ARMY AL&T
There is a new breed of warriors that have become critical to Army modernization: data scientists.
ANALYTICAL APPROACH Data scientists often take multiple approaches to different chal- lenges. At AMLC, data scientists are working on developing capabilities in three primary areas:
• Predictive maintenance: Using ML techniques to predict medical maintenance requirements before equipment failure. Predictive maintenance will improve medical equipment functionality and longevity while proactively supporting unit readiness for operational needs. Predictive maintenance will aid in identifying patterns and predicting the timing of the next materiel failure, as well as provide a possible solution (e.g., Equip- ment X is likely to fail in Y days for Z reason; replace part A with part B).
• Demand forecasting: Leveraging time-series forecast- ing algorithms to predict demand for future large-scale combat operations. Through historical orders and supply consumption data analysis, AMLC can ensure warehouses and Army prepositioned stock inventories reflect active requirements and can accommodate future demands. Tis effort supports reducing waste and dimin- ishing the burden on the supply chain.
• Simulated scenarios: Simulating medical materiel requirements in various projected large-scale combat operations environments. By combining information on the effects of the scenario environment and supply consumption rates, these models help AMLC simulate the potential medical logistics landscape in large-scale combat operations.
AMLC’s end goal is to allow decision-makers at echelon to antic- ipate and position lifesaving materiel at necessary roles of care during large-scale combat operations. Tis involves accurately
predicting medical needs of wounded warfighters based on loca- tions, utilization rates and other vital information to optimize prioritization of medical materiel by type and quantity.
CONCLUSION As the global stage evolves, maximizing the use of data to support informed decision-making becomes increasingly critical to not only staying ahead of our adversaries, but also staying within constrained resources. Data helps leaders make smart decisions. By aggregating multiple data sources from diverse systems into a singular cloud platform to support quality analysis, AMLC’s data scientists generate actionable insights.
What medical supplies are being rapidly consumed and what is excess? Which medical devices are most likely to need repair parts soon? When does the device need its next preventive main- tenance service?
Tese insights also provide visibility into what, when and how things may break, as well as what may be needed to be replaced. In kind, this data can also tell us what we don’t need to buy—and this cost avoidance can return critical resources to the enterprise. If data tells the story, then data scientists are the writers—making meaning out of a mountain of information and giving leaders a tactical edge. Tat is why predictive logistics has become so crit- ical to the Army’s ability to fight. Data is now the most decisive commodity because resources are not limitless, and time is not a renewable resource.
For more information, go to
https://www.amlc.army.mil.
JOEL COOK is a technical acquisition management specialist and serves as chief of the Technical Information Management Division’s Logistics and Technical Support Directorate for the AMLC Integrated Logistics Support Center. He holds a master’s in public administration from Brigham Young University and a B.S. in exercise physiology from Brigham Young University-Idaho.
CONTRIBUTORS: Tajesvi Bhat, senior data scientist at the AMLC Integrated Logistics Support Center’s Logistics and Technical Support Directorate; and Arthur Braithwaite, director of the Logistics and Technical Support Directorate of the AMLC Integrated Logistics Support Center.
https://asc.ar my.mil
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