Often during a system Product Development program, external factors or requirements change, forcing system design change. This uncertainty adversely affects program outcome, often adding to development time and cost, production cost, and can compromise system performance. We present a development approach that minimizes the impacts, by proactively considering the possibility of changes in the external factors and the implications of mid‐course design changes. The approach considers the set of alternative designs and the burdens of a mid‐course change from one design to another in determining the relative value of a specific design through the set‐based design methodology. The approach considers and plans parallel (redundant) development of alternative designs with progressive selection of options, including time‐versus‐cost tradeoffs and the impact change‐costs. The approach includes a framework of the development process addressing design and integration lead‐times, their relationship to the time‐order of design decisions, and the time‐dependent burden of design changes. We also compare set‐based and single point design schemes.

The ability to rapidly mobilize the Marine Corps in times of crisis is a cornerstone of Unit ed States defense stra tegy. To mobilize rapidly, the marines need an efficient system for assigning officers to mobilization billets. The sys tem we designed and built is based on a network optimization algorithm that works in conjunction with carefully designed and scrupulously maintained Marine Corps data bases. It takes less than 10 minutes on a 386-based personal computer to complete a mobilization involving 40,000 officers and 27,000 billets and to produce output suitable for generating orders to report via MAILGRAM. Prior to our work, the Marine Corps had a mainframe-based system that took two to four days to complete a mobilization. The new system is not only much faster than the old system, but it also produces significantly better assignments with respect to all measures of effectiveness considered. You 'll find us rough, sir, but you'll find us ready.-Charles Dickens. David Copperfield A lmost all of the United States' contingen cy plan s for responding with force to international crises invo lve rapid deploymen t of the marin es in the earliest Copynghf Cl I~I. Tbe Inst1tutl' o f M.n.gl'mml Soences OO~I •2102 /91 /2 104 / 0026S0L2 5 Thls P<1P" wu refereed ph ases of action. The marines may be called upon to seize an d hold a stra tegic geograp hic location or to negate a specific ene my asset. The exact mission will depend on the nature of the crisis. but in any case , it is essential for national security MIUTARY Al'rUCATI O NS-MANPOWER O PTIMIZATION-N ETWO RKS

No abstract

Tradespace analysis and exploration is used to frame a design problem. By taking stock of available technologies, predictions of the performance of a system defined from a combinatorial combination of technologies (from say a morphological matrix) can be made. Based on these assessments, tradeoffs between functional performance objectives (often termed simply Functional Objectives or FOs) can be made. The result of these performance tradeoffs or Trades, can then be used to define a target design space for a problem. That design space can then be characterized with criteria to determine the viability of the tradespace and the design problem. However, the cost to develop the morphological matrix for the tradespace can be prohibitive. The tradespace at the US Army DEVCOM Ground Vehicle Systems Center (GVSC) took more than 2 years of effort by multiple staff and technical experts to develop and allows for the consideration of more than 1021 vehicles. To develop enhanced approaches to tradespace analysis and exploration to enhance programmatic decision-making, a simulated tradespace based on “synthetic data” is necessary. For tradespace studies within the Clemson University Virtual Prototyping of Ground Systems (VIPR-GS) it was necessary to develop a synthetic tradespace model to serve as a basis for evaluating improved approaches to tradespace analysis, exploration and decision-making methods. Within this work, we describe the state-of-the-art for developing models of the tradespace, formulations of functional objectives and defined models to represent different synthetic variable types to produce a synthetic tradespace with far less effort. Using this approach, we demonstrate the development of an example of a synthetic tradespace for small semi-autonomous ground vehicles developed within the VIPR Center that can be used to evaluate vehicle designs for the Clemson Deep Orange Project Vehicle and at GVSC. Finally, we will explore how this tradespace model can be used to facilitate decision-making surrounding the tradespace in the future.