INDUSTRY 4.0: INTELLIGENT QUALITY CONTROL AND SURFACE DEFECT DETECTION

被引:0
作者
Johnson, Vineeth C. [1 ]
Bali, Jyoti S. [1 ]
Kolanur, C. B. [1 ]
Tanwashi, Shilpa [1 ]
机构
[1] KLE Technol Univ, India, Hubballi 31, Karnataka, India
来源
3C EMPRESA | 2022年 / 11卷 / 02期
关键词
Quality Control; Industry; 4; 0; Internet of Things; Intelligent manufacturing; Interoperability; cutting-edge technologies; analytics; surface defect detection;
D O I
10.17993/3cemp.2022.110250.214-220
中图分类号
F [经济];
学科分类号
02 ;
摘要
Quality Control (QC) has recently emerged as a significant global trend among manufacturers, adopting intelligent manufacturing practices in view of Industry 4.0 requirements. Intelligent manufacturing is the process of enhancing production through the use of cutting-edge technologies, sensor integration, analytics, and the Internet of Things (IoT). The proposed paper mainly focuses on the study of the scope and the evolution of quality control techniques from conventional practices to intelligent approaches along with the state of art technologies in place. The challenges faced building intelligent QC systems, in terms of security, system integration, Interoperability, and Human robot collaboration, are highlighted. Surface defect detection has evolved as a critical QC application in modern manufacturing setups to ensure high-quality products with high market demand. Further, the recent trends and issues involved in surface defect detection using intelligent QC techniques are discussed. The methodology of implementing surface defect detection on cement wall surfaces using the Haar Cascade Classifier is discussed.
引用
收藏
页码:214 / 220
页数:7
相关论文
共 13 条
[11]  
Oztemel E., 2020, QUALITY CONTROL INTE, DOI [10.5772/intechopen.94971, DOI 10.5772/INTECHOPEN.94971]
[12]   Challenges, Opportunities and Future Directions of Smart Manufacturing: A State of Art Review [J].
Phuyal, Sudip ;
Bista, Diwakar ;
Bista, Rabindra .
SUSTAINABLE FUTURES, 2020, 2
[13]  
Sinha D, 2014, QUALITY CONTROL QC D