Article detail · 2024
State-of-the-art review of applications of image processing techniques for tool condition monitoring on conventional machining processes
Journal
The International Journal of Advanced Manufacturing TechnologyISSN 0268-3768
The ISSN points to another catalog journal; the name is from the YÖKSİS record.
- Year
- 2024
- Type
- article
Data source split
- YÖKSİS YÖKSİS article record
- YÖKSİS venue The International Journal of Advanced Manufacturing Technology
- Catalog match (ISSN) International Journal of Advanced Manufacturing Technology
- OpenAlex OpenAlex enrichment (abstract, citations, topics)
Abstract
OpenAlex · English
Abstract In conventional machining, one of the main tasks is to ensure that the required dimensional accuracy and the desired surface quality of a part or product meet the customer needs. The successful accomplishment of these parameters in milling, turning, milling, drilling, grinding and other conventional machining operations directly depends on the current level of tool wear and cutting edge conditions. One of the proven non-contact methods of tool condition monitoring (TCM) is measuring systems based on image processing technologies that allow assessing the current state of the machined surface and the quantitative indicators of tool wear. This review article discusses image processing for tool monitoring in the conventional machining domain. For the first time, a comprehensive review of the application of image processing techniques for tool condition monitoring in conventional machining processes is provided for both direct and indirect measurement methods. Here we consider both applications of image processing in conventional machining processes, for the analysis of the tool cutting edge and for the control of surface images after machining. It also discusses the predominance, limitations and perspectives on the application of imaging systems as a tool for controlling machining processes. The perspectives and trends in the development of image processing in Industry 4.0, namely artificial intelligence, smart manufacturing, the internet of things and big data, were also elaborated and analysed.
Topics
Citations
OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.
83 citations
OpenAlex cited_by_count (cache / database)
4 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).
- Assessing sine and Gaussian fitting for surface feature extraction in real-time wear monitoring of turning operations 2025
- Assessing sine and Gaussian fitting for surface feature extraction in real-time wear monitoring of turning operations 2025
- Investigation of Wear Behavior of Composite CYSZ Coating Under Different Loads 2024
- Investigation of Wear Behavior of Composite CYSZ Coating Under Different Loads 2024