N102-111 TITLE: Ground Tactical Vehicle Prognostics and Health Management

TECHNOLOGY AREAS: Information Systems, Materials/Processes

ACQUISITION PROGRAM: Autonomic Logistics (potential I), Embedded Platform Logistics System (IV)

RESTRICTION ON PERFORMANCE BY FOREIGN CITIZENS (i.e., those holding non-U.S. Passports): This topic is "ITAR Restricted." The information and materials provided pursuant to or resulting from this topic are restricted under the International Traffic in Arms Regulations (ITAR), 22 CFR Parts 120 - 130, which control the export of defense-related material and services, including the export of sensitive technical data. Foreign Citizens may perform work under an award resulting from this topic only if they hold the "Permanent Resident Card", or are designated as "Protected Individuals" as defined by 8 U.S.C. 1324b(a)(3). If a proposal for this topic contains participation by a foreign citizen who is not in one of the above two categories, the proposal will be rejected.

OBJECTIVE: This topic seeks technology to identify maintenance trends in both platforms/components and prognostics to determine the likelihood that any one particular vehicle/system or tactical grouping of vehicles/systems will complete its assigned mission.

DESCRIPTION: Aging systems, spare parts shortages, and high operating tempo are placing increasing pressure on the material readiness of our force. The long-term sustainability of the equipment is a continuing challenge requiring new initiatives to effectively address both equipment and mission readiness. With the implementation of the Embedded Platform Logistics System (EPLS) on USMC ground tactical vehicles, the monitoring and collection of system/subsystem/assembly mission critical data elements is now available for further analysis. To realize the full potential of this data, further research and development of tools to analyze datasets for trends and projected performance is needed. The ability to mine, process, mechanically model and statistically analyze this aggregated data from a fleet perspective to determine maintenance trends, failure mechanisms, support system lifecycle management, and better understand the probability that an item of equipment will/will not fail over the course of a mission has significant benefit to the operating forces. Such prognostic and trend analysis tools would significantly enhance the capabilities provided by the Autonomic Logistics Program of Record and provide the warfighter with an application-level tool to support tactical decision making and improve mission performance of sensor-equipped vehicles.

PHASE I: 1) Develop and construct a set of statistical analysis tools (algorithms, models, data mining techniques, etc.) for identifying maintenance trends. 2) Develop and construct a set of prognostic tools (algorithms, models, etc.) for determining remaining useful life.

PHASE II: Develop proof-of-concept demonstrators based on a set of realistic, operationally based scenarios and mission profiles.

PHASE III: Integrate proof-of-concept demonstrators with existing application(s).

PRIVATE SECTOR COMMERCIAL POTENTIAL/DUAL-USE APPLICATIONS: Equipment reliability and availability are significant aspects of commercial product success. Application of statistical trending and/or prognostic tools during both the design process and/or as an embedded attribute of the final product leads to a product line that incorporates machine learning to improve overall product performance.

REFERENCES:
1. Capability Development Document for Autonomic Logistics � Marine Corps

2. Capability Development Document for Electronic maintenance Support System

3. Initial Capability Document for Sense and Respond Logistics

4. Condition Based Maintenance Plus DOD Guidebook

KEYWORDS: Prognostics, statistical analysis, algorithm, data mining, data analysis, trending, decision support tools, prediction, remaining useful life

** TOPIC AUTHOR (TPOC) **

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