Aircraft Condition Analysis and Management System (ACAMS)

Monitoring the continued health of aircraft subsystems and identifying problems before they affect airworthiness has been a long-term goal of both the U.S. military and commercial aviation industry. Now, that goal has come closer to being realized with the ARINC Aircraft Condition Analysis and Management System (ACAMS), an aircraft diagnosis and prognosis system. ACAMS is unique in the industry because it offers real-time diagnosis and prognosis that accounts for subsystem or component interactions within a complex system.

Working with NASA's Langley Research Center under the Aviation Safety Program, ARINC is developing ACAMS to automatically diagnose and predict faults in complex aircraft subsystems, including flight subsystems, landing gear, and structural elements. ACAMS can also be configured for propulsion health management. Unlike conventional diagnostic techniques, ACAMS accesses and analyzes a myriad of information sources to isolate and predict fault behavior at the system level rather than at the LRU level.

ACAMS consists of onboard and ground-based elements. The onboard system collects information from numerous data sources. Proprietary ACAMS models and algorithms continually analyze these data in real time to identify and help manage anomalies that could adversely affect continued airworthiness. In certain cases, ACAMS can predict faults in the monitored subsystems before they occur.

The diagnostic and prognostic results delivered by data link service are automatically prioritized in accordance with user-specific criteria to assess the impact of fault conditions on future operation. If a critical anomaly is identified, that information is automatically transmitted to the ground crew. Aircraft maintainance and ground crews then use this information for operational and maintenance planning and take any corrective action needed.

On the ground, an off-board ACAMS combines all of the collected and analyzed in-flight data with historical information, such as component maintenance history, reliability and maintainability data, and—for commercial air carriers—quick-access recorder (QAR) and flight operations quality assurance (FOQA) data. The system analyzes these data for higher fidelity diagnosis and prognosis, helping to facilitate long-term, fleet-wide aircraft dispositioning and improve maintenance scheduling and parts supply management.