Sources Sought: Aviation Maintenance & Supply Ontology
NCMS is assisting the Department of Defense (DoD) locate technology that can connect disparate data and uniformly agree on the meaning of critical terms to speed the application of Artificial Intelligence (AI) and Machine Learning (ML) within the field of maintenance and sustainment. In the area of logistics, encompassing maintenance and sustainment, disconnected and non-uniform data limits the utility of data analysis and the practicality of end-to-end solutions for common logistics problems. Non-uniform data is especially problematic when applying AI and ML approaches that optimally rely on the ingestion of a large amount of standardized, structured data.
The objectives for this technology are:
- Develop a repeatable ontology that enables end-to-end use of logistics data at an enterprise level for the purposes of AI/ML.
- Document this process and data sources.
The logistics domain for this project is aviation, more specifically supply and maintenance data for a rotary platform, the H60 helicopter. The government will provide H60 platform data, maintenance and sustainment domain expertise, data dictionaries from existing ERPs, and results from a case study in the domain.
Specific emphasis on the following:
- Data Obtention
- Supply transactions
- Maintenance transactions
- Data Mapping and Standardization of Terms
- Ontology Refinement and Process Mapping, applied to aviation case
- Delivery of Final Products
Key deliverables include:
- Connected Data roadmap, both data sources and data elements within these sources.
- Supply, Maintenance, Inventory, Availability and Cost Data Dictionaries
- Data Process map
This technology will provide the critical first step towards developing end-to-end usable data. Once a process is established to create a holistic ontology for maintenance and sustainment, the DoD can leverage current and future data to enable AI to predict failure efficiently. The outcome of the process will also provide an outline of future requirements for ERPs.
Responses to Sources Sought should provide:
• A value-based submission (completed Cost Summary Form)
• Background of capability development
• Understanding of logistics data analysis and ontology
• Cost Summary Form
Interested parties should respond on or before May 10, 2019.