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Award Data
The Award database is continually updated throughout the year. As a result, data for FY24 is not expected to be complete until March, 2025.
Download all SBIR.gov award data either with award abstracts (290MB)
or without award abstracts (65MB).
A data dictionary and additional information is located on the Data Resource Page. Files are refreshed monthly.
The SBIR.gov award data files now contain the required fields to calculate award timeliness for individual awards or for an agency or branch. Additional information on calculating award timeliness is available on the Data Resource Page.
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Additive Manufacturing Process Monitoring and Control Technologies
SBC: ARCTOS Technology Solutions, LLC Topic: DLA181002This project aims to make Laser Powder Bed Fusion (LPBF) additive manufacturing a practical tool for supply chain management for the Defense Logistics Agency.The key step is developing process standardization to make LBPF quality vendor independent. This project will seek to demonstrate the use of a promising high speed melt pool monitoring device as a practical means to establish such process sta ...
SBIR Phase I 2018 Department of DefenseDefense Logistics Agency -
Additive Manufacturing Process Monitoring and Control Technologies
SBC: Made In Space, Inc. Topic: DLA181002Made In Space, Inc. (MIS) and Siemens PLM Software propose an integrated Automated Processing. Monitoring, Control and Remediation System (Aul) to provide a process monitoring and control capability. Made In Space, Inc. leads the effort based on integrating Made In Space, Inc., proven inspection sensors systems with a Digital Thread for Additive Manufacturing (DTAM) system, co-developed by Siemens ...
SBIR Phase I 2018 Department of DefenseDefense Logistics Agency -
Additive Manufacturing Sensor Fusion Technologies for Process Monitoring and Control.
SBC: SENVOL LLC Topic: DLA18A001The Department of Defense (DoD) has a demand for out-of-production parts to maintain mission readiness of various weapons platforms. Additive manufacturing (AM) is an exciting and promising manufacturing technique that can make out-of-production parts and holds the potential to solve supply chain issues, such as high costs (i.e. for low-volume parts) and sole sourcing risks. The ability of AM to s ...
STTR Phase I 2018 Department of DefenseDefense Logistics Agency -
Additive Manufacturing Sensor Fusion Technologies for Process Monitoring and Control.
SBC: ARCTOS Technology Solutions, LLC Topic: DLA18A001Universal Technology Corporation (UTC) has teamed with the University of Dayton Research Institute (UDRI), Stratonics, and Macy Consulting to demonstrate not only the transitionability into commercial systems, but also to develop the data analytics and monitoring and control requirements to extract the full value fromseveral sensors, including the Stratonics ThermaViz, acoustic and profilometry se ...
STTR Phase I 2018 Department of DefenseDefense Logistics Agency -
Advanced Instrumentation for Non-Nulling Stack Velocity Testing
SBC: AIRFLOW SCIENCES CORP Topic: NoneIndustrial facilities, manufacturing plants, and electric power plants that burn fossil fuels exhaust the combustion products to atmosphere through their smokestacks. Stack pollutant emissions are quantified using manual testing methods developed in the 1960s, which are prone to error if non-axial flow exists in a stack.Recently, NIST has been working on an improved technique of performing 3D flow ...
SBIR Phase I 2019 Department of CommerceNational Institute of Standards and Technology -
Advanced Simulated Patient Intelligent Response Engine (ASPIRE)
SBC: VCOM3D INC Topic: DHA191002The goal of medical simulation-based training such as high-fidelity manikin simulators, part task trainers, and screen-based virtual patients, is to approximate real-life treatment experiences without risk to live patients. While the use of sensors has ma
SBIR Phase I 2019 Department of DefenseDefense Health Agency -
Algorithms for Look-down Infrared Target Exploitation
SBC: SIGNATURE RESEARCH, INC. Topic: 1Signature Research, Inc. (SGR) and Michigan Technological University (MTU) propose a Phase I STTR effort to develop a learning algorithm which exploits the spatio-spectral characteristics inherent within IR imagery and motion imagery.Our archive of modelled and labeled data sets will allow our team to thoroughly capture the variable elements that will drive machine learning performance.The overall ...
STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency -
Anatomic 3D Synthetic Tissue Printer for Medical Training
SBC: SERAPH ROBOTICS, INC. Topic: DHP12003Military medical personnel are not prepared to provide trauma care to severely injured soldiers in wartime due to inadequate and unrealistic battlefield training opportunities during peacetime. Training has historically been done on human cadavers and live animals, but cadavers are in limited supply, and animal rights groups and physicians are increasing pressure to end the practice of using live ...
SBIR Phase I 2013 Department of DefenseDefense Health Agency -
Asynchronous Multi-transmitter Multi-aperture Synthetic 3D Imaging System
SBC: VOXTEL, INC. Topic: NGA183001Traditional active 3D imaging systems, such as airborne and terrestrial lidar scanners, use a transmitter and receiver typically co-located on the same platform and connected in synchronous communications. However, recent advances in laser, detector, and airborne systems technology have opened the door to smaller, higher-performance and significantly lower-cost airborne lidar systems in which it i ...
SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency -
Augmented Reality Surgical Visualization
SBC: CFD RESEARCH CORPORATION Topic: DHA191001Care for the wounded Warfighters in austere and remote settings makes medical knowledge, skills and efficiency of the military medical professional paramount. For wounds that extend deep into internal anatomy, proper visualization of internal anatomy can
SBIR Phase I 2019 Department of DefenseDefense Health Agency