Predictive Maintenance for IT Infrastructure: A Machine Learning Approach

Abdulaziz N Mansouri1

1

Publication Date: 2024/12/13

Abstract: As IT infrastructure grows in complexity, proactive maintenance strategies are becoming increasingly crucial. Traditional reactive maintenance approaches often fail to prevent failures and optimize resource utilization. This research proposes a machine learning-based approach to predictive maintenance to anticipate potential hardware failures in IT infrastructure components. The model can schedule preventive maintenance interventions by analyzing historical data and real-time sensor readings, minimizing downtime and reducing operational costs. The methodology involves data collection, preprocessing, feature engineering, feature selection, model development, and deployment. Various machine learning algorithms are explored, including time series forecasting, anomaly detection, and classification. The paper also discusses ethical considerations and future research directions, such as hybrid approaches, explainable AI, transfer learning, continuous learning, and edge computing

Keywords: No Keywords Available

DOI: https://doi.org/10.5281/zenodo.14437188

PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT24NOV1431.pdf

REFERENCES

  1. Li, Y., Han, J., & Kaminski, J. (2017). Predictive maintenance with big data: A survey. IEEE Transactions on Industrial Informatics, 13(4), 1417-1427.
  2. Schouten, J. C., & Dekker, R. (2018). A review of predictive maintenance: Literature review and directions for future research. European Journal of Operational Research, 269(1), 1-24.
  3. Jardine, A. K. S., Lin, D., & Banjevic, D. (2006). A review on machinery diagnostics and prognostics using artificial intelligence techniques. Computers & Industrial Engineering, 51(1), 148-159.
  4. Wang, W., Wang, W., & Li, X. (2017). A review of the applications of machine learning in predictive maintenance. Reliability Engineering & System Safety, 164, 1-10.
  5. Saxena, A., Celaya, J., Balestrassi, J. P., & Paul, D. B. (2008). Predictive maintenance: A review of methods and techniques. IEEE Transactions on Industrial Informatics, 4(1), 14-20.
  6. Lee, J., Zhang, Y., & Bagler, S. (2017). A review of machine learning applications in predictive maintenance of manufacturing equipment. International Journal of Precision Engineering and Manufacturing-Technology, 18(2), 213-224