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On treatment of uncertainty in system planning

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  • Flage, R.
  • Aven, T.

Abstract

In system planning and operation considerable efforts and resources are spent to reduce uncertainties, as a part of project management, uncertainty management and safety management. The basic idea seems to be that uncertainties are purely negative and should be reduced. In this paper we challenge this way of thinking, using a common industry practice as an example. In accordance with this industry practice, three uncertainty interval categories are used: ±40% intervals for the feasibility phase, ±30% intervals for the concept development phase and ±20% intervals for the engineering phase. The problem is that such a regime could easily lead to a conservative management regime encouraging the use of existing methods and tools, as new activities and novel solutions and arrangements necessarily mean increased uncertainties. In the paper we suggest an alternative approach based on uncertainty and risk descriptions, but having no predefined uncertainty reduction structures. The approach makes use of risk assessments and economic optimisation tools such as the expected net present value, but acknowledges the need for broad risk management processes which extend beyond the analyses. Different concerns need to be balanced, including economic aspects, uncertainties and risk, and practicability.

Suggested Citation

  • Flage, R. & Aven, T., 2009. "On treatment of uncertainty in system planning," Reliability Engineering and System Safety, Elsevier, vol. 94(4), pages 884-890.
  • Handle: RePEc:eee:reensy:v:94:y:2009:i:4:p:884-890
    DOI: 10.1016/j.ress.2008.09.011
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    References listed on IDEAS

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    1. Hjorteland, A. & Aven, T. & Østebø, R., 2007. "Uncertainty treatment in production assurance analyses throughout the various phases of a project," Reliability Engineering and System Safety, Elsevier, vol. 92(10), pages 1315-1320.
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    Cited by:

    1. Flage, Roger & Coit, David W. & Luxhøj, James T. & Aven, Terje, 2012. "Safety constraints applied to an adaptive Bayesian condition-based maintenance optimization model," Reliability Engineering and System Safety, Elsevier, vol. 102(C), pages 16-26.
    2. Martinez, Lauro J. & Lambert, James H. & Karvetski, Christopher W., 2011. "Scenario-informed multiple criteria analysis for prioritizing investments in electricity capacity expansion," Reliability Engineering and System Safety, Elsevier, vol. 96(8), pages 883-891.

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