DOT · DOT-1000010 · record R1212

Technical Operations Predictive Maintenance

Department of Transportation · FAA AJO

Overview

Development stage: In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: 2024-11-21 (day precision)Source: 11/21/2024 12:00:00 AM
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Transportation
Operational functions: Forecasting and prediction Derived by keyword rules; see methodology

Problem the AI is intended to solve

"Utilize equipment telemetry data, statistical modeling and Machine Learning to predict equipment failures before they occur. This will improve operational efficiency and safety by reducing unscheduled outages and/or shortening outage times as replacemen

Expected benefits

Not reported

System outputs

Utilize equipment telemetry data, statistical modeling and Machine Learning to predict equipment failures before they occur. This will improve operational efficiency and safety by reducing unscheduled outages and/or shortening outage times as replacement

Technology

AI classification: Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…
System name(s): Not reported
Custom-developed code: No
Public source code: Not reported

Sourcing

How it was built: Contract and in-houseSource: c) Developed with both contracting and in-house resources
Vendor (as reported): Not reported
Vendors (standardized): None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: Not reported
Privacy Impact Assessment: No
Authorization to Operate: Not reported
Demographic features: Not reported
Training and evaluation data: Utilize equipment telemetry data, statistical modeling and Machine Learning to predict equipment failures before they occur. This will improve operational efficiency and safety by reducing unscheduled outages and/or shortening outage times as replacement
Federal Data Catalog: Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported