Campus Units

Electrical and Computer Engineering, Industrial and Manufacturing Systems Engineering, Mechanical Engineering

Document Type


Publication Version

Accepted Manuscript

Publication Date


Journal or Book Title

Reliability Engineering & System Safety



First Page


Research Focus Area(s)

​Operations Research, Ergonomics and Human Factors, Information Engineering




Designing resilient engineered systems that can sense and withstand adverse events and recover from the effects of the adverse events is increasingly seen as an important goal of engineering design. This paper proposes a value-driven design for resilience (VD2R) framework in order to enable the assessment of system resilience and the optimization of decision variables (or design characteristics) that maximize the value of the system for a firm. The VD2R framework possesses three unique features that allow system resilience and value to be addressed in a theoretically founded and explicit way. First, it assesses the time-dependent resilience of an engineered system by explicitly modeling the redundancy, robustness, and restoration of the system. This assessment captures the stochastic behavior of degradation and restoration and their impact on system resilience. Second, it encompasses a value model that links time-dependent system resilience to a design firm's future profit. Third, the VD2R framework offers an efficient optimization method to solve high-dimension, mixed-integer decision-making models. The proposed framework is demonstrated with a case study, where the resilience of a series-parallel system is modeled and its design characteristics optimized.


This is a manuscript of an article published as MacKenzie, Cameron A., and Chao Hu. "Decision Making under Uncertainty for Design of Resilient Engineered Systems." Reliability Engineering & System Safety 192 (2018): 106171. DOI: 10.1016/j.ress.2018.05.020. Posted with permission.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Copyright Owner

Elsevier Ltd.



File Format


Published Version