Axioms for Overcoming Resistance to Decision Based Design

这笔赠款为开发一种新的设计决策程序提供资金。目前，设计工程师使用各种程序进行权衡决策。其中许多程序结构松散，严重依赖一两个人的专家意见。这些程序在过去运作得相当好，但随着设计过程变得更加复杂，这些程序变得不够充分。该项目将开发一套公理或程序，以解决团队设计项目中提出的问题、不确定条件下的权衡以及对环境影响等“外部性”的考虑。具体而言，将制定程序，以便在两个关键阶段充分利用效用函数中包含的信息：综合以创造替代方案，分析以最大限度地开发每个替代方案的潜力。重点领域将是独立条件、属性定义、功能性多属性形式以及在评估不确定性和偏好方面的偏差。如果成功，这个项目将有助于将设计决策分析从艺术转变为科学。这些好处将由广泛的设计工程师实现，而不仅仅是决策分析方面的专家。在设计过程中，努力将重点放在潜在回报最大的地方。产品设计和开发将花费更少的时间，因为努力将集中在对整体产品效用贡献最大的合成和分析任务上。非线性偏好和权衡意愿将被精确建模，不确定性的影响将以合理、一致的方式包括在内。然后，将向客户展示更好地满足他们对高性能、高质量、低成本和低环境影响的冲突需求的产品。

This grant provides funding for the development of a new procedure for design decision making. Currently, design engineers make tradeoff decisions using a wide variety of procedures. Many of these procedures are loosely structured, and rely heavily on one or two individual's expert opinion. These procedures have worked reasonably well in the past, but have become inadequate as the design process has become more complex. This project will develop a set of axioms or procedures that will address issues raised in team design projects, tradeoffs under uncertainty, and consideration of "externalities" such as environmental impacts. Specifically, procedures will be developed for fully employing the information contained in a utility function during two critical stages: synthesis to create alternatives, and analysis to develop each alternative to its fullest potential. Focus areas will be the independence conditions, attribute definition, the functional multi-attribute form, and biases in assessing uncertainties and preferences. If successful, this project will help transform design decision analysis from an art to a science. The benefits will be realized by a broad range of design engineers, rather than by only specialists in decision analysis. During the design process, effort will be focussed where the potential payoff is greatest. Product design and development will take less time, since effort will be directed at synthesis and analytic tasks which contribute most to overall product utility. Nonlinear preferences and willingness to make tradeoffs will be modeled precisely, and the effect of uncertainty will be included in a rational, consistent manner. Customers will then be presented with products that better meet their conflicting needs for high performance, high quality, low cost, and low environmental impact.