaboration opportunities or further information, please contact Dr. M. Sharp in the Smart Connected Systems Division at NIST.
In a recent paper titled “Design of Control Systems with Multiple Memoryless Nonlinearities for Inputs Restricted in Magnitude and Slope” published in the International Journal of Control, NIST researcher Van Sy Mai and collaborators from Chulalongkorn University presented a new methodology for designing control systems that integrate a linear time-invariant subsystem with multiple decoupled nonlinearities. It focuses on ensuring system outputs of interest and nonlinearity inputs remain within prescribed bounds for all system inputs or disturbances that happen or are likely to happen in practice, i.e., inputs that are restricted by magnitude, energy, and rate of change. Such design criteria are common in various practical applications, where systems must operate within strict limits to guarantee stability, safety, and quality of service.
To overcome challenges due to the complex behavior of nonlinear systems, the research employs the Schauder fixed-point theorem to demonstrate how a design associated with a linear system can effectively address the outlined problem. It then introduces surrogate design criteria, provides solvability conditions for certain nonlinearities common in most practical control systems, and presents numerical methods for solving those criteria for a more general class of nonlinearities.
The authors demonstrated how the developed methodology can be applied to design a controller for a load frequency control (LFC) system that includes communication delays and accounts for nonlinearities like dead zones (or unresponsive zones) in the speed governor and generation rate constraints in the steam turbine. Here, the objective of the LFC is to maintain the frequency deviation in the presence of load variations within an acceptable range for all time during operation. They illustrate the effectiveness of the proposed approach by comparing the performance of controllers designed with and without considering the nonlinearities. Their results show that on one hand neglecting nonlinearities in the design process can lead to unsatisfactory performance or even instability of the system. The controller obtained using the developed methodology on the other hand provides satisfactory results, ensuring the system operates within desired parameters even in the presence of nonlinearities. This essentially validates the theoretical concepts presented in the paper through a real-world engineering problem highlighting the importance of considering all aspects of a system, including potential nonlinear behaviors, to achieve a robust and reliable control system design.
In summary, this study addresses the need to maintain system variables within certain tolerances, offering a realistic and practical approach to control system design. It is particularly relevant for engineers monitoring control system performance and has the potential to be applied in various practical scenarios, where systems, especially critical ones, must operate within strict limits, ensuring reliability and stability in real-world applications.
The SAE World Congress Experience (WCX) 2024 was held on April 16–18, 2024 in Detroit, Michigan. The event attracts researchers, government officials, and the engineering community to discuss the mobility industry's biggest challenges, including the deployment of electric vehicles, autonomous vehicle timelines, and global supply chain constraints. Organized by SAE International, this event served as a forum and showplace for the latest technology, consumer metrics, regulatory standards, and technical sessions covering the entire vehicle, from hardware to software, and beyond to their usage in transportation systems as part of Smart Cities. The WCX 2024 keynote speaker, Toyota Research Institute’s Avinash Balachandran, described the ubiquitous role of artificial intelligence (AI) in automotive technology development, from the way vehicles perceive the roadway, to path planning and adaptive manufacturing tooling.
NIST CPS and Autonomous Systems researcher Dr. Edward Griffor shared the NIST Strategic and Emerging Research Initiatives (SERI) Automated Vehicle Project’s advances in autonomy modeling and integration of uncertainty into AI-enabled perception. Griffor also discussed NIST progress to date in developing measurement methods for autonomous system task performance, formalizing the work allocation of task performance between an autonomous system and its operating environment in terms of the “fit” of information acquired by the system from its surroundings. Based on these discussions with industry and standards experts, Griffor was able to assess stakeholder interest in and alignment with research directions at NIST.
In April 2024, the NIST Industrial Wireless Team hosted visitors from the Asia Open-RAN Academy, showcasing the innovative NIST 5G Industrial Testbed. NIST’s Rick Candell presented the testbed's mission and ongoing projects, including exploring 5G private networks with the Firecell Labkit 100 system and collaborating with Intel on time-sensitive networking over Wi-Fi. This critical research facility is designed to evaluate and develop 5G technology specifically for industrial applications, supporting the demands of Industry 4.0. This informative session and lab tour, part of a broader interaction organized by the NIST Wireless Networks Division, fostered discussions on potential collaboration between the two groups. Together, they aim to leverage their world-class research to accelerate the adoption of O-RAN technology in manufacturing, construction, and other operational technology sectors, where appropriate.
