ARL software integrates human factors into system design so systems are first built right

January 03, 2012

Story Highlights

  • IMPRINT helps the military make smarter purchasing decisions.
  • IMPRINT looks close at how Soldiers interact with planned new systems.
  • IMPRINT is part of the U.S. Army's MANPRINT program.

The Army Research Laboratory's unique computer-based tool helps the military make smarter purchasing decisions to ensure Soldier systems and equipment like new or upgraded vehicles, handheld weapons or electronic devices are built or designed right, for the right price, to accomplish what it's intended to do.

ARL's software tool, IMPRINT, takes a close look at how Soldiers interact with planned new systems by involving the Soldier interface throughout the system lifecycle--from concept and design to field testing and system upgrades.

"IMPRINT stands for the Improved Performance Research Integration Tool, and it's a dynamic task network modeling tool that we can use to model the missions of warfighters, or Soldiers or Sailors or whatever service we're looking at, breaking it into functions and tasks and actually examining and predicting how their performance will be effected using different systems," said Charnetta Samms, who leads the Tools Development Team within the Human Research and Engineering Directorate.

In 1995, the software demonstrated that upgrades to the Gulf War's primary nuclear, biological and chemical reconnaissance vehicle were worthwhile investments. Analysts in ARL's Human Research and Engineering Directorate conducted IMPRINT analysis on the then-proposed FOX M93A1, and showed that wartime manpower and operations planners could reduce the crew size in the wheeled armored vehicle from four to three Soldiers, and that adding fully automated standoff detection capabilities for immediate analysis and warning of contamination would not impede upon Soldier performance, Samms said.

IMPRINT uses commercially-available Micro Saint, an embedded discrete event task network modeling language, as its engine. Task-level information is used to construct networks representing the flow and the performance time and accuracy for operational and maintenance missions. IMPRINT is used to model both crew and individual Soldier performance. For some analyses, workload profiles are generated so that crew-workload distribution and Soldier-system task allocation can be examined. In other cases, maintainer utilization is assessed along with the resulting system availability. Also, using embedded algorithms, IMPRINT models the effects of personnel characteristics, training frequency, and environmental stressors on the overall system performance. Manpower requirements estimates can be generated for a single system, or a unit. IMPRINT outputs can be used as the basis for estimating manpower lifecycle costs.

HRED analysts conduct lengthy Soldier interviews to gain understanding of how they use equipment, or would expect to use new systems. Analysts take into consideration various dynamics like changes in the operational environment, what happens to system functionality and recovery if a Soldier uses the equipment incorrectly or makes a mistake, and how noise and temperature not only effect the Soldier, but the system itself. That information is then translated into a network model whose outputs help set realistic system requirements.

"We have users across the different services," Samms said. "Even NASA is very interested in using to help develop systems. So my goal and my job as the IMPRINT developer are to ensure I'm building a tool that can be used by all of our services to build better systems for our Soldiers, our Sailors, our Airmen, our astronauts, anybody we're putting in very complex environments."

IMPRINT is part of the U.S. Army's MANPRINT program, which is organized to optimize total system performance, reduce life cycle costs and minimize risk of Soldier loss or injury by ensuring a systematic consideration of the impact of materiel design on Soldiers throughout the system development process.


Last Update / Reviewed: January 3, 2012