Beyond Traditional Methods: Data Mining for Next-Generation Reliability Assessment

Abstract

The advent of Industry 4.0, marked by intricate machinery and systems, has brought to the fore an urgent need for robust reliability assessment methods. These methods are crucial to ensure the uninterrupted performance of industrial systems. While traditional techniques have been the go-to for reliability assessment, they often fall short of capturing the wealth of data that modern systems generate. This study explores the potential of data mining to enhance reliability assessment in industrial settings. Data mining offers powerful tools to discover hidden patterns and insights within this data. Unlike traditional methods, data mining can uncover these patterns without preconceived assumptions, leading to a more comprehensive understanding of system behavior. By leveraging these techniques, the goal is to enhance the reliability of industrial systems by uncovering hidden insights and patterns.