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Getting Left of Readiness Drivers

Aviation Maintenance/Sustainment / By Ms. Debbie Daniel and Mr. Fred W. Pieper, Jr.: The U.S. Army Aviation and Missile Command (AMCOM) is driving forward and challenging the status quo; and that is readily present in optimizing the supply chain. The following article describes the Army’s efforts to develop a predictive analysis capability integral to the supply chain management. The effort to develop the predictive analysis capability in the supply chain will span and engage all sustainment logistics business areas including, Business and Finance; Supply Chain Execution; Supply Chain Planning; Product Logistics Management; and

U.S. Army PFC Tess Sandoval assigned to 2nd Squadron, 6th Calvary Regiment, 25th Combat Aviation Brigade work on an AH-64 at Wheeler Army Airfield, Hawaii, Aug. 25, 2019. / U.S. ARMY PHOTO BY 1ST. LT. RYAN DEBOOY)

Maintenance and Remanufacture.

The Army has metrics across all its business areas of operation to include, but not limited to, Supply Availability (SA); Performance to Promise; Administrative/Production Lead-Times (ALT and PLT); and On-Time Delivery. Each of these metrics prove useful, but only to a certain extent, and they all have one thing in common – they are rearward looking. These metrics all measure, or compare, events in the past and historically have not been good predictors of future performance. The right application and utilization of artificial intelligence (AI) can help the Army better analyze the available data, identify patterns and trends and assist the Army to make decisions based on desired outcomes.

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Early ID is Paramount

Early identification of readiness drivers (items that could potentially go into a negative supply position adversely impacting unit readiness) is of paramount importance to maintaining the supply availability necessary to keep our weapon systems in the fight. Due to the long lead times associated with certain materials and/or shortfalls in available industrial capacity, the Army sometimes needs to forecast supply demand three to five years out. By identifying the correct data in the appropriate business area and connecting the data from multiple business areas, the Army can develop predictive analytics that will drive insight and actions throughout the supply chain. Through the selective implementation of AI, the Army will develop real-time visibility into inventory at rest and in motion, and improve the precision of supply availability and drive continual improvement throughout the supply chain.

A few of the factors that can negatively affect supply availability include protracted ALTs, lengthy PLTs, repair lead-times, delinquent deliveries, reductions in repair programs, contracts, safety messages and fluctuations in fielding or modification schedules. Developing the ability to immediately identify and analyze the possible impact of these factors on SA would enable immediate action to mitigate the impact of such events occurring.

The AMCOM Logistics Center (ALC) strives to refine the logic for predicting future readiness drivers. It is this effort that drives the ALC to look at AI applications for the supply chain, to include Machine Learning (ML). AI makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks. ML can analyze complex data and establish current patterns and future trends. AI augments the ALC’s abilities and makes us better at what we do. AI algorithms learn differently than humans, they look at things differently. AI algorithms can see relationships and patterns that escape humans. In turn, a human/AI partnership offers the following opportunities:

  • Brings analytics to industries and domains where it’s currently underutilized.
  • Improves the performance of existing analytic technologies, such as computer vision and time series analysis.
  • Breaks down economic barriers, including language and translation barriers.
  • Augments existing abilities and makes us better at what we do.
  • Gives us better vision, better understanding, better memory and much more.

Supply Chain Optimization Efforts

The ALC’s supply chain optimization efforts are multi-faceted. First, the ALC is currently developing the basic logic for identifying the correct data to analyze. Second, the ALC has partnered with Gartner Incorporated, a leading research and advisory company, Gartner is connecting the ALC with companies that are already utilizing AI as well as companies just beginning the AI journey. Third, the ALC is pursuing a proof of concept with a local company in the Huntsville, Alabama area. This local company will work with the ALC to integrate AI into a supply chain forward-looking tool, thus providing a predictive analytical tool. The ALC is deliberately embracing AI.

A fundamental tenet of a successful supply chain is the accuracy of the data upon which the supply chain is dependent. Provisioning for parts, components and assemblies is heavily reliant on clean, accurate data; to that end, the ALC team has developed a Data Quality Assessment Tool (DQAT). The better the provisioning of accurate data determines the success of the supply chain’s ability to support the Warfighters maintaining our weapon systems. The DQAT increases the speed at which the ALC can review provisioning data, significantly reduces the number of human errors and measures the quality of Original Equipment Manufacturer (OEM) data deliveries over time, increasing our confidence in the data and improving the provisioning process overall. The data accuracy improvements are foundational in optimizing the supply chain and directly supports the efforts to develop predictive analysis tools for the supply chain. Once we have developed effective predictive analysis tools, we can more rapidly get left of readiness drivers.

As the Army implements the Enterprise Resource Planning System and improves the Logistics Modernization Program, the ALC is well postured to take advantage of AI applications to optimize the supply chain. AI has several applications in the supply chain, such as collecting information/data, supply and demand planning, data analysis, materiel distribution and warehouse management. As the ALC takes every opportunity to connect data across multiple business areas we also connect with business systems throughout the industrial base, specifically, OEMs. We are working to connect data from various business areas in order to source, process and understand that data. Ultimately, the ALC strives to more accurately forecast future supply demands.

Early identification of readiness drivers is of paramount importance to maintaining the supply availability necessary to keep our weapon systems in the fight. Getting left of those readiness drivers is our primary mission, and a formidable one at that. Bringing predictive analysis to the Army’s supply chain management is what we need to do in order to prepare our sustainment logistics business area to support large-scale combat operations in the future, against a peer or near-peer threat. Getting left of readiness drivers means staying a step ahead of the threat.

Mr. Fred W. Pieper, Jr. is the deputy executive director and Ms. Debbie Daniel is with the Materiel Management Directorate of the AMCOM Logistics Center of the U.S. Army Aviation and Missile Command (AMCOM) at Redstone Arsenal, AL.

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