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Schedule risk analysis for new-product development: The GERT method extended by a characteristic function
Stockholm University, Faculty of Social Sciences, Stockholm Business School. Nanjing University of Aeronautics and Astronautics, China.
Stockholm University, Faculty of Social Sciences, Stockholm Business School. Economics and Management School of University of Chinese Academy of Sciences, China.
Number of Authors: 42017 (English)In: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836, Vol. 167, p. 464-473Article in journal (Refereed) Published
Abstract [en]

Schedule risk analysis plays a key role in new product development. A typical project-schedule model using the Critical Path Method (CPM) and Program, Evaluation, and Review Technique (PERT) falls short in many practical situations. Instead, a graphical evaluation and review technique (GERT) has been recommended for its ability to address probability branches and loops. This paper introduces a GERT model based on a characteristic function and designs its numerical solution. First, an inversion formula is applied to derive the probability distribution of the completion time of a product development. Second, to address the implications of a due date, a novel measure of schedule risk is introduced to give a view of both loss and probability. Third, an elasticity analysis is used to identify the network parameters that facilitate the control of schedule risk. A case study of new product development in a high-technology enterprise is presented to demonstrate the proposed methods. The approach will be useful in schedule risk analysis across several problem domains including engineering, environment, management, economic development, etc.

Place, publisher, year, edition, pages
2017. Vol. 167, p. 464-473
Keywords [en]
Schedule risk, Elasticity analysis, Characteristic function, Project management, Planning, Numerical methods, Graphical user interface
National Category
Economics and Business Other Engineering and Technologies
Identifiers
URN: urn:nbn:se:su:diva-150019DOI: 10.1016/j.ress.2017.06.010ISI: 000412607200042OAI: oai:DiVA.org:su-150019DiVA, id: diva2:1167627
Available from: 2017-12-19 Created: 2017-12-19 Last updated: 2017-12-19Bibliographically approved

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