Robust and Reliability-Based Design

The idea behind this special supplement came out of discussions with the Editor, Dr. Michael McCarthy, about the need to present some recent advances in the area of risk-based and robust design. We felt, and still feel, that there is an ever increasing need to design mechanical and structural systems that are risk tolerant and robust. It was our belief that it would be useful if, by way of a dedicated special issue, we could help advance the understanding of risk-based and robust design in our mechanical design community. In this regard, the idea of the special issue was suggested to Dr. McCarthy who was immediately and enthusiastically responsive and supportive of the idea. We would like to specially thank him for that. The papers in this supplement were submitted to the ASME Journal of Mechanical Design in response to a Call for Papers CFP for the special issue. The CFP was issued in June 2005 with a submission deadline in mid September 2005. We received around 30 papers. All papers went through at least two rounds of review following the guidelines and standard review procedures of the journal. The 19 papers that are presented in this special supplement are for the most part in the area of robust and reliability-based design. We therefore decided to call the special supplement as such. These papers are organized into four groups: 1 robust design; 2 reliability-based design; 3 understanding and managing uncertainty; and 4 collaborative and multilevel design. There are six papers in the Robust Design group. An invited paper by Allen, Seepersad, and Mistree gives a literature survey of models and methods in the area of robust design. They classify robust design into three types, based on the source of uncertainty. These include: Type I, which refers to uncertainty or noise in the environment; Type II, which refers to uncertainty in design variables or control factors; and Type III, which refers to uncertainty introduced by modeling methods. They review numerous papers including those related to the Taguchi approach and its limitations and extensions, various stochastic and deterministic robust design models and methods, models in early stage of design, and those for multidisciplinary systems. They conclude their paper with a discussion of research challenges in robust design of multiscale systems and materials. In the next paper, Rolander, Rambo, Joshi, Allen, and Mistree present a combined compromise decision support robust design approach with proper orthogonal decomposition POD . POD is a reduced order modeling approach which, in the paper, is used for compact modeling of turbulent convection. The combined approach is demonstrated with an example for thermally efficient computer server cabinet configurations, with the computer servers cooled by forced air convection. The paper shows that the combined approach can handle variability well while improving heat dissipation and decreasing temperature using the same cooling infrastructure. Next, Mourelatos and Lian consider both robustness and reliability in their approach. They present a probabilistic multiobjective optimization model wherein mean performance is traded-off against robustness for some target reliability level.