Please see the full solicitation for complete information about the funding opportunity. Below is a summary assembled by the Research & Innovation Office (RIO). Note the cost-share requirements in the Award Information section below.

Program Summary

NIST is seeking proposals from eligible applicants to establish and operate a Manufacturing USA庐 institute focused on the use of Artificial Intelligence (AI) to increase the resilience of U.S. manufacturers. A proposed institute in this topic area will be considered for funding pursuant to this NOFO if it does not substantially duplicate the principal technical focus area(s) of existing federally funded institutes within Manufacturing USA network, or the technical focus area(s) identified within any in-progress Manufacturing USA institute funding opportunity announced by a Federal Agency.

Proposers should note that applications for product development and commercialization are not considered responsive to this NOFO and are excluded from consideration for funding. Proposers should also note that proposals focused on the use of AI for semiconductor manufacturing applications are not considered responsive to this NOFO and are excluded from consideration for funding

NIST expects to select an applicant or applicant team most capable of establishing and leading a public-private partnership that will integrate expertise in AI, manufacturing processes, and supply chain networks to conduct applied R&D projects that address industry-wide needs for innovation leading to greater resilience of manufacturing systems. The AI MFG USA institute is also expected to cultivate the development of a world-leading workforce needed to deploy institute-developed AI technologies into industrial use. The award will provide financial resources to establish the AI MFG USA institute, conduct startup activities and operate a national effort to accelerate manufacturing innovation and increase U.S. global competitiveness.

AI for Resilient Manufacturing Institute. Resilience may be defined as the ability of a given system to prepare for and adapt to unexpected events; to quickly adjust to sudden disruptive changes that negatively affect performance; to continue functioning during a disruption (sometimes referred to as 鈥渞obustness鈥�); and to recover quickly to its pre-disruption state or a more desirable state. Adoption of AI has the potential to strengthen resilience of U.S. manufacturing through improvements in productivity and efficiency, job quality, worker safety and quality control systems, while reducing downtime for predictive maintenance, waste and defects. AI adoption has the potential for efficient utilization of other digital technologies in optimizing product design and process flow, and energy management. Furthermore, adoption of AI technologies can drive greater resilience for manufacturing supply chain networks and increase visibility of domestic suppliers.

While the following list is illustrative in nature and not exhaustive, AI tools applied to use cases such as the following can boost resiliency within individual firms and the overall manufacturing sector:

  • Rapid qualification. Qualification of new production technologies, facilities, or processes by potential customers can take years. AI-based analytics and predictive models can be used to quickly identify critical tests to perform, gauge dependencies and success probabilities of other tests, and assess likely operating conditions and boundary conditions. These methods help reduce the number of tests to perform and thereby shorten the path to qualification.
  • Predictive maintenance of structures and equipment. In a high-volume manufacturing facility, equipment outage is a serious problem. AI-based advanced analytics and sensors can be used to analyze in real-time the stresses on critical equipment and structures, compare to past events, and predict the likelihood of an outage within a certain time period. This way, equipment can be serviced before failure, or operational parameters can be tuned to reduce stresses on equipment.
  • Yield, energy, throughput, and quality (YETQ) optimization. Improving the operational productivity of the manufacturing process, such as reducing resource inputs (such as materials and energy), increasing throughput, or reducing defects in the process can be critical, particularly in industries with high resource intensity. AI can be used to learn current and target YETQ metrics and dynamically adjust process parameters for optimal outcomes.
  • Working capital optimization. In fast-moving industries and those with long and complex supply chains where inventory costs can be high, having the 鈥渨rong鈥� amount of inventory can be catastrophic to bottom lines. AI can be used to learn and predict the amount of inventory at each stage of the production process to optimize total working capital relative to demand trends and supply chain capacity.
  • Supply chain risk prediction. Another critical aspect of supply chain resilience is a manufacturer鈥檚 ability to predict or be prepared for potential supply chain disruptions. AI- based analytics can identify potential disruptions based on natural disasters or other shocks by analyzing and correlating data from multiple sources. AI can also help size the potential disruptive effect on operations to help manufacturers prepare for events and guide the development of more resilient supply chain networks with decreased reliance on foreign suppliers.

