A Low-Cost Vision-Based Monitoring of Computer Numerical Control (CNC) Machine Tools for Small and Medium-Sized Enterprises (SMEs)

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.

Medienart:

E-Artikel

Erscheinungsjahr:

2019

Erschienen:

2019

Enthalten in:

Zur Gesamtaufnahme - volume:19

Enthalten in:

Sensors (Basel, Switzerland) - 19(2019), 20 vom: 17. Okt.

Sprache:

Englisch

Beteiligte Personen:

Kim, Hyungjung [VerfasserIn]
Jung, Woo-Kyun [VerfasserIn]
Choi, In-Gyu [VerfasserIn]
Ahn, Sung-Hoon [VerfasserIn]

Links:

Volltext

Themen:

Journal Article
Machine tool monitoring
Open-source software
Optical character recognition
Small and medium-sized enterprises
Smart factory

Anmerkungen:

Date Completed 22.10.2019

Date Revised 08.01.2020

published: Electronic

Citation Status PubMed-not-MEDLINE

doi:

10.3390/s19204506

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM302336826