Analysis of Traditional vs. Industry 4.0 Methodology in Predictive and Preventive Maintenance of Industrial Machines: Systematic Review

Autores/as

  • Alan Elías Mora Universidad Tecnológica Del Perú
  • Juan Martin Campos Universidad Tecnológica Del Perú
  • Oscar Rafael Mansilla Alza Universidad Tecnológica Del Perú
  • Alberto Deyvid Coello Acosta Universidad Tecnológica Del Perú

DOI:

https://doi.org/10.18687/LACCEI2025.1.1.817

Palabras clave:

word: Industry 4.0, IoT, AI, maintenance.

Resumen

This research compares the traditional methodology with Industry 4.0 in the maintenance of industrial machines. Traditional methods, including preventive, corrective, condition-based maintenance, and TPM, are effective, but have significant limitations such as long downtime and high costs. On the other hand, Industry 4.0 uses advanced technologies such as the Internet of Things (IoT), artificial intelligence (AI) and data analysis to offer more automated and efficient production. These tools enable continuous monitoring and early failure detection, reducing unplanned downtime and improving efficiency and productivity. Industry 4.0 is gradually replacing traditional methods, especially in developing countries, where these new methodologies are significantly improving maintenance processes. It is worth mentioning that Industry 4.0 is still being implemented in this field, and most of the current results are qualitative. It is expected that future research will allow for more detailed and efficient comparisons

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Publicado

2025-04-09

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Articles

Cómo citar

Mora, A. E., Campos, J. M., Mansilla Alza, O. R., & Coello Acosta, A. D. (2025). Analysis of Traditional vs. Industry 4.0 Methodology in Predictive and Preventive Maintenance of Industrial Machines: Systematic Review. LACCEI, 1(12). https://doi.org/10.18687/LACCEI2025.1.1.817

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