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Engineering Laboratory

Systems Integration Division

Projects/Programs

Displaying 1 - 25 of 32

Advanced Informatics and Artificial Intelligence for Additive Manufacturing

Ongoing
Objective To develop and deploy the metrics, models, reference data, and best practices for implementing and adopting advanced informatics (including product definition, digital twins, ontology, and machine learning) and artificial intelligence to enhance additive manufacturing design, process...

Advanced Manufacturing Data Infrastructure and Analytics Program

Ongoing
Objective The Advanced Manufacturing Data Infrastructure and Analytics (AMDIA) Program will develop and deploy measurement science to advance a data infrastructure that will improve the productivity, resiliency, and sustainability of manufacturing operations and supply chains to enhance U.S...

Agri-Food Manufacturing System and Supply Chain Integration

Ongoing
Objective: Deploy new standards and reference data supporting agri-food manufacturing systems to enable industry to more efficiently and cost effectively produce food-based products of higher quality and with improved food safety. Technical Idea: Today, food producers face many challenges include...

Artificial Intelligence (AI) for Manufacturing

Ongoing
Objective To develop the methods, metrics, models, tools, and consensus-based standards necessary to empower the next-generation manufacturing systems with the trustworthy and interoperable advanced data infrastructure and AI technologies. More specifically, the project focuses on developing...

Data Analytics for Smart Manufacturing Systems

Ongoing
Objective: Develop standards, software tools, methodologies, and guidelines to enable small and medium enterprises to apply data analytics services to improve decision-making and performance in smart manufacturing systems. Technical Idea: Manufacturers need enhanced decision-support tools that would...

Data Driven Decision Support for Additive Manufacturing

Completed
Objective To develop and deploy the metrics, models, and best practices for using product definition, advanced analytics, and machine learning methods in additive manufacturing design and process planning to reduce lead times and support first-part-correct goals. Technical Idea Future advancements...

Data Infrastructure for Biomanufacturing

Ongoing
Objective Develop measurement science for new, computationally more precise, and AI-understandable data standards that would allow for quick and easy 1) configuration of integrated equipment and software components within the production system and 2) knowledge discovery, visualization, and...
A Life Cycle Engineering perspective

Data Infrastructure for Critical Material Recovery

Ongoing
Objective The objective of this project is to strengthen critical materials recovery data infrastructure via the development of suitable data sets, metrics, indicators, models and technical standards to help define critical materials and information pathways across entire product life cycles and...

Data Integration and Management for Additive Manufacturing

Completed
Objective Data plays the most critical role in linking AM lifecycle and value chain activities and streamlining the AM development process. While the AM data from a single build is essential for establishing part traceability, when methodically collected, the full processing history of thousands of...

Data Integration, Management and Fusion for AM Industrialization

Ongoing
Objective Developing methods, models, software tools, open data, and best practices for data integration, management, and fusion in additive manufacturing to accelerate AM Industrialization. Technical Idea Our technical idea is to enable an integrated, streamlined, and effective AM development and...

Data-Driven Design for Product Recovery

Ongoing
Objective To develop standards, metrics, and data-driven methods that can be implemented in early product design stages to increase the efficacy of end-of-use product recovery pathways and keep valuable products in the economy and recover valuable materials. Technical Idea The Data-Driven Design for...
Manufacturing Digital Twins

Digital Twins for Advanced Manufacturing

Ongoing
Objective To provide measurement science and open standards to help U.S. manufacturers better define, measure, analyze, and control advanced manufacturing systems using trustworthy digital twins and enable a marketplace for digital twin users and technology providers. Technical Idea This project...

Extended Digital Thread

Ongoing
OBJECTIVE: To deliver standards, methods, and tools that improve smart manufacturing efficiency, agility, and reliability, by increasing the quality of information representations across more of the product lifecycle, including design, production, and use of resulting products. WHAT IS THE TECHNICAL...
Human-Machine

Human/Machine Teaming for Manufacturing Digital Twins

Completed
Objective To remove barriers to the use of complex tools in manufacturing, such as digital twins, by developing the foundation for integrating generative AI, declarative domain-specific languages, and human/AI teaming. Technical Idea The mission of NIST’s Engineering Laboratory includes researching...

Knowledge Extraction and Application

Completed
Objective - To develop and deploy advances in standards, measurement science, and software tools using actionable, computable, domain knowledge and data in operations and logistics to improve the reliability, quality, and efficiency of advanced manufacturing systems. What is the technical idea? The...

Measurement Science for Additive Manufacturing Program

Ongoing
Objective To develop and deploy measurement science that will enable rapid design-to-product transformation through advances in: material characterization; in-process sensing, monitoring, and model-based optimal control; performance qualification of materials, machines, processes and parts; and end...

Model-Based Enterprise Program

Ongoing
OBJECTIVE: The Model-Based Enterprise (MBE) Program will develop and deploy advances in standards, test methods, and measurement science that enable manufacturers to integrate system, service, product, process, and logistics models across the manufacturing enterprise. WHAT IS THE NEW TECHNICAL IDEA...

Model-Based Manufacturing Services

Ongoing
Manufacturing systems need to transform towards a new service-oriented architecture to benefit from new smart manufacturing technologies such as IIoT, AI, and Big Data Analytics. A service-oriented manufacturing system (SOMS) is a dynamic composition of networked manufacturing software and cyber...

Modeling Methodology for Smart Manufacturing

Ongoing
Objective: Develop new modeling methodologies, guidelines, and software tools to enable manufacturers to more easily apply analytical methods to manufacturing operations and processes. Technical Idea: Manufacturers would realize great benefit were the costs of composing analytical models reduced...

Operations-driven Performance Measurement for Smart Manufacturing Systems

Ongoing
Objective: Develop and deploy standards, guidelines, and reference data for measuring the performance of manufacturing systems to inform the design and aid in analysis of factory improvements. Technical Idea: Manufacturers are adopting smart systems to drive gains in agility, productivity, quality...

Product Lifecycle Data Exploration and Visualization

Ongoing
With the continuing emergence of low-cost, lightweight, and powerful hardware at the edge, opportunities grow for advancing methods, standards, and software tools for data exploration and visualization in smart manufacturing systems. Small and medium-sized enterprises have limited resources to...
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