Just In Time (JIT) Aircraft Maintenance System

Period of Performance: 10/27/2014 - 06/16/2016

$750K

Phase 2 SBIR

Recipient Firm

Cybernet Systems Corp.
3741 Plaza Drive Array
Ann Arbor, MI 48108
Principal Investigator

Research Topics

Abstract

ABSTRACT: The High Velocity Maintenance (HVM) initiative strives to reduce aircraft downtime while maintaining the most capable air fleet that achieves Air Force mission requirements. Unscheduled maintenance, due to issues uncovered midway into the maintenance work, introduces the most delays that negatively impact HVM turnaround time. To increase the predictability of the actual maintenance required, we propose to develop an Automated Maintenance Prediction System (AMP) that leverages our core analysis algorithms designed in Phase I and our patented Automated System Test and Repair System (A-STAR) developed for the Navy to achieve similar fault prognostic objectives. At the end of Phase II, the Sponsor will possess the first implementation of the Automated Maintenance Prediction System (AMP) that will enable automated root-cause analysis and risk assessment of repair actions. We plan to mature and evolve the AMP functionality to suit the target aircraft application, beginning with basic functionality and adding more sophisticated root-cause analysis and risk-based maintenance capabilities with each development milestones. BENEFIT: The major goal of this project is to develop an Automated Maintenance Prediction System (AMP) to provide enhanced root-cause diagnostics and optimized, risk-based maintenance assessments. We will extend the work performed during the Phase I to create a fully functional AMP system that accelerates the determination and execution of flight line maintenance actions. The prototype delivered to the Sponsor at the conclusion of this Phase II will show we have developed effective techniques for an enhanced diagnostics tool approach that has the capacity to assess the most effective maintenance path considering history, likelihood of success, and time constraints to determine the optimal corrective actions. This will result in the development of a flexible toolset of algorithms for enabling just-in-time aircraft maintenance. Some of the main tasks include interfacing with the on-board computing and diagnostics systems data and the continued development of maintenance prediction algorithms. Additionally, Cybernet intends to leverage its A-STAR technology to design and develop the fault detection and maintenance capabilities of the AMP system. This will also aid in the process of generating a more multi-purpose prediction system for fault detection, isolation, and repair. The Phase II effort will focus on the development of AMP system capabilities and an integration plan for the Air Force Logistics Center at Robins. Phase II will also provide the opportunity to present the technology to commercial users, such as GE and other aircraft systems manufacturers. We will work with the Air Force maintainer community to transition this technology into an active program that provides ongoing support for HVM maintenance initiatives at Robins.