The fourth industrial revolution, Industry 4.0, has brought internet, artificial intelligence (AI),
and machine learning (ML) concepts into manufacturing. There is an immediate need to …

Existing computer vision methods to measure surface roughness rely on feature extraction to
quantify the surface morphology and build prediction models. However, the feature …

Computer vision provides image-based solutions to inspect and investigate the quality of the
surface to be measured. For any components to execute their intended functions and …

Research on specimen surface roughness is crucial because of its impact on machined
components' functionality. In the meanwhile, a vision system is a cutting-edge method that is …

The present paper focuses on evaluation of surface roughness (R a) in incrementally formed
parts by different image processing based methods. For this, twenty-seven parts are formed …

Monitoring surface quality during machining has considerable practical significance for the
performance of high-value products, particularly for their assembly interfaces. Surface …

A ground surface roughness measurement method is proposed to address current problems
in the use of machine vision technology to measure roughness: the calculations are …

For condition monitoring and predictive maintenance of high-end manufacturing equipment,
surface roughness is a critical metric to evaluate machining quality. Designing a method that …

Shape memory alloys (SMAs) have the unique ability to regain their shape under specified
conditions, making them extremely useful for a wide range of applications. However, non …

The traditional devices, used to measure the surface roughness, are very sensitive, and they
are obtained by scratching the surface of materials. Therefore, the optic systems are used as …