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Find similar grantsSmall Business Innovation Research (SBIR) Artificial Intelligence (AI) for Additive Manufacturing (AM) Part Selection is sponsored by Department of Defense (DoD) Army. This SBIR topic aims to develop AI capabilities that significantly improve the method for identifying and analyzing additive manufacturing candidate parts for the Army.
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Artificial Intelligence (AI) for Additive Manufacturing (AM) Part Selection – Army SBIR|STTR Program Artificial Intelligence/Machine Learning, Army SBIR, Phase I Artificial Intelligence (AI) for Additive Manufacturing (AM) Part Selection Application Due Date: 03/01/2022 The objective of this Phase I topic is to develop Artificial Intelligence (AI) capabilities that analyzes technical data information and assesses the candidacy of a component for additive manufacturing, automate manual processes in order to reduce the time of engineering analysis by up to 80%, increase the pool of Additive Manufacturing (AM) candidates which leads to new opportunities and program creation, optimize the “Can Print / Should Print” analysis for higher yield of impactful AM candidates, and improve logistics trails and increase readiness through increased usage of additive manufacturing.
The purpose of this Phase I topic is to develop an AI capability that greatly improves the method for identifying and analyzing AM candidate parts. Currently, there is a manual process in place performed by engineers who are AM Subject Matter Experts. AM SME engineers search through Army databases to pull technical and logistics data and analyze data to determine printability.
The development of an AI system which can automate the technical data analysis process through critical factors will greatly benefit efforts. AM can be integrated in a multitude of DoD programs and supply chains will be greatly improved with the increase of AM candidate parts, saving time, money and resources.
When completing the Phase I proposal, submission must demonstrate developed capability where technical data can be processed by an AI system to provide information and analysis on AM candidacy. Criteria may include the following: Material, Tolerance, Size, System, Supplier, and Item owner.
When completing Phase II of this topic, submission must build upon and improve the AI system to increase efficiency and throughput and expand candidacy criteria. The effort should focus on the printability of the part and deviations against component requirements.
Success In order to successfully complete Phase III, submission must show the performance of scaling and integration of the AI system with current Army Digital Management Systems. For more information, and to submit your full proposal package, visit the DSIP Portal . https://www.
ieomsociety. org/singapore2021/papers/476.
pdf The objective of this Phase I topic is to develop Artificial Intelligence (AI) capabilities that analyzes technical data information and assesses the candidacy of a component for additive manufacturing, automate manual processes in order to reduce the time of engineering analysis by up to 80%, increase the pool of Additive Manufacturing (AM) candidates which leads to new opportunities and program creation, optimize the “Can Print / Should Print” analysis for higher yield of impactful AM candidates, and improve logistics trails and increase readiness through increased usage of additive manufacturing.
The purpose of this Phase I topic is to develop an AI capability that greatly improves the method for identifying and analyzing AM candidate parts. Currently, there is a manual process in place performed by engineers who are AM Subject Matter Experts. AM SME engineers search through Army databases to pull technical and logistics data and analyze data to determine printability.
The development of an AI system which can automate the technical data analysis process through critical factors will greatly benefit efforts. AM can be integrated in a multitude of DoD programs and supply chains will be greatly improved with the increase of AM candidate parts, saving time, money and resources.
When completing the Phase I proposal, submission must demonstrate developed capability where technical data can be processed by an AI system to provide information and analysis on AM candidacy. Criteria may include the following: Material, Tolerance, Size, System, Supplier, and Item owner.
When completing Phase II of this topic, submission must build upon and improve the AI system to increase efficiency and throughput and expand candidacy criteria. The effort should focus on the printability of the part and deviations against component requirements.
Success In order to successfully complete Phase III, submission must show the performance of scaling and integration of the AI system with current Army Digital Management Systems. For more information, and to submit your full proposal package, visit the DSIP Portal . https://www.
ieomsociety. org/singapore2021/papers/476. pdf Assistant Secretary of the Army for Acquisition, Logistics, and Technology ASA(ALT) releases contract opportunities on an ad-hoc basis to meet Army research and development needs.
Army Futures Command (AFC) releases topics during three specific solicitation periods throughout the fiscal year to address the Army’s current and anticipated war-fighting technology needs. Army STTR follows AFC’s topic release schedule but partners with a university, federally funded research and development center, or a qualified non-profit research institution as part of their contract.
Is the opportunity to establish the scientific, technical, commercial merit and feasibility of your proposed innovation. Is focused on the development, demonstration and delivery of your innovation from Phase I. Represents the commercialization phase of the program in which the company can market their products or services developed in Phase II, either to the government or in the commercial sector.
Allows small businesses to submit to Direct to Phase II applications if they performed the Phase I research through other funding sources. Provides funding to projects that require additional funding during their open Phase II contract. A Phase II Awardee may receive one additional, sequential Phase II award to continue the work of an initial Phase II award.
The sequential Phase II award has the same guideline amounts and limits as an initial Phase II award.
Artificial Intelligence/Machine Learning (supply chain management, logistics coordination, target identifications and simulation) Advanced Materials and Manufacturing (additive manufacturing) Autonomy (unmanned systems, drones, ground vehicle capabilities) Chemical and Biological (detection, defense) Cyber (biometric authentication, secure communications) Electronics (microelectronics, Very-Large-Scale Integration (VLSI)) Electronic Warfare (jamming, spoofing) Human Performance (wearables) Immersive (augmented reality, virtual reality, mixed reality) Network Technologies (antennas, radio frequency, communications systems) Position, Navigation, and Timing (GPS) Power (batteries, generators) Software Modernization (high performance computing, data management and visualization) Sensors (infrared sensing) Weapons Systems (hypersonics, munitions and projectiles, directed energy)
According to the current listing, eligibility includes: U. S. small businesses. Specific eligibility requirements will be outlined in the official solicitation. Confirm the full requirements in the official notice before applying.
The current listing shows varies by Phase (Phase I typically up to $250,000, Phase II typically $750,000 to $1.8 million). Verify award ceilings, matching requirements, and allowable costs in the official notice.
Small Business Innovation Research (SBIR) Artificial Intelligence (AI) for Additive Manufacturing (AM) Part Selection is funded by Department of Defense (DoD) Army. Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
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