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System Scenario Selection Method for Faster Analysis
Author(s) -
Ferris Timothy L.J.,
Barker Stephen
Publication year - 2017
Publication title -
incose international symposium
Language(s) - English
Resource type - Journals
ISSN - 2334-5837
DOI - 10.1002/j.2334-5837.2017.00384.x
Subject(s) - risk analysis (engineering) , computer science , variety (cybernetics) , scenario analysis , selection (genetic algorithm) , value (mathematics) , order (exchange) , simple (philosophy) , operations research , engineering , mathematics , business , artificial intelligence , machine learning , statistics , philosophy , finance , epistemology
Abstract Scenario analysis is a frequently‐used method to explore what a proposed system is required to do in the early phases of system development leading towards finding system requirements. A system which is intended to perform a variety of roles under a range of conditions is likely to result in the need for a quantity of scenarios that becomes intractably pluriform. The consequence of too many scenarios is that either the number of scenarios to be analyzed must be reduced to a manageable number or the analysis is likely to be perfunctory, diminishing the value of the analysis, or the total effort required for the analyses may become unjustifiably great given the value of the project and the risks associated with it. We present a method for reducing the number of scenarios to be analyzed through study of the organization of the factors which distinguish scenarios from each other, and for selecting which scenarios need analysis through identifying their points of commonality and identifying where differences may impact system capability. Our method organizes the types and potential values of factors related to a particular system development in order to reduce the number of scenarios to be investigated. We illustrate our approach with a simple case developed for the purpose of this paper.