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Digital Twin and PHM for Optimizing Inventory Levels

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Production Research (ICPR-Americas 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1407))

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Abstract

Intelligent manufacturing associated with the advent of industry 4.0 marks a new era associated with technological solutions. Physical and virtual systems (CPS) are employed to improve processes and operations in a highly competitive environment. In this context, digital twin (DT) and asset health prognosis and management (PHM) play a fundamental role in manufacturing, allowing, through monitoring and analysis by physical and virtual means, to maximize the use of assets with estimated remaining life (RUL) and minimize unscheduled interruptions. This article proposes an extension to this context addressing the optimization of the inventory of materials and spare parts, representing a significant value that is often immobilized without expected use, causing a financial impact on organizations. It’s evaluated in the literature the use of DT and PHM related to the control of spare parts and gaps found, and opportunities to be addressed.

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Authors and Affiliations

  1. Pontifical Catholic University of Paraná, Curitiba, Brazil

    Joceir Chaves, Eduardo F. R. Loures, Eduardo A. P. Santos, Julio C. Silva & Ricardo Kondo

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  1. Joceir Chaves
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  2. Eduardo F. R. Loures
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  3. Eduardo A. P. Santos
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  4. Julio C. Silva
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  5. Ricardo Kondo
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Editor information

Editors and Affiliations

  1. Universidad Nacional del Sur and CONICET, Bahía Blanca, Argentina

    Daniel Alejandro Rossit

  2. Universidad Nacional del Sur and CONICET, Bahía Blanca, Argentina

    Fernando Tohmé

  3. Universidad de la Sabana, Chía, Colombia

    Gonzalo Mejía Delgadillo

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Chaves, J., Loures, E.F.R., Santos, E.A.P., Silva, J.C., Kondo, R. (2021). Digital Twin and PHM for Optimizing Inventory Levels. In: Rossit, D.A., Tohmé, F., Mejía Delgadillo, G. (eds) Production Research. ICPR-Americas 2020. Communications in Computer and Information Science, vol 1407. Springer, Cham. https://doi.org/10.1007/978-3-030-76307-7_24

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  • DOI: https://doi.org/10.1007/978-3-030-76307-7_24

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