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Open AccessProceedings

An Economical and Environmental Alternative to Traditional Can Manufacturing Using a New Pre-Laminated Steel

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Department of Mechanical and Materials Engineering, Universitat Politècnica de València, 03801 Alcoy, Spain
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Department of Mechanical Engineering and Engineering Science, University of North Carolina, Charlotte, NC 28223, USA
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Department of Mechanical Engineering, Auckland University of Technology, WZ 334C Auckland, New Zealand
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Department of Statistics and Operations Research, Universitat Politècnica de València, 03801 Alcoy, Spain
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Author to whom correspondence should be addressed.
Presented at the 2nd Coatings and Interfaces Web Conference, 15–30 May 2020; Available online: https://ciwc2020.sciforum.net/.
Mater. Proc. 2020, 2(1), 21; https://doi.org/10.3390/CIWC2020-06841
Published: 2 August 2020
(This article belongs to the Proceedings of 2nd Coatings and Interfaces Web Conference (CIWC-2 2020))
Metal containers are the most commonly used packaging worldwide in both the food processing industry. Usually, the production processes involved in the canning industry include multi-step transformations that take large aluminum or steel coils and make them into two or three-piece cans. During this process, these parts are sprayed to obtain a better surface for the contents; however, this spray produces volatile organic compounds (VOC). This paper presents a new and environmentally friendly can manufacturing method, which uses a novel pre-laminated two-layer polymer steel. As experimentally proven, this innovative polymer-coated steel successfully withstands every manufacturing requirement. The specimens were tested in an ironing simulator, measuring roughness, and friction coefficients. The development of an upper bound ironing model, along with a supporting neural network, allows an insight into the design of new materials for can manufacturing.
Keywords: coating; ironing; VOC; upper bound; polymer; coating; can; neural network; ANN coating; ironing; VOC; upper bound; polymer; coating; can; neural network; ANN
MDPI and ACS Style

Selles, M.A.; Schmid, S.R.; Sanchez-Caballero, S.; Ramezani, M.; Perez-Bernabeu, E. An Economical and Environmental Alternative to Traditional Can Manufacturing Using a New Pre-Laminated Steel. Mater. Proc. 2020, 2, 21.

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