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News: Predictive analysis reduces uncertainty, RCM adds efficiency, both save dollars

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Predictive analysis reduces uncertainty, RCM adds efficiency, both save dollars Cpl. Shawn Valosin

Cpl. Erikon Rosamond (center), a Kosciusko, Miss., native, and combat engineer with Bridge Company, 8th Engineer Support Battalion, 2nd Marine Logistics Group, guides an M1A1A1 Abrams Main Battle Tank from 2nd Tank Battalion, 2nd Marine Division onto a raft made up of improved ribbon bridges during a tank crossing aboard Camp Lejeune, N.C., Oct. 17. The tank is just one of many pieces of equipment that can benefit from predictive analysis programs carried out through the Research and Readiness Analysis cell within Marine Corps Systems Command’s Acquisition Logistics and Product Support. (Photo by Lance Cpl. Shawn Valosin)

QUANTICO, Va. - Knowing the future removes all doubt, but crystal balls are not government-issue. The next best thing is a computer-based simulation platform that predicts potential future outcomes with a high degree of confidence. In the world of military acquisition, reducing uncertainty can potentially lead to millions of dollars in cost-avoidance. This is where the Research and Readiness Analysis cell within Marine Corps Systems Command’s Acquisition Logistics and Product Support comes in.

The R2A team uses a variety of tools and analytical methods to reduce uncertainty related to sustainment planning and to identify efficiency initiatives at no or low cost to program managers. Coincidentally, one of the tools used by ALPS is aptly named “Crystal Ball” and allows program teams to identify the potential impact of sustainment decisions on future outcomes.

Besides Crystal Ball, the R2A team uses other predictive analysis tools to identify the potential impact of programmatic decisions on ownership cost and availability. This includes Reliability Centered Maintenance, known as RCM, to determine optimal failure management strategies to preserve a system’s key functions.

Predictive analysis is just one of many services provided through Marine Corps Systems Command, which is the Department of the Navy’s systems command for Marine Corps ground weapon and information technology systems. It is also the Marine Corps commandant's agent for acquisition and sustainment of warfighting systems and equipment.

R2A’s predictive analysis approach applies probability-based computer simulation software to support Marine Corps total lifecycle management and total lifecycle systems management.

“R2A employs such high-fidelity predictive analysis capabilities, widely used throughout the commercial sector, to assist [program managers and product support managers] and facilitate product support decisions that maximize readiness and minimize cost,” according to Joe Katz, Logistics Vehicle System Replacement logistician and former R2A predictive analysis lead.

“This brings modeling and simulation into the picture with software designed to project the effects of sustainment-related decisions over the performance of a system throughout its lifecycle,” he said. This predictive analysis approach reveals the potential outcome of multiple courses of action, which can be explored virtually before investing significant resources.

ALPS R2A employs a highly reputed predictive lifecycle modeling platform known as Demand Pro. To date, the Marine Corps has created and validated Demand Pro models for the Medium Tactical Vehicle Replacement, Light Armored Vehicle, Assault Amphibious Vehicle, Lightweight 155mm Howitzer, Joint Light Tactical Vehicle, M1A1 Abrams Tank, Mine Resistant Ambush Protected vehicle, M9 Armored Combat Earthmover and the Internally Transportable Light Strike Vehicle.

Katz said previous Demand Pro studies addressed a myriad of questions to support program managers and product support managers’ decisions. These included parts use predictions, battle damage repair kits, predictive sparing, performance-based logistics business case analysis, reset strategy comparison and home station training field service representatives’ analysis.

R2A aspires to develop its advanced forecasting technology portfolio and has recently begun to explore using the Crystal Ball program to aid in predicting the probability of particular outcomes.

“Crystal Ball is a spreadsheet-based software predictive analysis suite that allows many ‘what if’ questions to be answered with greater certainty. As such, it is a valuable decision-support tool to help program leaders identify and manage risk related to sustainment decisions,” said Maj. Dustin Thorn, current R2A predictive analysis lead.

In addition to predictive analysis, R2A leverages proven RCM methods to optimize failure management strategies that maximize platform availability at minimal cost.

“Over the past 30 years, maintenance has changed perhaps more so than any other management discipline,” as Capt. Christophe Radel, RCM lead, cited. “The changes are due to an increase in the number and variety of physical assets, their complexity and our changing views on maintenance organization and responsibilities.”

Early maintenance programs were based on the premise that components have a “life“ and are affected by age-related failures, and aimed to prevent all possible failures. Periodic and often intrusive maintenance actions were then considered to be essential to sustain performance and reliability.

This concept took a hit when researchers discovered as far back as 1943 that these actions often did more harm than good and contributed greatly to early breakdowns. In effect, these researchers determined that not all preventive maintenance is good maintenance and that maintenance actions may at times be wasteful. Unwarranted and intrusive may also destabilize otherwise stable systems and lead to failures.

Such realizations along with the desire to develop maintenance strategies based on the “Evidence of Need” led to the emergence of reliability-centered maintenance.

“The RCM process identifies the ways in which a system or asset can fail to live up to its expectations,” Radel said. “This is followed by a failure modes and effects analysis that identifies all the events reasonably likely to cause each failed state. RCM seeks to identify a suitable failure management policy to deal with each failure mode in the light of its consequences and technical characteristics.

“RCM is a time-honored, proven process,” he said. “When applied correctly and with qualified personnel, RCM produces overwhelmingly positive results. The goals of RCM can vary, but RCM has been used to enhance safety, reduce costs, improve availability, increase maintenance efficiency, improve environmental integrity and achieve longer useful life for weapon system components. It is the most effective way we have to serve the warfighter.”

ALPS and R2A personnel stand ready to help programs identify sustainment options that reduce cost, logistics footprint and maintenance requirements while maximizing availability, safety and environmental compliance.


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This work, Predictive analysis reduces uncertainty, RCM adds efficiency, both save dollars, by James Katzaman, identified by DVIDS, is free of known copyright restrictions under U.S. copyright law.

Date Taken:10.22.2013

Date Posted:10.22.2013 14:44

Location:QUANTICO, VA, USGlobe

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