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Managing a Complex Interdisciplinary Engineering System using Feature Models

  • Author / Creator
    Leitch, Michael
  • In order to assist in the management of complex engineering design tasks, a famework is proposed which allows for the formal modelling and coordination of design activities as a Cyber-Physical System. Unified feature models are used to define the design tasks employed in the design process, and these models are coordinated using design structure matrices. These techniques allow for design managers to optimize the sequencing and coordination of design activities in a way that minimizes the size and cost of design iterations, while improving design quality.The methods proposed are explored in the context of activities used for the design of downhole tools used in the extraction of heavy oil. The complexity of this system is explained, and a functional decomposition is used to define and justify the design tasks which are included in the model. Generic features are presented which define the mechanical system (design features), the interactions between the system and the environment (phenomenon features), and engineering design tasks which can be used to model the system and optimize the design (evaluation features). The relations and dependencies between all of these elements are mapped, and a Design Structure Matrix is used to explore how the design process can be optimized by rearranging the tasks, coupling or decoupling tasks, and identifying opportunities to improve the system by focussing on those dependencies which can be shown to negatively impact the performance of the system (or the cost of the design process).The proposed framework provides the requirements and design structure for a software tool which can, when implemented, be used as a stand-alone design tool, or as a high performance physics engine to enable the systematic and accurate estimation of critical parameters in conjunction with existing commercial system-level models.

  • Subjects / Keywords
  • Graduation date
    Spring 2019
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/r3-5hqh-j656
  • License
    Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.