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Improving Project Performance by Predicting Engineering Impacts on Operations Failure Risks Using a Quantitative Model of Product, Organization, Process, and Environment

TitleImproving Project Performance by Predicting Engineering Impacts on Operations Failure Risks Using a Quantitative Model of Product, Organization, Process, and Environment
Publication TypeWorking Paper
Year of Publication2005
AuthorsChachere, J
IssueWP096
Date Published06/2005
PublisherCIFE
Publication Languageeng
KeywordsCenter for Integrated Facility Engineering, CIFE, Coordination, Decision Analysis, Design, Design Theory, Organization Models, Planning, Process Models, Product Models, Reliability Theory, Risk Analysis, Simulation, Stanford University, VDT, Virtual Design Team
AbstractProducing manned space missions, new cancer drugs, and civil facilities all involve an expensive design and development effort that culminates in operations that are at risk of technical failure. Today, few existing social science and engineering theories offer sufficient precision to support specific decisions involving project tradeoffs among operations failure risks and programmatic considerations (such as development schedule and cost). The aim of this research is to precisely identify theory-based mechanisms by which management choices influence engineering processes—specifically the failure to complete necessary rework— that creates product flaws which jeopardize downstream operational success, and to quantify the degree to which these phenomena are likely to manifest for a given project. We propose a quantitative method for analyzing these risks by modeling the interdependencies among upstream engineering and downstream operations considerations. The proposed model integrates the Probabilistic Risk Analysis (PRA) model of product functions and operating environments, with the Virtual Design Team (VDT) simulation model of engineering organizations and processes. This research offers a formal definition of the ways in which many theoretical factors (such as component redundancy, human error, constructive oversight, and information processing) that are chosen in the design phase may subsequently interact to determine operational phase failure risk. The integrated model is intuitively more justified for interdependent project planning applications than either model alone because most failures involve interactions among product, organization, process, and environmental factors. The proposed model offers project planners a more holistic assessment of operational failure risks and a broader range of testable mitigation strategies than models that are limited to consider the operations stage alone.
URLhttps://purl.stanford.edu/zz183dr4753
PDF Linkhttps://stacks.stanford.edu/file/druid:zz183dr4753/WP096.pdf
Citation Key844