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DEVELOPMENT OF A KNOWLEDGE MANAGEMENT MODEL IN LARGE-SCALE INTERNATIONAL SPACE SCIENCE PROJECTS
Title
DEVELOPMENT OF A KNOWLEDGE MANAGEMENT MODEL IN LARGE-SCALE INTERNATIONAL SPACE SCIENCE PROJECTS.
Creator
Nunez, Jose, Kotnour, Timothy, University of Central Florida
Abstract / Description
Large-scale international science projects (LISPs) are those projects where two or more countries formally agree to cooperate toward the achievement of a scientific, research and development, or engineering goal. In general, only projects exceeding $1 billion U.S. are considered LISPs, so sheer size commands attention, and because they are so costly and visible, failure can lead to significant scientific, financial and political consequences. This researched focused on how 7 different...
Show moreLarge-scale international science projects (LISPs) are those projects where two or more countries formally agree to cooperate toward the achievement of a scientific, research and development, or engineering goal. In general, only projects exceeding $1 billion U.S. are considered LISPs, so sheer size commands attention, and because they are so costly and visible, failure can lead to significant scientific, financial and political consequences. This researched focused on how 7 different critical success factors impacted the level of technical interface knowledge shared among international partners involved in a large-scale international space science project (LISSP) – the International Space Station (ISS), which is currently under assembly and testing at the Kennedy Space Center, Florida. The research methodology employed documentation review, individual interviews and surveys of experienced engineers and managers from three different countries associated with the ISS. The research methodology was applied to three different cases (retrospectively) involving the processing of flight hardware from the three different international partners. The analysis showed that only 5 out of the 7-factor model played a significant role in the level of knowledge sharing between partners. The developed model provides future international partnerships with critical success factors that they can apply to their specific project / mission teams in order to improve the level of knowledge shared between them.
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Date Issued
2005
Identifier
CFE0000656, ucf:46501
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0000656
IMPROVING PROJECT MANAGEMENT WITH SIMULATION AND COMPLETION DISTRIBUTION FUNCTIONS
Title
IMPROVING PROJECT MANAGEMENT WITH SIMULATION AND COMPLETION DISTRIBUTION FUNCTIONS.
Creator
Cates, Grant, Mollaghasemi, Mansooreh, University of Central Florida
Abstract / Description
Despite the critical importance of project completion timeliness, management practices in place today remain inadequate for addressing the persistent problem of project completion tardiness. Uncertainty has been identified as a contributing factor in late projects. This uncertainty resides in activity duration estimates, unplanned upsetting events, and the potential unavailability of critical resources. This research developed a comprehensive simulation based methodology for conducting...
Show moreDespite the critical importance of project completion timeliness, management practices in place today remain inadequate for addressing the persistent problem of project completion tardiness. Uncertainty has been identified as a contributing factor in late projects. This uncertainty resides in activity duration estimates, unplanned upsetting events, and the potential unavailability of critical resources. This research developed a comprehensive simulation based methodology for conducting quantitative project completion-time risk assessments. The methodology enables project stakeholders to visualize uncertainty or risk, i.e. the likelihood of their project completing late and the magnitude of the lateness, by providing them with a completion time distribution function of their projects. Discrete event simulation is used to determine a project's completion distribution function. The project simulation is populated with both deterministic and stochastic elements. Deterministic inputs include planned activities and resource requirements. Stochastic inputs include activity duration growth distributions, probabilities for unplanned upsetting events, and other dynamic constraints upon project activities. Stochastic inputs are based upon past data from similar projects. The time for an entity to complete the simulation network, subject to both the deterministic and stochastic factors, represents the time to complete the project. Multiple replications of the simulation are run to create the completion distribution function. The methodology was demonstrated to be effective for the on-going project to assemble the International Space Station. Approximately $500 million per month is being spent on this project, which is scheduled to complete by 2010. Project stakeholders participated in determining and managing completion distribution functions. The first result was improved project completion risk awareness. Secondly, mitigation options were analyzed to improve project completion performance and reduce total project cost.
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Date Issued
2004
Identifier
CFE0000209, ucf:46243
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0000209