Chong, Bin Hong (2023) A study and development of computer vision measurement system: performance evaluation towards improvement on fabrication for end mill cutting tool. Masters thesis, Universiti Tun Hussein Onn Malaysia.

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Abstract

Precision manufacturing demand has continuously risen in the manufacturing industry due to the market's need for mobility in the size of technological products. As a result, the manufacturing sector's predominant trend has shifted toward tiny but precise applications such as semiconductors, die & moulding, and precision cutting tools. As a result, quality control has become the most important aspect of the production process to guarantee that the dimensions and final output fulfil consumer expectations. Tight tolerance and high accuracy in dimension have become important considerations for the precision end mill cutting tool manufacturing industry in order to meet market demand in precision manufacturing. As a consequence, manufacturers of end mill cutting tools invest in thorough inspection and measuring equipment. A computer vision measuring system with high accuracy and simplicity in structure has been created to enhance the quality of end mill cutting tool goods in terms of geometry dimension measurement. The equipment used standard components such as servo motors, DC motors, pneumatics, and computer vision systems, all of which are low- maintenance and long-lasting. The open-source platform Node-red was used to provide the application's graphical user interface, while the Python language was used as the major language throughout measurement module development. End mill cutting tool geometry characteristics such as cutting diameter, radial runout, corner radius, and ballnose radius were all measured in the measurement module. The created measuring system's performance was assessed by comparing it to a commercial device, the Zoller Venturion. The percentage of improvement in terms of standard deviation for diameter, runout, ballnose radius, and corner radius during performance revision was 52.9%, 66.7%, 75.0%, and 83.3%, respectively, which is regarded substantial for improvement activities. The four study goals were met, and a highly reliable but sustainable computer vision measuring equipment for end mill cutting tools was produced

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