USAF Condition-Based Maintenance Research Environment Air Force Research Laboratory 17 June 2009

Problem Statement CBM+ Policy/Definition AFRL CBM+ Study Re-cap AFRL CBM+ RE Strategy CBM+ RE 1 st Gen Capability AGENDA

3 Problem Statement 1.AFRL RESEARCHERS NEED REAL DATA –to develop diagnostic/prognostic algorithms –to verify performance of new capabilities in the field –to shorten development/insertion cycle time 2.AF SUSTAINING ENGINEERING NEEDS –Collaborative engineering tools –Improved system performance monitoring and assessment –Proactive lifecycle weapon system management 3.AF ENTERPRISE INTEGRATION REQUIREMENTS –Linkage between platforms and logistics enterprise –Integrated architectures defining information exchange

4 Condition Based Maintenance Plus (CBM+) DoDD – Maintenance of Military Materiel – Mar 2004 AFI – Integrated Product Support Planning and Assessment – Nov 2004 DODI – CBM+ Policy – Dec 2007 DoD CBM+ Guidebook – May “ the application and integration of appropriate processes, technologies, and knowledge-based capabilities to improve the reliability and maintenance effectiveness of DoD systems and components.” Policy & Guidance Formal Definition AF Solutions Develop & Sustain Warfighting Systems (D&SWS) AF Transformation Supply Chain Operations Systems Lifecycle Integrity Management (SLIM) CBM+ (Prognostics (RUL/SLA), Diagnostics)

5 5 CBM+ Capability Metrics Advanced Diagnostics/ Basic Prognostics: estimate the probabilistic distribution of RUL for an asset type (X within one standard deviation), based on past usage and on fleet wide averages. Predictive Prognostics: estimate the expected RUL for an individual asset (X within one standard deviation), based on past and future usages for the individual asset. Requires OEM lifing algorithms, material properties/Red Book curves. Diagnostics/Health Assessment: Determine current health of system or subcomponents through diagnostics. Condition Monitoring/State Detection: Compare features against expected values or operational limits. Anomaly detection. Reduced-Order or Estimation Models Applicability Signal-Based Anomaly Detection Evolutionary or Data-Driven Models Increasing complexity and cost Predictive Prognostics The required level of capability depends upon the technical problem, the desired outcome and economics

6 USAF CBM+ Framework AFRL capabilities provide critical information which can enhance decision support, dynamic mission planning and resource optimization AFRL capabilities provide critical information which can enhance decision support, dynamic mission planning and resource optimization or 4 AFRL Research Areas

7 CBM+ Operational View Level 1 Research Mission Planning Maintenance Logistics Integrated Systems Health Management Data Recorders Sensor Data Remaining Useful Life Data Manipulation Pre-Processing Feature Extraction Signal Characterization Diagnostics/ Health Assessment Determine current health of system or subcomponents Prognostics Project future health of the system, taking into account estimates of past and future operation profiles RUL Continuous Process Improvement Inspections Inspection Data Feedback loops in place to allow an S&T role in continuous process improvement Fleet Level Avionics System Level Engines Structures Condition Monitoring/ State Detection Compare features against expected values or operational limits Sense Assess Predict

Attributes: Federated Architecture Standard Data Exchange Single Point Entry and Security Verification Supports Spiral Development of CBM+ Capabilities Condition-Based Maintenance Plus Research Environment (CBM+ RE) Global Combat Support System – Data Services Engine Health Management Data Aircraft Structures Data OEM Data Avionics Data CBM+ RE Metadata Repository Working Storage RESEARCH ENTERPRISE INTEGRATION SYSTEMS ENGINEERING Other CBM+ Data Access to pedigreed data Validate research results Shorten development/insertion cycle time Support collaboration of engineering tools Improve system performance monitoring and assessment Proactive lifecycle weapon system management Integrated architectures define information exchange requirements Links platforms and logistic enterprise

9 9 CBM+RE Resource Discovery Application A web application providing a rich and intuitive user experience to subject matter experts for searching and displaying both static and dynamic enterprise resource links Built on top of the MDE Information Asset Discovery, it will leverage the vocabulary repository to drive ad hoc data discovery

10 CBM+RE Engineering Model Mashup Capability Web application that provides aggregation, transformation, and computational services over top of the data exposed by one or more sources. It focuses on run time development, drag-and-drop, and Subject Matter Expert empowerment.

11 What CBM+RE Engineering Mashup Provides Aggregation and Transformation of engineering data to provide new reusable data sources Uploading and Execution of 3 rd party algorithms 3 rd party intellectual property assurance Testing on live data WSDL Interrogator (Support dynamic service call) Credential proxy for data assurance Parallel processing Results of analysis that can be reused across the AF enterprise

12 Benefits of CBM+RE Mashup Cost Savings potentials to DoD using Mashup services –“Fast Track Development” by shortening the software development life cycle through “Reuse” of existing applications (services) to generate new applications (services) SOA and Web Service exposure standards to generate new applications (e.g., minutes with Mashup) vs. Traditional Web Application development to generate new applications (e.g., months without Mashup) 12

13 Summary AFRL CBM+ Study identified challenges associated with CBM+ implementation –Provided CBM+ framework and baseline enterprise architecture –CBM+ RE designed to give systems engineers and Weapon System Mgr access to production data for tool development and validation CBM+ RE is an integral part of the SLIM AFSO21 and USAF Logistics Transformation efforts CBM+ RE capability will be expanded on a ‘Use Case’ basis

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