Using Data Analytics and Machine Learning to Improve Inventory Management Capabilities

NCMS Project #: 141050

Problem: Low volume inventory demand often results in long lead times due to economic quantity demands not being reached.  Planning for these parts requires more than just historical demand data and necessitates greater analytic capability to accurately forecast.  With advances in manufacturing techniques, such as digital manufacturing, low rate production of critical parts is now becoming cost-effective and can satisfy previously uneconomic demand quantities significantly faster.

Benefit: This project will utilize U.S. Marine Corps data and existing ERP systems as a surrogate for an eventual industry solution that satisfies an important public need.  The results are expected to be easily transferable to commercial industry, which will positively impact delivery of products and services.

Solution/Approach: Efforts will focus on integration and analysis of data while pursuing a long-term machine learning solution.  This learning solution will automate much of the analysis resulting in increased velocity of critical information required to make managerial decisions.

Impact on Warfighter:

  • Provide effective and efficient data analysis
  • Improve supply chain visibility
  • Ability to prioritize needs for decision-makers
  • Reduce cost and eliminate waste
  • Enhance warfighter readiness

DOD Participation:

  • U.S. Marine Corps

Industry Participation:

  • Fairway Technologies, Inc.
  • NCMS

Benefit Area(s):

  • Cost savings
  • Positive environmental impact
  • Safety
  • Maintenance management improvement
  • Improved readiness
  • Reliability improvement

Focus Area:

  • Reliability improvement

Final Report