Design Catalogs: A Systematic Approach to Design and Value Flexibility in Engineering Systems
Name
Cardin2015SE-DC-manuscript-R2-clean.pdf
Description
I think this is the right pdf (a collaborator was able to send)--thanks!
Size
841.7 KB
Format
Adobe PDF
Checksum (MD5)
2d383437620b83940895c3661c2817cf
Author(s)
Cardin, Michel-Alexandre
Geltner, David M
de Neufville, Richard L
Date Issued
October 2015
Journal
Systems Engineering
Publisher
Elsevier
Citation
Cardin, Michel-Alexandre, Richard de Neufville, and David M. Geltner. “Design Catalogs: A Systematic Approach to Design and Value Flexibility in Engineering Systems.” Systems Engineering 18.5 (2015): 453–471.
Version
Author's final manuscript
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Department of Urban Studies and Planning
Massachusetts Institute of Technology. Engineering Systems Division
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1002/sys.21323
