AADL-Based Stochastic Error Propagation Analysis for Reliable System Design of a Medical Patient Table

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Contributors

Abstract

This paper introduces a new method for stochastic error propagation analysis of mechatronic systems designed with Architecture Analysis Design Language (AADL). The analysis is based on a formal Dual-graph Error Propagation Model (DEPM). This model captures control and data flow aspects and reliability properties of system components and allows the quantitative system reliability evaluation using underlying Markov chain models. This paper describes an automatic transformation algorithm from AADL to DEPM that identifies data and control flow transitions between devices, processes and threads of an AADL model and generates a DEPM for further error propagation analysis. An integrated third-party scheduling tool Cheddar helps to generate control flow sequences that are transformed into a stochastic control flow graph of the DEPM. The generated DEPM allows a user to specify fault activation probabilities for particular system components and numerically analyze error propagation to critical outputs. The introduced method is illustrated with a reliability analysis of a mobile medical patient table.

Details

Original languageEnglish
Title of host publication2018 Annual Reliability and Maintainability Symposium, RAMS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (print)9781538628706
Publication statusPublished - 11 Sept 2018
Peer-reviewedYes

Publication series

SeriesAnnual Symposium on Reliability and Maintainability (RAMS)
Volume2018-January
ISSN2577-0993

Conference

Title2018 Annual Reliability and Maintainability Symposium, RAMS 2018
Duration22 - 25 January 2018
CityReno
CountryUnited States of America

External IDs

Scopus 85054138194

Keywords

Keywords

  • AADL, Control flow, Data flow, Error Propagation Analysis, Healthcare, Model-to-model Transformation, Reliability Modeling