NASA · NASA-894 · record R0492

AI assisted Image recognition for EEE parts kitting and auditing

National Aeronautics and Space Administration · GSFC: Goddard Space Flight Center

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: Not reported
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Science
Operational functions: Image and video analysis Derived by keyword rules; see methodology

Problem the AI is intended to solve

Due to the limits in personnel capacity, warehouse inventory contract (TRAX), and the limits in the Goddard Material Management System (MMS), EEE parts kitting and auditing is labor intensive, and error prone. This project aimed to utilize the image recognition potential to help reduce partial man-hour involved in the kitting and auditing process.

Expected benefits

The outcome of this project will benefit the Goddard EEE parts engineer, the Printed Wiring Assembly card lead, the EEE parts technician, the vendor who receives the kit, and the Quality Assurance (QA). The measurements KPI include: 1) The man-hour saved in generating the correct parts kitting list with all required information; 2) The accuracy of with the assistance from AI, comparing the old method. The overall benefit should consider a combination of both factors, not just focused on accuracy improvement.

System outputs

A parts kitting list in spreadsheet format, against released BOMs, including the Part Number, Quantity, Manufacture, Date code/lot, batch data.

Technology

AI classification: Computer visionSource: Computer Vision: AI that processes and interprets visual data (e.g., images and videos).
System name(s): Not reported
Custom-developed code: Not reported
Public source code: Not reported

Sourcing

How it was built: Not reported
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: Not reported
Authorization to Operate: Not reported
Demographic features: Not reported
Training and evaluation data: Not reported
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