Our Government Division is pleased to announce the award of the Phase II AFWERX Small Business Innovation Research (SBIR) to extend and adapt our Maintenance Data Capture pipeline prototype concept for Air Force use.
Artificial Intelligence to Predict Maintenance Record Fields
This Phase II effort will pilot the Maintenance Data Capture agent at the Air Force Life Cycle Management Center (AFLCMC) with both a voice and traditional user interface that eases maintainer documentation and uses artificial intelligence to predict the maintenance record fields required by the maintenance transactional system.
Phase I: Human Factors and Technical Capabilities
ILW successfully completed the Phase I feasibility effort, which focused on two broad areas of product development: human factors and technical capability. The human factors evaluation focused on subject matter expert interviews and summarization of interview data. The technical capability evaluation focused specifically on the natural language processing functionality of the tool.
As part of the three-month Phase I feasibility study, ILW data scientists extracted free text from Air Force maintenance transactions and mission debrief data to perform classification, training, and evaluation to statistically infer drivers and predict likelihood of occurrence of specific maintenance actions based on correlations and ambiguities between free text and categorical variables to improve the accuracy of the data. For more information on Phase I, check out our case study and video.
Illumination Works is excited to continue its partnership with the Air Force on this important task. The Air Force community has a need for real-time, modern data capture to provide the young workforce with the tools and technologies of their generation.
Phase II: Voice and Graphical User Interface
For this Phase II effort, ILW will enhance the automated Maintenance Data Capture concept to align to a procedural reasoning system, agent-based architecture to provide an extensible platform to prototype and demonstrate voice and graphical user interfaces within the Air Force maintenance environment. Specific focus will include entity extraction, classification, and prediction providing an intuitive data entry mechanism in multiple medias for Air Force maintainers.
Background: ILW Innovation Lab
ILW’s automated Maintenance Data Capture and prediction engine is a product of the ILW Innovation Lab, which was originally prototyped based on machine learning work performed for the Air Force. This tool successfully enabled more efficient and accurate capture and structure of maintenance records by leveraging native mobile technologies to collect maintenance actions, observations, and notes, and simplified and automated the data collection processes. This tool is ready to be leveraged by the Air Force Logistics Community and expanded to other data collection uses and domains.
About Illumination Works
Illumination Works is a trusted technology partner in user-centric digital transformation, delivering impactful business results to clients through a wide range of services including big data information frameworks, data science, data visualization, and application/cloud development, all while focusing the approach on the end-user perspective. Established in 2006, ILW has offices in Beavercreek, Cincinnati, and Columbus.
