講演情報
[2801-14-01]Development of Automatic Sorting System for Recycling Black Plastics from Used Small Household Appliances
○Eun Kyu Park1, Bam Bit Jung1, Tae Jun Choe1, Sung Kwun Oh1, Woo Zin Choi1 (1. Center for IT and Environmental Research, The University of Suwon)
司会（Chairman）：Kazutoshi Haga （Akita University）, Makoto Harita (Harita Metal Co lyd)
Small household appliances (small HH), such as vacuum cleaner, electric cooker, and air cleaner among others, are diverse and complex given their materials and components, as well as the waste streams from the manufacturing processes. The plastic concentration in used small HH is particularly high compared to that of large HH. A great variety of plastics is used in small HH, and such differ not only by plastic type but also by color and presence of additives.
Different separation technologies, such as optical sorting, gravity and electrostatic separation, and flotation, are widely used for recovering plastics from municipal wastes, e-scraps, and so on. Near-infrared ray (NIR) sensors are particularly used for separating plastics by resin type at high throughputs. However, one of the shortcomings of NIR sensors is its inability to detect black plastics.
This study developed an automatic sorting system based on a new sensing system to classify black plastics obtained from used small HH. To reduce data dimensions, spectrum data were preprocessed by adopting principal component analysis and by treating with a classifier, which was designed with artificial intelligence algorithm. Results of the lab-scale automatic sorting system for sorting black plastics by type are discussed.
Different separation technologies, such as optical sorting, gravity and electrostatic separation, and flotation, are widely used for recovering plastics from municipal wastes, e-scraps, and so on. Near-infrared ray (NIR) sensors are particularly used for separating plastics by resin type at high throughputs. However, one of the shortcomings of NIR sensors is its inability to detect black plastics.
This study developed an automatic sorting system based on a new sensing system to classify black plastics obtained from used small HH. To reduce data dimensions, spectrum data were preprocessed by adopting principal component analysis and by treating with a classifier, which was designed with artificial intelligence algorithm. Results of the lab-scale automatic sorting system for sorting black plastics by type are discussed.