Design Catalogs: A Systematic Approach to Design and Value Flexibility in Engineering Systems

This paper proposes design catalogs as an efficient systematic process for identifying and evaluating improved designs in engineering systems by exploiting ideas of flexibility. Standard design and evaluation approaches typically do not cope well with a range of possible operating conditions. They o...

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Bibliographic Details
Main Authors: Cardin, Michel-Alexandre, Geltner, David M, de Neufville, Richard L
Other Authors: Massachusetts Institute of Technology. Department of Urban Studies and Planning
Format: Article
Language:en_US
Published: Elsevier 2017
Online Access:http://hdl.handle.net/1721.1/108089
https://orcid.org/0000-0002-1024-7555
Description
Summary:This paper proposes design catalogs as an efficient systematic process for identifying and evaluating improved designs in engineering systems by exploiting ideas of flexibility. Standard design and evaluation approaches typically do not cope well with a range of possible operating conditions. They often simplify considerations of uncertainty, which may lead to designs that do not perform as well as those responding dynamically to changing conditions. The proposed process addresses the complexity of the design problem under uncertainty, recognizing that it is impossible to analyze all possible combinations of evolutions, and the flexible ways in which the system could adapt over time. The process creates a small subset of designs that collectively perform well over a range of scenarios. It bundles representative scenarios and their flexible responses to enable a more thorough analysis that accounts explicitly for uncertainty—and enable considerations of improved designs. Each element consists of combinations of design variables, parameters, and management decision rules carefully selected, and referred as operating plans. In the example analysis, the process improves economic performance by 37% as compared to standard methods in an infrastructure system case study, while exploring only 3% of the design space. It reaches 86% of the stochastically optimal solution while being 183 times faster computationally in the example numerical study. The systematic property aims for practical applications in industry. In each phase, it gives the freedom to rely on the designer's expertise with the system, or to consider analytical tools already in use at the design organization.