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6.3.1 Decision Oriented Systems Engineering (DOSE) 1 – A Structured, Systematic Approach to Function Allocation
Author(s) -
Buckley Michael E.,
Stammnitz Volker
Publication year - 2004
Publication title -
incose international symposium
Language(s) - English
Resource type - Journals
ISSN - 2334-5837
DOI - 10.1002/j.2334-5837.2004.tb00568.x
Subject(s) - system of systems , computer science , system of systems engineering , function (biology) , process (computing) , systems engineering , complex system , set (abstract data type) , legacy system , systems analysis , systems design , risk analysis (engineering) , management science , software engineering , engineering , artificial intelligence , medicine , software , evolutionary biology , biology , programming language , operating system
Perhaps the most important reason Systems Engineering exists as a discipline lies in the observation that complex systems cannot be treated merely as an assemblage of so many building blocks. Systems Engineering employs techniques and practices that attempt to consider the whole throughout the design process. Systems Engineering offers quite an assortment of processes, and tools devices to capture, describe, derive, and otherwise characterize various aspects of systems under design or analysis. There are many evolving Systems Engineering processes and practices, including processes in which the object‐oriented paradigm dominates. Unfortunately, the set of available processes, models, and tools remains weakest where they are needed the most: where decision tradeoffs are most negotiable, where “requirements” are not yet firmly established, where the use of legacy systems can have the greatest impact, and where the (projected) life cycle impacts of such decisions are greatest. This paper describes a new system development practice named Decision Oriented Systems Engineering (DOSE). If consistently and diligently applied in tandem with other more conventional practices, DOSE provides a solid Systems Engineering “hook” to the application of Human Systems Integration principles and offers considerable promise in simplifying the design of even the most complex systems involving teams working with mixes of new, evolving, and legacy systems.