TY - JOUR

T1 - Making design decisions under uncertainties

T2 - probabilistic reasoning and robust product design

AU - Gembarski, Paul Christoph

AU - Plappert, Stefan

AU - Lachmayer, Roland

PY - 2021/12

Y1 - 2021/12

N2 - Making design decisions is characterized by a high degree of uncertainty, especially in the early phase of the product development process, when little information is known, while the decisions made have an impact on the entire product life cycle. Therefore, the goal of complexity management is to reduce uncertainty in order to minimize or avoid the need for design changes in a late phase of product development or in the use phase. With our approach we model the uncertainties with probabilistic reasoning in a Bayesian decision network explicitly, as the uncertainties are directly attached to parts of the design artifact′s model. By modeling the incomplete information expressed by unobserved variables in the Bayesian network in terms of probabilities, as well as the variation of product properties or parameters, a conclusion about the robustness of the product can be made. The application example of a rotary valve from engineering design shows that the decision network can support the engineer in decision-making under uncertainty. Furthermore, a contribution to knowledge formalization in the development project is made.

AB - Making design decisions is characterized by a high degree of uncertainty, especially in the early phase of the product development process, when little information is known, while the decisions made have an impact on the entire product life cycle. Therefore, the goal of complexity management is to reduce uncertainty in order to minimize or avoid the need for design changes in a late phase of product development or in the use phase. With our approach we model the uncertainties with probabilistic reasoning in a Bayesian decision network explicitly, as the uncertainties are directly attached to parts of the design artifact′s model. By modeling the incomplete information expressed by unobserved variables in the Bayesian network in terms of probabilities, as well as the variation of product properties or parameters, a conclusion about the robustness of the product can be made. The application example of a rotary valve from engineering design shows that the decision network can support the engineer in decision-making under uncertainty. Furthermore, a contribution to knowledge formalization in the development project is made.

KW - Bayesian network

KW - Decision network

KW - Decision-making under uncertainty

KW - Probabilistic reasoning

KW - Solution space development

UR - http://www.scopus.com/inward/record.url?scp=85112853501&partnerID=8YFLogxK

U2 - 10.1007/s10844-021-00665-6

DO - 10.1007/s10844-021-00665-6

M3 - Article

AN - SCOPUS:85112853501

VL - 57

SP - 563

EP - 581

JO - Journal of Intelligent Information Systems

JF - Journal of Intelligent Information Systems

SN - 0925-9902

IS - 3

ER -