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Infrastructure Resilience Conference 2018

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Resilience Quantification and Development Process Applied to Ultrasound Indoor Localization System

In the last decades many resilience concepts have emerged which comprise methods to assess and control consequences in case of disruptive events of socio technical systems with the aim of improving resilience behaviour. However, previous studies are often very generic and vague, such that specific applications to real systems are challenging. The present approach addresses the application of a resilience quantification and development concept to an ultrasound indoor localization system, which is relevant e.g. for the performance of production nodes and supply logistic nodes of modern infrastructures. In particular, it can be used for locating goods or robots in storehouses. For a systematic implementation, an already presented process in eight steps is partially implemented: (1) system and context definition, (2) identification of system performance functions and related quantities, especially in undisturbed operation mode, (3) identification of possible disruptive events and threats, (4) (pre-)identification of critical combinations of disruptions and performance functions e.g. by using a resilience criticality matrix of combinations of performance functions and disruptions, (5) definitions of (broad) scenarios for detailed resilience assessment, (6) refined resilience assessment and analyses, (7) resilience evaluation, and (8) selection and implementation of design improvements. Based on a comprehensive assessment of critical combinations, practical scenarios are selected to simulate the effects of disruptions on the system performance, e.g., changes of the localization accuracy caused by initiated receiver losses, mechanical coverage or drop of the ambient temperature. Based on experimental quantifications and an inductive and deductive analytical system resilience quantification, different improvements of the system are proposed which can be applied to existing systems as well as newly developed systems on hardware and software level. The study also shows how different resilience cycle phases, e.g. prevent, absorb, response and recover, can be linked and tailored to the indoor logistic example by using suitable system (non-) performance measures. Furthermore, it will be indicated how informed real-time selection of localization algorithms can be used to generate adaptive intelligent behaviour of the system countering disruptions.

Ivo Häring
Fraunhofer Ernst-Mach-Institut, EMI, Freiburg, Germany
Germany

Johannes Scheidereiter
Fraunhofer Ernst-Mach-Institut, EMI, Freiburg, Germany
Germany

Stefan Ebenhöch
Fraunhofer Ernst-Mach-Institut, EMI, Freiburg, Germany
Germany

Dominik Jan Schott
Departement of Microsystems Engineering, University of Freiburg, Germany
Germany

Fabian Höflinger
Departement of Microsystems Engineering, University of Freiburg, Germany
Germany

 

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