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Article

Vision System Experimentation in Furniture Industrial Environment

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Control 2K, Waterton Technology Centre, Waterton Industrial Estate, Bridgend CF31 3WT, UK
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AIDIMME, Benjamin Franklin, 13 Parque Tecnológico, 46980 Paterna, Spain
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Author to whom correspondence should be addressed.
Academic Editors: Francesco Lelli and Stefano Modafferi
Future Internet 2021, 13(8), 189; https://doi.org/10.3390/fi13080189
Received: 17 May 2021 / Revised: 12 July 2021 / Accepted: 12 July 2021 / Published: 23 July 2021
The integration of devices that support manufacturing activities and the interaction of workers with these devices in production plants, leads to potential benefits in the industrial environment. Problems, bottlenecks and improvement opportunities throughout production times need to be detected, analyzed and prioritized in order to select the most suitable solutions and address them properly. The integration of particular devices supports the manufacturing process and prevents the need for contingency planning; it also increases the quality of the produced goods, which leads to higher customer confidence and satisfaction. The scope of this article focuses on the development and experimentation of a vision system for the recognition of product components in order to support the classification of such items by the users working in a particular area of the production line. Even if the proposed solution presents a low level of human interaction and innovation, the objective of this paper is to demonstrate how the proposed classification system brings valuable benefits to the overall manufacturing process in a traditional furniture environment, with the inherent advantage that workers can perform this task in a more guided and riskless manner. The Overall Equipment Effectiveness (OEE) approach was adopted to measure the benefits of the solution, which are described in article. View Full-Text
Keywords: furniture; factory connectivity; production optimization; vision system furniture; factory connectivity; production optimization; vision system
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MDPI and ACS Style

Bhullar, G.; Osborne, S.; Núñez Ariño, M.J.; Del Agua Navarro, J.; Gigante Valencia, F. Vision System Experimentation in Furniture Industrial Environment. Future Internet 2021, 13, 189. https://doi.org/10.3390/fi13080189

AMA Style

Bhullar G, Osborne S, Núñez Ariño MJ, Del Agua Navarro J, Gigante Valencia F. Vision System Experimentation in Furniture Industrial Environment. Future Internet. 2021; 13(8):189. https://doi.org/10.3390/fi13080189

Chicago/Turabian Style

Bhullar, Gurbaksh, Simon Osborne, María J. Núñez Ariño, Juan Del Agua Navarro, and Fernando Gigante Valencia. 2021. "Vision System Experimentation in Furniture Industrial Environment" Future Internet 13, no. 8: 189. https://doi.org/10.3390/fi13080189

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