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A Conceptual Framework for Estimating the Remaining Operational Lifetime of the Recovered Components from End of Life Aircraft Using Fuzzy Simulation and Digital Twin

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Intelligent and Fuzzy Techniques in Aviation 4.0

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 372))

Abstract

Industry 4.0 promotes product lifecycle management and promises to provide digital models and integrating product lifecycle data. Aviation 4.0 addresses the implications of the fourth industrial revolution in the operation and management of aircraft during their lifecycles. The management of the end of life (EoL) phase of aircraft is essential and contains uncertainty data. The revenue from recovered parts plays an important role in the sustainability of the EoL aircraft business. Estimating the operational life of high-value parts is critical in EoL decision-making. This chapter proposes a framework including use of fuzzy simulation and digital twins to estimate the remaining useful life (RUL) of recovered parts. The proposed framework contains three digital models including the digital twins of parts health management, disassembly process, and recovered parts. A fuzzy intelligent decision-making model generates the rules based on sensor measurements and operational settings for the estimation of the RUL of a part. The application of the model related to aircraft engines is discussed.

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Authors and Affiliations

  1. Department of Mathematical and Industrial Engineering, Polytechnique Montreal, Montreal, Quebec, Canada

    Samira Keivanpour

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  1. Samira Keivanpour
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Correspondence to Samira Keivanpour .

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Editors and Affiliations

  1. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Turkey

    Cengiz Kahraman

  2. Air Force Academy, National Defence University, Istanbul, Turkey

    Serhat Aydın

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Keivanpour, S. (2022). A Conceptual Framework for Estimating the Remaining Operational Lifetime of the Recovered Components from End of Life Aircraft Using Fuzzy Simulation and Digital Twin. In: Kahraman, C., Aydın, S. (eds) Intelligent and Fuzzy Techniques in Aviation 4.0. Studies in Systems, Decision and Control, vol 372. Springer, Cham. https://doi.org/10.1007/978-3-030-75067-1_13

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