Reducing the Logistics Burden for the Army After Next Doing More with Less (1999) / Chapter Skim
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3 Logistics Trade-Off Analysis
3 Logistics Trade-Off Analysis
Pages 29-47
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From page 29... ...
FACTORS IN TRADE-OFF ANALYSES To assess the potential impact of various technologies on logistics burdens, the committee was divided into three panels that focused on mobility, engagement, and sustainment functions. The panels quickly found that many of the technologies and system concepts being considered for the AAN battle force would have pervasive effects on both AAN operational capabilities and logistics burdens.
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From page 30... ...
Conversely, improving durability and mission reliability with heavy structural designs could decrease high-speed mobility and increase fuel consumption (the major logistics burden for the AAN battle force)
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From page 31... ...
fuel consumption and the life-cycle system cost for radical new vehicle designs will require significant advances. Simulation tools and capabilities will have to be greatly improved for mission rehearsal, for determining the logistics requirements of specific tactical operations (including operations with logistical constraints, such as fuel shortages, etc.)
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From page 32... ...
Requirement pulls must lead to specific, quantifiable performance constraints and objectives at all levels, down to the models used for engineering design studies. Promising technology-push opportunities must be weighed against each other and competing performance requirements using reliable, realistic parameters of system performance and limitations in force-on-force engagement models.
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From page 33... ...
Nor has the Army made a concerted effort to implement linkages in the time frame relevant to AAN design decisions. This problem is analogous to the difficulties faced by manufacturers in effectively linking computer-aided design tools with manufacturing tools, an area that is receiving a great deal of attention in the commercial manufacturing sector.
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From page 34... ...
Despite this strong endorsement more than six years ago of M&S technology for designing complex systems, the committee found little evidence that creating and implementing the M&S capability that is needed now for AAN analyses and designs has been given a high priority. The remainder of this chapter spells out in general terms the kind of M&S environment that will be necessary for analyses of ANN systems.
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From page 35... ...
At the other extreme, tools for engineering analysis and design use peak Toad information from higher level simulations to drive detailed component designs toward meeting or undershooting constraints on volume, weight, and cost, while achieving or exceeding performance objectives. Just as the force-on-force analysis at the top of Figure 3-l involves a complex military system, the component analysis and design at the bottom of the figure involves complex engineering considerations.
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From page 36... ...
A traditional approach to achieving high reliability, despite the extreme Toads encountered in high-speed cross-country mobility, would be to incorporate more material into the vehicle structure, which would make the vehicle heavier and would increase fuel consumption. To overcome the fundamental conflicting trade-offs inherent in conventional technology, advanced technology concepts, such as active suspension and traction control, could be simulated in a virtual proving ground with a soldier driving the vehicle (the midIeve!
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From page 37... ...
The examples are drawn from the three focal areas listed in Box 3-3: mobility trade-off analyses for AAN combat vehicle concepts, tradeoff analyses at the level of small-unit and force-on-force engagements, and AAN mission reliability trade-offs for AAN vehicle design. Mobility Trade-off Analyses Three mobility analysis capabilities start out as high-priority requirements for making AAN logistics trade-offs: comparative analysis of vehicle performance and logistics requirements; mission rehearsal to determine logistics requirements; and driver training for optimum mobility.
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From page 38... ...
However, the values for the speed, tractability, and fuel consumption parameters for NRMM are problematic at best for the advanced vehicle system and subsystem concepts being considered for the AAN. Engineering models can not yet accurately predict speed and tractability for vehicles with active suspension, all-wheel traction control, electric drive or a power source other than an internal combustion engine, and a host of related advanced technologies.
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From page 39... ...
The capability of modeling the interactive effects of driver behavior, tactics, and variations in system configuration on fuel consumption and mobility performance measures is particularly important. Moving down the M&S hierarchy of Figure 3-l, results from the virtual proving ground experiments could be used to identify critical elements of vehicle-terrain interaction in the mobility subsystem (and critical elements in models for other subsystems, such as the situational awareness subsystems for both driver and vehicle)
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From page 40... ...
Mission Rehearsal, Mission Logistics Planning, and Training Applications A hierarchical M&S environment well suited to system trade-off analyses in which logistics requirements are a primary design objective is not just a design tool. The same M&S capabilities can be used to support mission rehearsal, detailed logistics planning for specific missions, and troop training exercises.
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From page 41... ...
Existing models must be extended to represent the revolutionary tactics and materiel capabilities being considered for the AAN at both the small-unit and force-onforce engagement levels. Box 3-4 is a preliminary list of the major characteristics of an AAN operational unit and the interactions that must be represented in M&S tools to support AAN logistics trade-off analyses at this level.
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From page 42... ...
data and physical representation. Trade-off Analyses to Support AAN Mission Reliability The extraordinarily high levels of operational performance desired by AAN planners must be traded off against the equally fundamental logistical objective of 14-day self-sustainment.
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From page 43... ...
The conceptual relation of physics-of-faiTure modeling in electronics to the more general use of mechanisms of failure for reliability engineering of AAN systems is discussed in Chapter 7. An adequate systems design environment to meet the goal of 14-day selfsustainment will require significant development and integration of engineering-level M&S tools, as well as technology developments of dynamic-system simulation tools for loads prediction and of stress analysis tools for failure prediction.
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From page 44... ...
One way to accomplish this would be to establish a strategic technology objective that had strong support and continuing oversight from senior war-fighters committed to the AAN process. In this section, the committee suggests how the Army can facilitate integration, improvement, and development of M&S tools.
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From page 45... ...
For the recommended exploratory development program to bear fruit, the necessary capabilities can be built on the extensive existing infrastructure, which includes models developed by the defense community and M&S tools developed by commercial enterprises, existing and developmental virtual proving ground simulators, and the DoD DIS (distributed interactive simulation) environment.
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From page 46... ...
SCIENCE AND TECHNOLOGY INITIATIVES TO REDUCE LOGISTICS BURDENS THROUGH TRADE-OFF ANALYSES The committee concluded that the Army must make use of system trade-off analyses, beginning with the conceptual design phase, to ensure that AAN systems fielded in 2025 meet the objectives for reducing logistics burdens. The committee recommends that the following areas of scientific research and technology development be pursued to ensure that the trade-off analyses are both efficient and rational.
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From page 47... ...
The committee identified three focus areas where the development of M&S capabilities will be critical to system decisions in the next decade: high-speed cross-country mobility, materiel mission reliability, and small unit and forceon-force engagement. These and other applications are described in Chapters 4 through 7 and Appendices C through F
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