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Critical Life-Cycle Decision Making for Projects under Uncertainty

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2016 ASEE Annual Conference & Exposition


New Orleans, Louisiana

Publication Date

June 26, 2016

Start Date

June 26, 2016

End Date

June 29, 2016





Conference Session

Engineering Economy Division Technical Session 1

Tagged Division

Engineering Economy

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Paper Authors


K. Jo Min Iowa State University

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K. Jo Min is Associate Professor and Associate Chair, Director of Undergraduate Education in Industrial and Manufacturing Systems Engineering Department at Iowa State University. He teaches courses on production systems, closed-loop supply chains, and engineering valuation. His education research interests include outcome assessment and visualization aids, and his engineering research focuses on application of stochastic optimal control on engineering decision making. He has co-authored numerous papers in The Engineering Economist, IEEE Transactions on Engineering Management, International Journal of Production Research, International Journal of Engineering Education, and other peer-reviewed journals. He has been serving as an ABET program evaluator for EAC and ETAC and as a reviewer for various NSF engineering education panels.

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John Jackman Iowa State University

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John Jackman is an associate professor of industrial and manufacturing systems engineering at Iowa State University. His research interests include engineering problem solving, computer simulation, web-based immersive learning environments, and data acquisition and control.

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Michelle Zugg Iowa State University

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Michelle Zugg is a Masters of Science candidate in Industrial Engineering at Iowa State University. Her research interests include supply chain management with specific interest in quality and efficiency.

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In this paper, we first describe how critical life-cycle decisions are made for projects facing significant uncertainties. The key differentiating aspect of our approach from the traditional net present value approach is regarding the timing of such decisions. For example, our emphasis is on the effective dates for the commencement and expiration (i.e., a window of opportunity) for possible actions regarding a project, which is clearly above and beyond a single shot decision of investment or no investment. Our approach is based on elementary stochastic optimal control methods, which often afford closed-form solutions on critical timing information such as the expected remaining life of a project under significant uncertainties. These analytic solutions provide managerial insights and economic implications that are simply absent in numerical results under particular sets of parameter values. We next show how we integrate our approach in a traditional engineering economy course utilizing a short, self-contained module of a few lectures. The context of the lectures is the decisions by wind farms to exit and/or enter. For this module, we administer pre- and post- tests as well as self-efficacy surveys. In addition, focus groups are utilized to obtain immediate feedback in an interactive manner. The results from the assessment of outcomes and the self-efficacy surveys, as well as the feedback from focus groups are presented. Finally, subsequent steps towards improved teaching and learning in life-cycle decision making for projects under uncertainty are outlined.

Min, K. J., & Jackman, J., & Zugg, M. (2016, June), Critical Life-Cycle Decision Making for Projects under Uncertainty Paper presented at 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana. 10.18260/p.26598

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