Technical data-driven tool condition monitoring challenges for CNC milling: a review
Document Type
Article
Publication Date
1-1-2020
Abstract
CNC milling is a highly complex machining process highly valued in various industries, including the automotive and aerospace industries. With the increasing competition, manufacturers are aiming to keep maintenance costs low while ensuring high levels of manufacturing equipment reliability. It is also highly important for them to maximize the service life of each cutting tool by avoiding premature replacements while minimizing the risks of scrap due to tool breakage. This calls for the need for a condition-based maintenance approach and more powerful, flexible and robust tool condition monitoring (TCM) techniques with minimal reliance on subjective diagnosis based on the expert knowledge. This paper discusses the technical aspects of recent developments in state-of-the-art TCM techniques and current challenges which limit the viability of TCM in real-life industrial applications. The technical challenges in modern TCM were split into two major groups of problems: (1) challenges in data processing and (2) issues regarding tool wear model performance. Current methodologies to overcome issues in each of the sections in this paper are discussed and, where possible, compared to highlight their respective advantages and disadvantages. Finally, this paper concludes with a discussion on possible trends in TCM development and interesting avenues for future research. © 2020, Springer-Verlag London Ltd., part of Springer Nature.
Keywords
CNC milling, Cutting tool health, Remaining useful life, Tool condition monitoring, Tool wear
Divisions
fac_eng
Funders
Fundamental Research Grant Scheme (FRGS) grant from the Malaysian Ministry of Higher Education with the grant no. FRGS/1/2017/TK04/UM/02/4
Publication Title
The International Journal of Advanced Manufacturing Technology
Volume
107
Issue
11-12
Publisher
Springer Verlag