There is growing acceptance in the design community that two types of uncertainty exist: inherent variability and uncertainty that results from a lack of knowledge, which variously is referred to as imprecision, incertitude, irreducible uncertainty, and epistemic uncertainty. There is much less agreement on the appropriate means for representing and computing with these types of uncertainty. Probability bounds analysis (PBA) is a method that represents uncertainty using upper and lower cumulative probability distributions. These structures, called probability boxes or just p-boxes, capture both variability and imprecision. PBA includes algorithms for efficiently computing with these structures under certain conditions. This paper explores the advantages and limitations of PBA in comparison to traditional decision analysis with sensitivity analysis in the context of environmentally benign design and manufacture. The example of the selection of an oil filter involves multiple objectives and multiple uncertain parameters. These parameters are known with varying levels of uncertainty, and different assumptions about the dependencies between variables are made. As such, the example problem provides a rich context for exploring the applicability of PBA and sensitivity analysis to making engineering decisions under uncertainty. The results reveal specific advantages and limitations of both methods. The appropriate choice of an analysis depends on the exact decision scenario.
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机译：在设计社区中，存在两种类型的不确定性存在：具有缺乏知识产生的固有的变异性和不确定性，这些变异性和不确定性导致了这一知识，这些变异性和不确定性导致了各种所谓的不确定，感觉，不可缩短的不确定性和认识性不确定性。关于用这些类型的不确定性表示和计算的适当手段的一致性较少。概率界限分析（PBA）是一种方法，其表示使用上下累积概率分布的不确定性。这些结构，称为概率框或仅限P盒，捕获可变性和不精确。 PBA包括在某些条件下用这些结构有效地计算的算法。本文探讨了PBA与敏感性分析与环境良性设计和制造的敏感性分析的优点和局限性。选择滤油器的选择涉及多个目标和多个不确定参数。这些参数以不同的不确定性级别的不同，并且对变量之间的依赖性的不同假设是不同的。因此，示例问题为探索PBA和敏感性分析的适用性提供了丰富的上下文，以便在不确定性下进行工程决策。结果揭示了两种方法的特定优点和局限性。 The appropriate choice of an analysis depends on the exact decision scenario.
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