See the solicitation for full details.

Deadlines

CU Internal Deadline: 11:59pm MST August 26, 2024

NIST Concept Paper Deadline: 9:59pm MST September 30, 2024

NIST Application Deadline (by invitation): 9:59pm MST January 23, 2025

Internal Application Requirements (all in PDF format)

  • Concept Paper (10-point font minimum, 4 pages maximum): Please include:
    • 1) a concise summary/abstract of the proposed activity suitable for dissemination to the public. It should be a self-contained document that identifies the name of the applicant, the director/principal investigator(s), the application title, the objectives of the proposed institute, a description of the proposed institute, methods to be employed, the potential impact of the proposed institute (i.e., benefits, outcomes), and major participants (for collaborative institute activities). This document must not include any proprietary or sensitive business information as NIST may make it available to the public after selection of concept papers has been completed.
    • 2) a description of the proposed AI MFG USA institute sufficient to permit evaluation of the concept paper in accordance with the Evaluation Criteria (see Section 5.1 on page 46 of the ); and a description of how the proposed MFG USA AI institute would be non- duplicative of and complementary to the work within the existing network of Manufacturing USA institutes, as well as the NIST-sponsored U.S. Artificial Intelligence Safety Institute (USAISI) Consortium.
  • Lead PI Curriculum Vitae
  • Budget Overview (1 page maximum): A basic budget outlining project costs is sufficient; detailed OCG budgets are not required. Details should be included on the source(s) of cost-share.

To access the online application, visit: 听

Eligibility

See the solicitation for full details.

Limited Submission Guidelines

Only a single concept paper may be submitted from a lead applicant entity.

Award Information

Amount: $14M per year over 5 years

Number of Awards: 1

This program requires cost-share (financial support) from non-federal sources in an amount at least equal to the amount of federal funding over the lifetime of the award (i.e., 50% or more of the total funding for the Institute must come from non-federal sources). Reference the full solicitation for cost-share requirements.

Review Criteria

The internal committee will use NIST鈥檚 concept paper evaluation criteria below for the selection process.

