Automatic inspection of paperboard creases to improve the quality of the packaging process
Authors: Igor Lajas Andoni Larrañaga Luis Amozarrain
Date: 01.03.2023
International Journal of Advanced Manufacturing Technology
Abstract
In the paper-based packaging field, a sheet of paper material is introduced in a die cutter to create several creases and cuts. These creases allow to fold the sheet, and consequently, to build the final package. Thus, the quality of the crease is critical to get a valuable final product. In this work, a new system for automatic crease inspection is presented. The inspection is performed by processing crease visual information captured by a laser sensor. Automation is achieved by moving the laser with a cartesian robot along the sheet. A crease profile processing algorithm is proposed as well, which is able to extract geometric features from the different patterns that are associated with different paper types. Moreover, a crease classification methodology is proposed, where creases are grouped taking into account some physical properties. The experiments performed show the viability and usefulness of the proposed system.
BIB_text
title = {Automatic inspection of paperboard creases to improve the quality of the packaging process},
journal = {International Journal of Advanced Manufacturing Technology},
pages = {2455-2466},
volume = {125},
keywds = {
Automated inspection; Metrology; Quality inspection
}
abstract = {
In the paper-based packaging field, a sheet of paper material is introduced in a die cutter to create several creases and cuts. These creases allow to fold the sheet, and consequently, to build the final package. Thus, the quality of the crease is critical to get a valuable final product. In this work, a new system for automatic crease inspection is presented. The inspection is performed by processing crease visual information captured by a laser sensor. Automation is achieved by moving the laser with a cartesian robot along the sheet. A crease profile processing algorithm is proposed as well, which is able to extract geometric features from the different patterns that are associated with different paper types. Moreover, a crease classification methodology is proposed, where creases are grouped taking into account some physical properties. The experiments performed show the viability and usefulness of the proposed system.
}
doi = {10.1007/s00170-022-10722-1},
date = {2023-03-01},
}
