Proceedings of the International Naval Engineering Conference & Exhibition (INEC)
Published October 3, 2018 | Version v1
Conference paper Open

Network-based metrics for assessment of naval distributed system architectures

Creators

  • 1. University of Strathclyde, Glasgow, UK
  • 2. BAE Systems Maritime - Naval Ships, Glasgow, UK

Description

The architecture of a system is generally established at the end of the conceptual design phase where sixty to eighty percent of the lifetime system costs are committed. The architecture influences the system’s complexity, integrality, modularity and robustness. However, such properties of system architecture are not typically analytically evaluated early on during the conceptual process. System architectures are defined using qualitative experience, and the early stage decisions are subject to the judgement of stakeholders. This article suggests a set of network-based metrics that can potentially function as early evaluation indicators to assess complexity, integrality, modularity and robustness of distributed system architectures during conceptual design. A new robustness metric is proposed that assesses the ability of architecture to support a level functional requirement of the system after a disruption. The new robustness metric is evaluated by an electrical simulation software (MATPOWER). A ship vulnerability assessment software (SURVIVE) was used to find potential disruptive events. Two technical case studies examining existing naval distributed system architectures are elaborated. Conclusions on the network modelling and metrics as early aids to assess system architectures and to choose among alternatives during the conceptual decision phase are presented. 

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References

  • Baldwin, C.Y., Clark, K.B., 2000. Design Rules: Volume 1. The Power of Modularity. The MIT Press, Cambridge, Massachusetts, London, England.
  • Brefort, D., Shields, C., Habben Jansen, A., Duchateau, E., Pawling, R., Droste, K., Jasper, T., Sypniewski, M., Goodrum, C., Parsons, M.A., Kara, M.Y., Roth, M., Singer, D.J., Andrews, D., Hopman, H., Brown, A., Kana, A.A., 2018. An architectural framework for distributed naval ship systems. Ocean Eng. 147, 375–385.
  • Browning, T., 2015. Design Structure Matrix Extensions and Innovations: A Survey and New Opportunities. IEEE Int. Eng. Manag. Conf. 63, 27–52.
  • Crawley, E., Week, O.L. De, Eppinger, S.D., Magee, C., Moses, J., Seering, W., Schindall, J., Wallace, D., Whitney, D., 2004. The influence of architecture in engineering systems. Pap. Present. MIT Eng. Syst. Symp. 29.
  • de Vos, P., 2014. On the application of network theory in naval engineering - Generating network topologies, in: 12th International Naval Engineering Conference and Exhibition. pp. 130–137. Amesterdam, Netherlands.
  • Department of Defense, 2011. FACT SHEET: Resilience of Space Capabilities.
  • Dobson, A.T., 2014. Cost Prediction Via Quantitative Analysis of Complexity in Ship Building. MSc Thesis, Massachusetts Institute of Technology, USA
  • Goodrum, C.J., Shields, C.P.F., Singer, D.J., 2018. Understanding cascading failures through a vulnerability analysis of interdependent ship-centric distributed systems using networks. Ocean Eng. 150, 36–47.
  • Gravil, K., Hayes, C., Mistery, A., 2014. How to exploit fundamental design modularity to obtain cost-effective life extension and through-life capability management for submarines, in: 12th International Naval Engineering Conference and Exhibition. pp. 270–285. Amsterdam, Netherlands.
  • INCOSE, 2015. Systems Engineering Handbook 4E.
  • Keane, R.G., Mierzwicki, T., Grogan, G., 2017. Designing Out Complexity Early: A Path to Affordable Flexible Warships. Nav. Eng. J. 129, 25–40.
  • Koc, Y., Warnier, M., Kooij, R.E., Brazier, F.M.T., 2013. A robustness metric for cascading failures by targeted attacks in power networks. 2013 10th IEEE Int. Conf. Networking, Sens. Control. ICNSC 2013 48–53.
  • Kott, A.; Abdelzaher, T. 2014 Resiliency and Robustness of Complex Systems and Networks. Adapt. Dyn. Resilient Syst. 67, 67–86.
  • Luo, J., 2015. A simulation-based method to evaluate the impact of product architecture on product evolvability. Res. Eng. Des. 26, 355–371.
  • Maier, M.W., Rechtin, E., 2000. The Art of Systems Architecting - Second Edition, New York.
  • Mehrpouyan, H., Haley, B., Dong, A., Tumer, I.Y., Hoyle, C., 2014. Resiliency analysis for complex engineered system design. Artif. Intell. Eng. Des. Anal. Manuf. AIEDAM 29, 93–108.
  • Newman, M., 2010. Networks: an introduction.
  • Newmann, M.E.J., 2003. The structure and function of complex networks. SIAM Rev. 45, 167–256.
  • Raz, A.K., DeLaurentis, D.A., 2017. System-of-Systems Architecture Metrics for Information Fusion: A Network Theoretic Formulation. AIAA Inf. Syst. Infotech @ Aerosp. 1–14.
  • Rebentisch, E., Schuh, G., Riesener, M., Breunig, S., Pott, A., Sinha, K., 2016. Assessment of Changes in Technical Systems and their Effects on Cost and Duration based on Structural Complexity. Procedia CIRP
  • Rigterink, D.T., 2014. Methods for Analyzing Early Stage Naval Distributed Systems Designs, Employing Simplex, Multislice, and Multiplex Networks. PhD Thesis, University of Michigan, USA.
  • Sinha, K., 2014. Structural Complexity and its Implications for Design of Cyber Physical Systems. PhD Thesis, Massachusetts Institute of Technology, USA.
  • Sinha, K., Suh, E.S., 2017. Pareto-optimization of complex system architecture for structural complexity and modularity. Res. Eng. Des. 29, 1–19. Conference