The Role of Augmented Reality in Achieving the Goals of Metrology 4.0


Industry 4.0 technologies are transforming how manufacturing systems operate, creating data-rich environments and unleashing new methods and paradigms to solve old and emerging challenges. Manufacturers face major metrology challenges to achieve dependable (e.g., accurate, timely, traceable) measurement, inspection, and quality control systems, which highly impacts on product costs, time to market and, ultimately, on businesses’ competitiveness. Metrology 4.0 has recently emerged as a new term referring to the deployment of I4.0 technologies to advance manufacturing metrology processes. To date, there are urgent knowledge gaps on the understanding of the several I4.0 technologies and how they can support manufacturers improving their capabilities. To help bridging this gap, we’ve selected Augmented Reality (AR), an unexpensive core I4.0 technology that has shown widely success in advancing manufacturing systems in the recent years, to carry out a systematic review of the literature on its use to advance manufacturing metrology. The several types of AR technologies, its key features and applications are summarised and analysed considering the requirements of Metrology 4.0. The results will be presented to demonstrate and provide insights on the role of AR in achieving the goals of Metrology 4.0.

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Dr Lorena C. Moreira (LM) is a Research Fellow at the Institute for Advanced Manufacturing and Engineering (AME), Coventry University (UK). Her research focuses on the development of CPS systems for optimising process’ performance and traceability through predictive modelling and optimal control and connected workers under the research area of People-Centred Productivity (PCP). PCP’s purpose is to improve businesses productivity by deploying technologies that will enhance workers capabilities (e.g., use of ‘X’ reality and emerging technologies to enhance workers’ performance and well-being). LM is working with a multidisciplinary academic network; and has won prizes for her work, including Best Developmental Paper Award 2020 of the BAM and Best Paper Award of the CIRP 15th IMCC.