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http://bura.brunel.ac.uk/handle/2438/29791
Title: | An intelligent metrology informatics system based on neural networks for multistage manufacturing processes |
Authors: | Papananias, M McLeay, TE Mahfouf, M Kadirkamanathan, V |
Keywords: | multistage manufacturing;intelligent/smart manufacturing;manufacturing informatics;artificial neural networks |
Issue Date: | 5-Jul-2019 |
Publisher: | Elsevier |
Citation: | Papananias, M. et al. (2019) 'An intelligent metrology informatics system based on neural networks for multistage manufacturing processes', Procedia CIRP, 82, pp. 444 - 449. doi: 10.1016/j.procir.2019.04.148. |
Abstract: | The ability to gather manufacturing data from various workstations has been explored for several decades and the advances in sensory and data acquisition techniques have led to the increasing availability of high-dimensional data. This paper presents an intelligent metrology informatics system to extract useful information from Multistage Manufacturing Process (MMP) data and predict part quality characteristics such as true position and circularity using neural networks. The input data include the tempering temperature, material conditions, force and vibration while the output data include comparative coordinate measurements. The effectiveness of the proposed method is demonstrated using experimental data from a MMP. |
URI: | https://bura.brunel.ac.uk/handle/2438/29791 |
DOI: | https://doi.org/10.1016/j.procir.2019.04.148 |
Other Identifiers: | ORCiD: Moschos Papananias https://orcid.org/0000-0001-7121-9681 |
Appears in Collections: | Dept of Mechanical and Aerospace Engineering Research Papers |
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FullText.pdf | Copyright © 2019 The Author(s). Published by Elsevier B.V. This is an open access article under a Creative Commons license (https://creativecommons.org/licenses/by-nc-nd/4.0/). | 1.24 MB | Adobe PDF | View/Open |
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