Enterprise Condition-Based Maintenance Plan (eCBM+) Interoperability

NCMS Project #: 140840

Problem: Maintenance actions should be based on evidence of need as opposed to predetermined schedules, Condition Based Maintenance (CBM) effectively reduces the risk of failure while also reducing the cost of maintenance. CBM Plus (CBM+) is a designation used by the Department of Defense (DoD) to communicate the need for CBM systems to be inclusive of the entire data management lifecycle of equipment, not strictly maintenance operations. In this context, CBM+ might also impact the acquisition process as well as being tightly integrated with supply chain management. The transformational change from preventive maintenance to CBM+ relies heavily on several key phases of data management lifecycle.

Benefit: DoD systems are generating increasingly larger amounts of CBM relevant data, with some systems projected to generate up to 500 times more data than they do today; significantly compounding the data analysis challenge. Since industry partners in this project are providing all the required analytic software and associated data infrastructure connectors based on current commercial products, development efforts will primarily be limited to implementation of value added analytical implements capabilities within these analytic engines that are of direct value to the CBM+ community. The information gleaned from this project will provide DoD/NAVAIR considerable insights into the process of actually creating CBM+ systems as envisioned by the Guidebook.

Solution/Approach: SAS Institute will leverage their products that can operate on vast amounts of enterprise data, most of which is currently under-utilized, to uncover CBM+ relevant relationships, and ultimately, create actionable tasks to optimize maintenance based on materiel condition. This effort will include development of an overall eCBM+ template architecture, including integration with the NAVAIR data stores, NAVAIR’s closed loop Hadoop environment, metadata management, governance, data cleansing methods and data quality assessments, as well as development and interpretation of appropriate advanced analytic methods based on specific use cases, and more specifically, an end product that provides value to specific maintenance tasking.

Impact on Warfighter: Improved logistics readiness able to:

  • Work with arbitrarily large datasets
  • Work with any type of equipment
  • Apply a wide range of analytics and advanced modeling techniques
  • Continually monitor and adjust CBM+ algorithms to meet changing conditions

DoD Participation:

  • U.S. Navy (NAVAIR Lakehurst)

Industry Participation:

  • Wyle
  • SAS Institute
  • NCMS

Technology Focus Area(s):

  • Cost savings
  • Repair turnaround time
  • Maintenance avoidance & reliability
  • Maintenance management improvement

Improved readiness