Metrology Process to Produce High-Value Components and Reduce Waste for the Fourth Industrial Revolution

Abstract

Conventionally, a manufactured product undergoes a quality control process. The quality control department mostly ensures that the dimensions of the manufactured products are within the desired range, i.e., the product either satisfies the defined conformity range or is rejected. Failing to satisfy the conformity range increases the manufacturing cost and harms the production rate and the environment. Conventional quality control departments take samples from the given batch after the manufacturing process. This, in turn, has two consequences, i.e., low-quality components being delivered to the customer and input energy being wasted in the rejected components. The aim of this paper is to create a high-precision measuring (metrology)-based system that measures the dimension of an object in real time during the machining process. This is accomplished by integrating a vision-based system with image processing techniques in the manufacturing process. Experiments were planned using an experimental design which included different lightning conditions, camera locations, and revolutions per minute (rpm) values. Using the proposed technique, submillimeter dimensional accuracy was achieved at all the measured points of the component in real time. Manual validation and statistical analysis were performed to check the validity of the system.

Publication DOI: https://doi.org/10.3390/su14127472
Divisions: College of Engineering & Physical Sciences > School of Engineering and Technology > Mechanical, Biomedical & Design
Funding Information: This research was funded by Taif University, Taif, Saudi Arabia, under Taif University Researchers Supporting Project (TURSP-2020/121).
Additional Information: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Funding Information: This research was funded by Taif University, Taif, Saudi Arabia, under Taif University Researchers Supporting Project (TURSP-2020/121).
Uncontrolled Keywords: Industry 4.0,machine vision,metrology,quality control,Computer Science (miscellaneous),Geography, Planning and Development,Renewable Energy, Sustainability and the Environment,Building and Construction,Environmental Science (miscellaneous),Energy Engineering and Power Technology,Hardware and Architecture,Computer Networks and Communications,Management, Monitoring, Policy and Law
Publication ISSN: 2071-1050
Last Modified: 15 May 2024 07:20
Date Deposited: 14 Jul 2022 13:49
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://www.mdp ... 1050/14/12/7472 (Publisher URL)
PURE Output Type: Article
Published Date: 2022-06-19
Accepted Date: 2022-06-09
Authors: Junaid, Ahmad
Siddiqi, Muftooh Ur Rehman (ORCID Profile 0000-0002-7209-7863)
Tariq, Sundas
Muhammad, Riaz
Paracha, Ubaidullah
Ullah, Nasim
Al Ahmadi, Ahmad Aziz
Suleman, Muhammad
Habib, Tufail

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