  • Potential to Fulfill a Recognized National Need with Substantial Broad-Based Benefits and Demonstrated Industry Leadership (40 pts): The concept paper will be evaluated for merit of the scope and vision of the proposed AI MFG USA institute, including: the technical focus area(s) to be addressed by the institute and the importance and significance of the institute鈥檚 focus within the context of U.S. advanced manufacturing national needs, existing capabilities, ongoing and existing efforts; the potential for substantive national impacts enabled as a result of the activities being proposed; and the evidence of industry commitment, involvement, and leadership towards creation of the proposed institute. Specifically, the concept paper will be evaluated in the context of the following sub-criteria:
  • Proposed Mission and Technical Scope. (0-15 pts): The quality, innovativeness, and merit of the mission and technical scope of the proposed AI MFG USA institute, and its potential impact on the resilience of U.S. manufacturers. This includes:
    • An appropriate and clear description of the use of AI on a manufacturing process, novel material, enabling technology, supply chain integration methodology, or other relevant aspect of advanced manufacturing that strengthens manufacturing resilience and that has not already been commercialized, marketed, distributed, or sold by another entity;
    • The extent to which the proposed AI MFG USA institute focus does not substantially duplicate the technical focus areas of the existing Manufacturing USA network and offers unique and complementary capabilities to the network;
    • The extent to which the proposed AI MFG USA institute will complement other federally funded AI initiatives of similar magnitude and how the institute plans to leverage these other initiatives to increase impact of the federal investments;
    • The extent to which the proposed approach for the AI MFG USA institute will: increase resilience of U.S. manufacturers by performing research and development to solve pre- competitive industrial problems important to economic or national security interests; retain, expand or strengthen industrial production in the United States; and facilitate the transition of innovative AI tools technologies into scalable, cost-effective, and high- performing manufacturing capabilities (MRL 7 and beyond);
    • The extent to which the proposal demonstrates knowledge of the current state of the art in AI, manufacturing processes, supply chain networks and relevant industrial applications for the scope of work proposed, as well as the feasibility of advancing the state of the art by addressing the gaps, constraints, and significant challenges that must be mitigated for the institute to be successful in the chosen area of focus; and
    • The clarity and rationality of the goals and objectives, and their alignment with the mission of the institute and likelihood to accelerate AI-enabled innovation for greater manufacturing resilience.
  • National Impacts and Broad-based Benefits. (0-15 pts): The magnitude, quality, and likelihood of the envisioned national impacts and broad- based benefits that would arise from the proposed AI MFG USA institute. This includes evaluation of:
    • The extent to which the AI MFG USA institute will advance the resilience of domestic manufacturing and the likelihood of economic impact, including the creation or preservation of high-quality jobs, for defined industry sectors, or in the overall industrial base;
    • The extent to which the AI MFG USA institute will advance economic competitiveness and generate substantial benefits to the Nation that extend beyond the direct return to participants in the institute, including through advancing equitable geographic, institutional, and societal access to the economic benefits facilitated by this program;
    • The extent to which the AI MFG USA institute will increase the non-federal investment in advanced manufacturing research in the United States;
    • The extent to which the AI MFG USA institute will successfully engage with small and medium-sized manufacturing enterprises and labor organizations as appropriate to improve the capacity of such enterprises to commercialize new processes and technologies and strengthen domestic supply chains;
    • The extent to which the AI MFG USA institute will act as a knowledge broker between users, manufacturers, industry associations, labor organizations, professional societies, and economic development entities to develop the capabilities, equipment, personnel, and other assets needed to shape U.S. participation in global supply chains; and
    • The extent to which the AI MFG USA institute will promote technology transfer to accelerate the flow of AI-enabled manufacturing innovation from initial targeted sectors into broader applications within the Nation鈥檚 industrial base.
  • Leadership and Involvement from Industry, Academia, Small-and Medium-sized Enterprises and Covered Entities. (0-10 pts): The quality, magnitude, adequacy, and evidence of leadership and involvement from academia and especially industry, assembled to date, towards creating a sustainable and equitable AI MFG USA institute. This includes the evaluation of:
    • The extent to which the proposal demonstrates engagement of industry, and academia in developing the scope and vision for the institute, and provides mechanisms for ongoing advice, participation, leadership, and other contributions (excluding cost-share) to the AI MFG USA institute from non-federal stakeholders within the advanced manufacturing ecosystem, to leverage these resources and to mitigate the need for long-term federal funding;
    • The extent to which the involvement and leadership of industry, labor, and academic partners are cultivated and balanced to create a significant positive force in establishing and sustaining the institute, as reflected by the scope, nature, and magnitude of proposed engagements;
