Enhancing Business Resilience: Predicting Hard Disk Failures with Machine Learning for Efficient Resource Management

Author(s)	Rajasee Thakre, Shruti Kulkarni, Anushka Kulkarni, Jayesh Suryawanshi
Country	India
Abstract	In today's data-driven business landscape, maintaining the resilience of digital infrastructure is paramount. One of the most critical components of this infrastructure is the hard disk drive (HDD). The potential for HDD failures poses a significant risk to data integrity and operational continuity. To address this challenge, this paper presents an innovative approach to enhancing business resilience through the predictive analysis of hard disk drive failures using machine learning techniques. Our research leverages machine learning algorithms to predict HDD failures, enabling organizations to proactively manage resources and mitigate potential disruptions. By harnessing historical data, system behavior patterns, and SelfMonitoring, Analysis, and Reporting Technology (S.M.A.R.T.) metrics, our model can accurately forecast when an HDD is likely to fail. This predictive capability empowers organizations to optimize resource allocation, reduce downtime, and enhance data security.
Keywords	Hard Disk Drive, Predictive Modeling, Resource Efficiency, Downtime Reduction
Field	Engineering
Published In	Volume 5, Issue 5, September-October 2023
Published On	2023-09-17
DOI	https://doi.org/10.36948/ijfmr.2023.v05i05.6521

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