Search Contract Opportunities

AI for the Depot: Using ETAR for Digital Health Records

ID: AF221-D010 • Type: SBIR / STTR Topic • Match:  85%
Opportunity Assistant

Hello! Please let me know your questions about this opportunity. I will answer based on the available opportunity documents.

Please sign-in to link federal registration and award history to assistant. Sign in to upload a capability statement or catalogue for your company

Some suggestions:
Please summarize the work to be completed under this opportunity
Do the documents mention an incumbent contractor?
Does this contract have any security clearance requirements?
I'd like to anonymously submit a question to the procurement officer(s)
Loading

Description

TECH FOCUS AREAS: General Warfighting Requirements (GWR) TECHNOLOGY AREAS: Materials; Air Platform OBJECTIVE: This effort will deliver a prototype Digital Health Record application to provide all Engineering Technical Assistance Request (or ETAR) information, non-destructive inspection (NDI) results, Airworthiness information and 3D images to determine the health of each aircraft. The Digital health record application will provide an organized and indexed data for Artificial Intelligence & Machine Learning for disposition decisions/actions and contribute to predictive Maintenance. DESCRIPTION: This project will include: 1. Designing and prototyping a Digital Health Record application to provide all ETAR information, NDI results, Airworthiness information and 3D images to determine the health of KC-135 2. Identify all relevant data sources and connect disparate data to create relationships to expand and operationalize AI/ML and 3. Use machine learning, historical performance data and contextual data to predict maintenance and alert for proactive identification of problem parts. While the data is currently being tracked, it is not analyzed to help make informed planning decisions- and this in this case KC-135 does not use the data to decide when to retire a plane. Engineering dispositions are burdened with repetitive assistance requests and responses, incorrect entry, lack of standards and quality. With increased data standards and quality, trending on historical mx actions it can result in faster/more accurate disposition. With the addition of technology and build out of the aircraft technical baseline (as sustained), the data can begin to be aggregated and analyzed to show predictive results. PHASE I: This topic is intended for technology proven ready to move directly into a Phase II. Therefore, a Phase I award is not required. The offeror is required to provide detail and documentation in the Direct to Phase II proposal which demonstrates accomplishment of a Phase I-like effort, including a feasibility study. This includes determining, insofar as possible, the scientific and technical merit and feasibility of ideas appearing to have commercial potential. PHASE II: Eligibility for D2P2 is predicated on the offeror having performed a Phase I-like effort predominantly separate from the SBIR Programs. Under the Phase II effort, the offeror shall sufficiently develop the technical approach, product, or process in order to conduct a small number of advanced manufacturing and/or sustainment relevant demonstrations. Identification of manufacturing/production issues and or business model modifications required to further improve product or process relevance to improved sustainment costs, availability, or safety, should be documented. Air Force sustainment stakeholder engagement is paramount to successful validation of the technical approach. These Phase II awards are intended to provide a path to commercialization, not the final step for the proposed solution. PHASE III DUAL USE APPLICATIONS: The contractor will pursue commercialization of the various technologies developed in Phase II for transitioning expanded mission capability to a broad range of potential government and civilian users and alternate mission applications. Direct access with end users and government customers will be provided with opportunities to receive Phase III awards for providing the government additional research & development, or direct procurement of products and services developed in coordination with the program. REFERENCES: Peixoto, R., Cruz, C., Silva, N. Adaptive learning process for the evolution of ontology-described classification model in big data context (2016) Proceedings of 2016 SAI Computing Conference, SAI 2016, art. no. 7556031, pp. 532-540. Cited 2 times. DOI: 10.1109/SAI.2016.7556031 14th Extended Semantic Web Conference, ESWC 2017 (2017) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10250 LNCS, pp. 1-278. Peixoto, R., Cruz, C., Silva, N. Semantic HMC: Ontology-described hierarchy maintenance in big data context (2015) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9416, pp. 492-501. Cited 2 times. DOI: 10.1007/978-3-319-26138-6_53 Boyles, R.R., Thessen, A.E., Waldrop, A., Haendel, M.A. Ontology-based data integration for advancing toxicological knowledge (2019) Current Opinion in Toxicology, 16, pp. 67-74. Cited 4 times. DOI: 10.1016/j.cotox.2019.05.005 ACM International Conference Proceeding Series (2018) ACM International Conference Proceeding Series, 152 p. Conway, M., O'Connor, D. Social media, big data, and mental health: Current advances and ethical implications (2016) Current Opinion in Psychology, 9, pp. 77-82. Cited 47 times. DOI: 10.1016/j.copsyc.2016.01.004 Kim, Y., Lee, J., Lee, E.-B., Lee, J.-H. Application of Natural Language Processing (NLP) and Text-Mining of Big-Data to Engineering-Procurement- Construction (EPC) Bid and Contract Documents (2020) Proceedings - 2020 6th Conference on Data Science and Machine Learning Applications, CDMA 2020, art. no. 9044209, pp. 123-128. DOI: 10.1109/CDMA47397.2020.00027 KEYWORDS: Artificial Intelligence (AI); Machine Learning (ML)

Overview

Response Deadline
Feb. 10, 2022 Past Due
Posted
Dec. 1, 2021
Open
Jan. 12, 2022
Set Aside
Small Business (SBA)
Place of Performance
Not Provided
Source
Alt Source

Program
SBIR Phase I / II
Structure
Contract
Phase Detail
Phase I: Establish the technical merit, feasibility, and commercial potential of the proposed R/R&D efforts and determine the quality of performance of the small business awardee organization.
Phase II: Continue the R/R&D efforts initiated in Phase I. Funding is based on the results achieved in Phase I and the scientific and technical merit and commercial potential of the project proposed in Phase II. Typically, only Phase I awardees are eligible for a Phase II award
Duration
6 Months - 1 Year
Size Limit
500 Employees
On 12/1/21 Department of the Air Force issued SBIR / STTR Topic AF221-D010 for AI for the Depot: Using ETAR for Digital Health Records due 2/10/22.

Documents

Posted documents for SBIR / STTR Topic AF221-D010

Question & Answer

The AI Q&A Assistant has moved to the bottom right of the page

Contract Awards

Prime contracts awarded through SBIR / STTR Topic AF221-D010

Incumbent or Similar Awards

Potential Bidders and Partners

Awardees that have won contracts similar to SBIR / STTR Topic AF221-D010

Similar Active Opportunities

Open contract opportunities similar to SBIR / STTR Topic AF221-D010