    • The consideration and involvement of small- and medium-sized enterprises (SMEs) and covered entities within the AI MFG USA institute鈥檚 design and governance, and effectiveness of proposed mechanisms to address specific needs and extend benefits of participation to these organizations.
  • The Proposed AI MFG USA Institute (30 pts): The concept paper will be evaluated for the technical and business merits associated with the proposed strategy and design for establishing and operating the proposed AI MFG USA institute. Specifically, the concept paper will be evaluated in the context of the following sub-criteria:
  • Business Plan. (0-20 pts): The soundness and adequacy of the conceptual vision and plan for the proposed AI MFG USA institute鈥檚 business structure, organization, management, and operations models. This includes:
    • The effectiveness of the models presented to establish the AI MFG USA institute as an independent, neutral, and non-biased entity able to coordinate and convene a broad range of stakeholders, including small and medium-sized enterprises (SMEs), and become a uniquely valued component of the Nation鈥檚 AI-enabled innovation infrastructure;
    • The soundness and rationality of the proposed organizational structure and the operation of the AI MFG USA institute, including: the strategies and approach for the institute鈥檚 management, governance and membership structures and roles for industry, academic, and other partners such as other Manufacturing USA institutes and Federal and non-Federal Government participation as appropriate;
    • The strategy and guiding principles for management and protection of Intellectual Property (IP) that will incentivize broad-based U.S. private sector involvement and cultivate economic benefits within the context of the global environment;
    • The strategy and guiding principles for the proposed AI Risk Management plan to identify and mitigate potential risks to individuals, organizations and society, associated with the activities undertaken within the institute.
    • The sufficiency of the proposed AI MFG USA institute鈥檚 physical facilities to meet the needs of the institute and contribute to the U.S. innovation infrastructure; and
    • The rationality and effectiveness of the guiding principles and approach for the AI MFG USA institute to progress expeditiously through a Startup Phase and begin its ongoing operations.
  • Integrated Education and Workforce Development (EWD) (0-10 pts): The quality, soundness, and appropriateness of the conceptual vision and plan for the proposed institute鈥檚 integrated education and workforce development. This includes:
    • How the AI MFG USA institute will design, develop, and direct educational and workforce activities that meet industrial needs and the needs of workers related to AI-enabled manufacturing resilience;
    • The demonstrated awareness of existing national and regional education and workforce development assets, including sectoral partnerships relevant to AI skillsets, and rational approaches to contribute to and leverage these assets in the institute鈥檚 EWD activities;
    • How the AI MFG USA institute will prioritize curriculum and content development for an AI-enabled manufacturing workforce; and
    • How the AI MFG USA institute will encourage the education and training of underrepresented communities and engage covered entities38 for advanced manufacturing career paths, as well as support inclusion of veterans and individuals with disabilities in the EWD opportunities.
  • Resources, Qualifications, and Experience for the Proposed Institute (30 pts): Concept papers will be evaluated for the strengths of the proposed budget, cost-share, and the proposed team in the context of the following sub-criteria:
  • Rough Order of Magnitude (ROM) Budget. (0-10 pts): The appropriateness and cost-effectiveness of the proposed ROM Budget with respect to carrying out the work and objectives as described in the program narrative. This includes:
    • How the proposed ROM cost for the work is appropriate for the work to be performed, per year, over the initial five (5) year award period, which includes: 1) the AI MFG USA institute establishment and Startup Phase, and 2) the Ongoing Institute Operations phase;
    • The degree to which the ROM Budget is consistent with the proposed AI MFG USA institute performance and the material described within the applicant鈥檚 concept paper.
  • Cost-share or Matching. (0-10 pts): The evidence, quality, reasonableness, and sufficiency of the financial commitment from partners assembled to date, for establishing the proposed institute. This includes:
    • The extent to which the non-federal financial support provided to the AI MFG USA institute is rational in magnitude and nature, from specific known and anticipated sources, and will exceed the requested federal share for the proposed institute; and
    • Evidence of the potential to leverage non-federal sources of financial support to promote a stable and sustainable business model to mitigate the need for long-term federal funding.
  • Qualifications and Experience. (0-10 pts): The quality, degree, and appropriateness of the qualifications of the lead organization(s), organization director, key personnel, and of other key participating organizations and key personnel assembled to date. This includes:
    • The extent to which the proposed lead organization(s), organization director, and key personnel have successful track records leading programs or entities similar in nature to the purpose, scope, and/or work activities described for the AI MFG USA institute; and
    • The extent to which AI MFG USA institute partner organizations identified have relevant and significant capabilities to contribute to the intended mission and scope of the proposed institute.