The goal of decision making is to select the most suitable option from a number of possible alternatives. Which is easy, if all possible alternatives are known and evaluated. This case is rarely encountered in practice; especially in product development, decisions often have to be made under uncertainty. As uncertainty cannot be avoided or eliminated, actions have to be taken to deal with it. In this paper a tool from the field of artificial intelligence, decision networks, is used. Decision networks utilize probabilistic reasoning to model uncertainties with probabilities. If the influence of uncertainty cannot be avoided, a variation of the product is necessary so that it adjusts optimally to the changed situation. In contrast, robust products are insensitive to the influence of uncertainties. An application example from the engineering design has shown, that a conclusion about the robustness of a product for possible scenarios can be made by the usage of the decision network. It turned out that decision networks can support the designer well in making decisions under uncertainty.
CITATION STYLE
Plappert, S., Gembarski, P. C., & Lachmayer, R. (2020). Decision-Making with Probabilistic Reasoning in Engineering Design. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12117 LNAI, pp. 56–65). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-59491-6_6
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