Connecting Sustainment Deliverables to Troubleshooting with Condition Based Maintenance Plus

The Department of Defense (DoD) and other Aerospace & Defense (A&D) customers are continuously seeking to maximize system Operational Availability (Ao) and reduce total lifecycle ownership cost. A key driver to both metrics is the effectiveness and efficiency of the maintainers who sustain systems. This paper discusses a methodology to improve maintainer performance through the integration of information technology solutions and sustainment technical data deliverables (e.g., Failure Modes, Effects and Criticality Analysis - FMECA, Reliability Block Diagrams, Interactive Electronic Technical Manuals - IETMs, etc.). We describe how digitally integrated solutions can be utilized to improve fault management and troubleshooting efficacy via the deployment of an Automated Guided Troubleshooting Toolset and a Condition Based Maintenance Plus (CBM+) user interface. The proposed integrated architecture combines industry-leading commercial troubleshooting software with OEM-generated system design data and a live condition data stream generated by the system-under-observation to create a powerful and dynamic troubleshooting solution. The architecture dynamically generates and iterates fault isolation results and maintenance recommendations based on evolving inputs, automatically drawn from the system or manually injected by the maintainer. Once the maintainer has validated system-generated results, they are then able to directly access relevant IETM work packages describing required service procedures, review part/tool availability, create work-orders to track completion of required repairs and automate the creation of reports. An Automated Guided Troubleshooting approach creates a cohesive, end-to-end user experience where the maintainer's workflow is guided via software from initial fault notification, through troubleshooting and onto service planning and execution. Maintainer workload and mental burden is reduced through automated synthesis and aggregation of data. The risk of human error is minimized via human-machine and machine-machine collaboration. The speed and accuracy of troubleshooting is increased. All of these factors combine to improve system availability and reduce costs associated with unnecessary service resulting from erroneous fault isolation and the speed of maintenance.