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A Low-Cost Vision-Based Monitoring of Computer Numerical Control (CNC) Machine Tools for Small and Medium-Sized Enterprises (SMEs)
- Source :
- Sensors, Volume 19, Issue 20, Sensors, Vol 19, Iss 20, p 4506 (2019), Sensors (Basel, Switzerland)
- Publication Year :
- 2019
- Publisher :
- Multidisciplinary Digital Publishing Institute, 2019.
-
Abstract
- In the new era of manufacturing with the Fourth Industrial Revolution, the smart factory is getting much attention as a solution for the factory of the future. Despite challenges in small and medium-sized enterprises (SMEs), such as short-term strategies and labor-intensive with limited resources, they have to improve productivity and stay competitive by adopting smart factory technologies. This study presents a novel monitoring approach for SMEs, KEM (keep an eye on your machine), and using a low-cost vision, such as a webcam and open-source technologies. Mainly, this idea focuses on collecting and processing operational data using cheaper and easy-to-use components. A prototype was tested with the typical 3-axis computer numerical control (CNC) milling machine. From the evaluation, availability of using a low-cost webcam and open-source technologies for monitoring of machine tools was confirmed. The results revealed that the proposed system is easy to integrate and can be conveniently applied to legacy machine tools on the shop floor without a significant change of equipment and cost barrier, which is less than $500 USD. These benefits could lead to a change of monitoring operations to reduce time in operation, energy consumption, and environmental impact for the sustainable production of SMEs.
- Subjects :
- 0209 industrial biotechnology
optical character recognition
business.product_category
Computer science
open-source software
small and medium-sized enterprises
02 engineering and technology
lcsh:Chemical technology
Biochemistry
Article
Analytical Chemistry
020901 industrial engineering & automation
0202 electrical engineering, electronic engineering, information engineering
lcsh:TP1-1185
Factory
Environmental impact assessment
Electrical and Electronic Engineering
Industrial Revolution
Instrumentation
Productivity
smart factory
Atomic and Molecular Physics, and Optics
Manufacturing engineering
Machine tool
machine tool monitoring
Numerical control
Factory (object-oriented programming)
020201 artificial intelligence & image processing
business
Subjects
Details
- Language :
- English
- ISSN :
- 14248220
- Database :
- OpenAIRE
- Journal :
- Sensors
- Accession number :
- edsair.doi.dedup.....b2cc0e51a8b5bcc0f40e45de3c6de98c
- Full Text :
- https://doi.org/10.3390/s19204506