Open AccessPreliminary study of Augmented Reality based manufacturing for further integration of Quality Control 4.0 supported by metrology
Author(s) -
Petr Ho,
José Antonio Albajez,
J.A. Yagüe,
Jorge Santolaria
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1193/1/012105
Subject(s) - quality (philosophy) , augmented reality , automotive industry , computer science , productivity , manufacturing engineering , product (mathematics) , process management , control (management) , process (computing) , scopus , systems engineering , engineering , artificial intelligence , philosophy , geometry , mathematics , medline , epistemology , law , political science , operating system , economics , macroeconomics , aerospace engineering
Augmented Reality (AR) is a key technology enabling Industry 4.0, which enriches human perspectives by overlaying digital information onto the real world. The maturity of AR technology has grown recently. As processes in the automotive and aeronautic sectors require high quality and near-zero error rates to ensure the safety of end-users, AR can be implemented to facilitate workers with immersive interfaces to enhance productivity, accuracy and autonomy in the quality sector. In order to analyse whether there is a real and growing interest in the use of AR as assisting technology for manufacturing sector in general and quality control in particular, two specific research questions are defined. In addition, two well-known research databases (Scopus, Web of Science) are used for the paper selection phase in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to conduct a preliminary study and evaluate the current development of AR applications in manufacturing sector in order to answer the defined questions. It is found that while the development of AR technology has widely implemented to assign real-time information to several systems and processes in assembly and maintenance sectors, this tendency has only emerged in the quality sector over the last few years. However, AR-based quality control has proved its advantages in improving productivity, accuracy and precision of operators as well as benefits to manufacturing in terms of product and process quality control across different manufacturing phases.