Optimal sensor selection for sensor-based sorting based on automated mineralogy data. (10th October 2019)

• Record Type: Journal Article
• Authors: Kern, Marius; Tusa, Laura; Leißner, Thomas; van den Boogaart, Karl Gerald; Gutzmer, Jens
• Is Part Of: Journal of cleaner production. Volume 234(2019)
• Page Start: 1144
• Page End: 1152
• Publication Date: 2019-10-10
• Subjects: Sensor-based sorting -- Dual energy X-ray transmission -- Short-wave infrared spectroscopy -- Automated mineralogy -- