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Optimizing the Life Cycle of Physical Assets through an Integrated Life Cycle Assessment Method

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  • José Edmundo de Almeida Pais

    (EIGeS—Research Centre in Industrial Engineering, Management and Sustainability, Lusófona University, 376, 1749-024 Lisboa, Portugal
    CISE—Electromechatronic Systems Research Centre, University of Beira Interior, 6201-001 Covilhã, Portugal)

  • Hugo D. N. Raposo

    (Centre for Mechanical Engineering, Materials and Processes (CEMMPRE), University of Coimbra, 3030-788 Coimbra, Portugal
    Instituto Superior de Engenharia de Coimbra, Polytechnic of Coimbra, 3030-199 Coimbra, Portugal)

  • José Torres Farinha

    (Centre for Mechanical Engineering, Materials and Processes (CEMMPRE), University of Coimbra, 3030-788 Coimbra, Portugal
    Instituto Superior de Engenharia de Coimbra, Polytechnic of Coimbra, 3030-199 Coimbra, Portugal)

  • Antonio J. Marques Cardoso

    (CISE—Electromechatronic Systems Research Centre, University of Beira Interior, 6201-001 Covilhã, Portugal)

  • Pedro Alexandre Marques

    (EIGeS—Research Centre in Industrial Engineering, Management and Sustainability, Lusófona University, 376, 1749-024 Lisboa, Portugal)

Abstract

The purpose of this study was to apply new methods of econometric models to the Life Cycle Assessment (LCA) of physical assets, by integrating investments such as maintenance, technology, sustainability, and technological upgrades, and to propose a means to evaluate the Life Cycle Investment (LCI), with emphasis on sustainability. Sustainability is a recurrent theme of existing studies and will be a concern in coming decades. As a result, equipment with a smaller environmental footprint is being continually developed. This paper presents a method to evaluate asset depreciation with an emphasis on the maintenance investment, technology depreciation, sustainability depreciation, and technological upgrade investment. To demonstrate the value added of the proposed model, it was compared with existing models that do not take the previously mentioned aspects into consideration. The econometric model is consistent with asset life cycle plans as part of the Strategic Asset Management Plan of the Asset Management System. It is clearly demonstrated that the proposed approach is new and the results are conclusive, as demonstrated by the presented models and their results. This research aims to introduce new methods that integrate the factors of technology upgrades and sustainability for the evaluation of assets’ LCA and replacement time. Despite the increase in investment in technology upgrades and sustainability, the results of the Integrated Life Cycle Assessment First Method (ILCAM1), which represents an improved approach for the analyzed data, show that the asset life is extended, thus increasing sustainability and promoting the circular economy. By comparison, the Integrated Life Cycle Investment Assessment Method (ILCIAM) shows improved results due to the investment in technology upgrades and sustainability. Therefore, this study presents an integrated approach that may offer a valid tool for decision makers.

Suggested Citation

  • José Edmundo de Almeida Pais & Hugo D. N. Raposo & José Torres Farinha & Antonio J. Marques Cardoso & Pedro Alexandre Marques, 2021. "Optimizing the Life Cycle of Physical Assets through an Integrated Life Cycle Assessment Method," Energies, MDPI, vol. 14(19), pages 1-24, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:19:p:6128-:d:643457
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    1. Caropul Mendes & Hugo Raposo & Ricardo Ferraz & José Torres Farinha, 2023. "The Economic Management of Physical Assets: The Practical Case of an Urban Passenger Transport Company in Portugal," Sustainability, MDPI, vol. 15(15), pages 1-19, July.
    2. Alexandre Martins & Balduíno Mateus & Inácio Fonseca & José Torres Farinha & João Rodrigues & Mateus Mendes & António Marques Cardoso, 2023. "Predicting the Health Status of a Pulp Press Based on Deep Neural Networks and Hidden Markov Models," Energies, MDPI, vol. 16(6), pages 1-26, March.
    3. João Antunes Rodrigues & Alexandre Martins & Mateus Mendes & José Torres Farinha & Ricardo J. G. Mateus & Antonio J. Marques Cardoso, 2022. "Automatic Risk Assessment for an Industrial Asset Using Unsupervised and Supervised Learning," Energies, MDPI, vol. 15(24), pages 1-17, December.

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