scholarly journals On Line Surface Roughness Measurement Using Labview And Vision Method For E Quality Control

2020 ◽  
Author(s):  
Richard Chiou ◽  
Michael Mauk ◽  
Yueh-Ting Yang ◽  
Robin Kizirian ◽  
Yongjin Kwon
2018 ◽  
Vol 144 ◽  
pp. 03008
Author(s):  
Ravi Kiran ◽  
H. J. Amarendra ◽  
Shashank Lingappa

Measurement of surface roughness is one of the quality control processes, usually carried out off line. Contact type surface roughness measurement method is commonly used in quality control. The processes consume lot of time with human interaction. In order to reduce or to eliminate non value added time, effective quality inspection tool and automation of the processes has to be utilized. An attempt has been made to automate the process with integration of vision camera in capturing the image of the component surface. The image process technique has the advantage of analyzing the single captured image for multiple area measurement. Hence, the in-line quality control of each component surface roughness measurement is ensured. The automation process involves component movement, image capturing, image processing, and decision making, using sensors, actuators and microcontroller. The proposed in-line quality control of surface roughness with vision system has been successfully developed. The designed automated system has fulfilled the objectives in respect of the scope of the present work.


2007 ◽  
Vol 104 (7-8) ◽  
pp. 348-353 ◽  
Author(s):  
W. Bilstein ◽  
W. Enderle ◽  
G. Moreas ◽  
D. Oppermann ◽  
T. Routschek ◽  
...  

2017 ◽  
Vol 137 (3) ◽  
pp. 147-152 ◽  
Author(s):  
Tetsuo Fukuchi ◽  
Norikazu Fuse ◽  
Mitsutoshi Okada ◽  
Tomoharu Fujii ◽  
Maya Mizuno ◽  
...  

2013 ◽  
Vol 465-466 ◽  
pp. 764-768 ◽  
Author(s):  
Tanel Aruväli ◽  
Tauno Otto

The paper investigates in-process signal usage in turning for indirect surface roughness measurement. Based on theoretical surface roughness value and in-process signal, a model is proposed for surface roughness evaluation. Time surface roughness and in-process signal surface roughness correlation based analysis is performed to characterize tool wear component behavior among others. Influencing parameters are grouped based on their behavior in time. Moreover, Digital Object Memory based solution and algorithm is proposed to automate indirect surface roughness measurement process.


Sensors ◽  
2013 ◽  
Vol 13 (9) ◽  
pp. 11772-11781 ◽  
Author(s):  
Félix Salazar ◽  
Alberto Barrientos

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