The design of a connected engineered system requires numerous design decisions that influence one another. In a connected system that comprises numerous interacting decisions involving concurrency and hierarchy, accounting for interactions while also managing uncertainties, it is imperative to make robust decisions. In this article, we present a method for robust design using coupled decisions to identify design decisions that are relatively insensitive to uncertainties. To account for the influence among decisions, design decisions are modelled as coupled decisions. They are defined using three criteria: the types of decisions, the strength of interactions and the decision levels. In order to make robust decisions, robust design methods are classified based on sources of uncertainty, namely, Type I (noise factors), Type II (design variables) and Type III (function relationship between design variables and responses). The design of a one-stage reduction gearbox is used as a demonstration example. To illustrate the proposed method for robust design using coupled decisions, we present the simultaneous selection of gear material and gearbox geometry in a coupled decision environment while managing the uncertainties involved in designing gearboxes.
Decision Support Problems (DSPs) are used to model design decisions involving multiple trade-offs. In practice, such design decisions are also coupled, that is, these decisions must be modelled by identifying and addressing the influence they exert on one another. Hence, we need to classify coupled decision problems and to introduce methods for managing uncertainty for such problems. Classification of coupled decision problems allows for the development and execution of decision templates to effect design and to archive design-related knowledge on a computer. Incorporating robustness metrics allows for the exploration of robust design solutions for coupled decision problems by managing uncertainty.
In this paper, we present a classification scheme for coupled decisions using DSPs, called the Decision Scenario Matrix and we illustrate its utility by solving a coupled problem using DSPs. The design of a beam to be used as a fender is used to illustrate the efficacy of the formulation of coupled problems. In the first example, we determine a robust design, that is, determine the dimensions of the fender and simultaneously design the material recognizing that the computational models are incomplete and inaccurate. In the second example, we determine robust design solutions when design decisions are coupled, that is, determine the dimensions of the fender and select the material concurrently. Our focus, in this paper, is on illustrating the efficacy of the method rather than on the results.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.