Loughborough University
Leicestershire, UK
LE11 3TU
+44 (0)1509 263171

Advanced VR Research Centre

Systems Integration Network Uncertainty (SINU)

‌Background

SINU is a pilot study for a new approach to analyse the risk of time scale overruns in large scale systems integration projects. This approach assumes that overruns occur within even the best managed project and aims to analyse the inter business factors that contribute to the overruns.

Unfortunately, overruns can cause significant financial losses in large engineering projects and, even if they are unavoidable, an understanding of why they occur could help managing and minimise the impact on cost and time.

Recent theoretical, modelling and empirical studies of financial and other markets suggest that their networks exhibit Self Organised Criticality (SOC) such that the statistics of the market fluctuations are of the Pareto-Levy kind.

Pareto-Levy statistics are characterised by a 'fat-tail' where extreme fluctuations are much more likely than would be expected from normal Gaussian statistics.

Objectives of SINU

This initial study seeks to establish through modelling the sensitivity of the parameters and the probability of unexpectedly long delays and extra cost in the system integration phase.

Scope

  • SOC theory is applied to bounded network simulation rather than continuous networks
  • Simulations are based on time to complete the required task and deliver a product to the customer
  • The cost of project overruns was not considered

Research Activities

  • A simulation based approach has been used to analyse and apply SOC theory to complex, business networks with a large number of external links.

  • An integrated supply chain model has been developed to model both service and inventory supply chains which was considered to be a more realistic representation of the actual system.

Planned Research Outputs

  • Derive metrics that relate the probability of system integration delays to size, scope and complexity of the network within which the supplier base exists
  • Estimate time/cost contingency that should be allowed for unforeseen risks in large system integration
  • Derive guidelines for designing the supply chain to minimise the effect of market fluctuations based on optimising the design structure matrix for the system integration under consideration.

This study has resulted in a comprehensive report to the project funding body and a research paper.

Project Consortium

Funding from the Systems Engineering Autonomous Systems Defence Technology Centre (SEAS DTC) is gratefully acknowledged.

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