Roundness Holes’ Measurement for milled workpiece using machine vision inspection system based on IoT structure: A case study

圆度(物体) MQTT公司 坐标测量机 机器视觉 计量学 计量系统 工程类 云计算 实时计算 计算机科学 机械工程 工程制图 物联网 计算机视觉 嵌入式系统 数学 统计 物理 操作系统 天文
作者
Yazid Saif,Yusri Yusof,Kamran Latif,Aini Zuhra Abdul Kadir,Maznah binti lliyas Ahmed,Anbia Adam,Noor Hatem,Danish Ali Memon
出处
期刊:Measurement [Elsevier BV]
卷期号:195: 111072-111072 被引量:24
标识
DOI:10.1016/j.measurement.2022.111072
摘要

Manufacturing Metrology is a vital aspect of the sophisticated industrial 4.0-based manufacturing industry, as practically everything machined with certain metrological systems has to be measured or inspected. The Internet of Things (IoT) is a critical technology for industry 4.0 development. Furthermore, modern industrial devices should communicate via local (edge) and cloud computing servers. The Message Queuing Telemetry Transport (MQTT) protocol intends to increase the performance for sending/receiving roundness holes’ data measuring from /to the server-based cloud. An error in its roundness mainly involves the inspection of circular portions. Roundness errors generate assemblies, lubricant distribution, and rotational force creation challenges. This study proposed applying the 3SMVI system and validating the system's by utilising the minimum zone circle tolerance algorithm to provide the precise error value and determine the roundness circle's error between the five circles. Hence, the approach is currently used for measuring the roundness circle error in the camera industry throughout the manufacture of components. The experiment was conducted using the smart system based on interpreted STEP-NC files for machine vision inspection (3SMVI) for non-contact and Coordinate Measuring Machine (CMM) for contact approaches by comparing the results. The Contact Measurement Method (CMM) is one of the most precise and time-consuming ways to inspect a round object for imperfections. The article validates the development of the 3SMVI system based on IoT architecture by utilising image processing technologies to measure errors in the circular roundness that can overcome these difficulties. The findings of both approaches showed a difference between 4.6 µm and 9.6 µm. However, Precession can be enhanced by a high-resolution camera with the right light.
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