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Generational Evolution in Complex Engineered Systems

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Disciplinary Convergence in Systems Engineering Research

Abstract

Systems need to evolve to what is required and needed functionally. Looking at how each generation of a system changes as an evolutionary process, one can see correlations with the natural evolution process. Using nature as a guide, biological models may be a means to assess an engineered system and propose anticipatory changes (evolutions) to a current system to create the next generation. This idea of systems generational evolution may provide insight into the design process of multigenerational systems to be more adaptable to changing technology. Fundamental areas of research for support in this topic are biological evolutionary mathematical models and system of systems classification.

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Authors and Affiliations

  1. University of Alabama in Huntsville, Huntsville, AL, USA

    L. Dale Thomas & Katherine Burris

Authors
  1. L. Dale Thomas
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  2. Katherine Burris
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Corresponding author

Correspondence to L. Dale Thomas .

Editor information

Editors and Affiliations

  1. Systems Architecting and Engineering Program, University of Southern California, Los Angeles, California, USA

    Azad M. Madni

  2. Center for Systems and Software Engineering, University of Southern California, Los Angeles, California, USA

    Barry Boehm

  3. Aerospace & Mechanical Engineering, University of Southern California, Los Angeles, California, USA

    Roger G. Ghanem

  4. University of Southern California, Los Angeles, California, USA

    Daniel Erwin

  5. Systems Engineering Fellow, The Aerospace Corporation, El Segundo, California, USA

    Marilee J. Wheaton

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Dale Thomas, L., Burris, K. (2018). Generational Evolution in Complex Engineered Systems. In: Madni, A., Boehm, B., Ghanem, R., Erwin, D., Wheaton, M. (eds) Disciplinary Convergence in Systems Engineering Research. Springer, Cham. https://doi.org/10.1007/978-3-319-62217-0_52

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  • DOI: https://doi.org/10.1007/978-3-319-62217-0_52

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-62216-3

  • Online ISBN: 978-3-319-62217-0

  • eBook Packages: EngineeringEngineering (R0)

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