Exploring the application of the Internet of Things in precision machining by comparative text mining

Abstract

Precision machining, manufacturing components with superior surface quality and dimensional accuracy, increasingly leverages Internet of Things (IoT) technologies. This study employs a novel comparative text mining approach by systematically integrating tree maps, word clouds, keyword network analysis, and Pearson correlation to identify critical linkages between IoT and precision machining. By analyzing a scientific research database (2019–2023), this study highlights IoT's core competencies in enhancing precision machining, including real-time monitoring, predictive maintenance, and data-driven optimization. Furthermore, this study proposes actionable strategies, including neural network-based cyber production systems, blockchain-integrated IIoT platforms, and machine learning-driven predictive models, for precision machining. These recommendations empower academia and industry to harness IoT to improve product quality and reduce costs in precision machining. This article is categorized under: Algorithmic Development > Text Mining Fundamental Concepts of Data and Knowledge > Knowledge Representation Technologies > Data Preprocessing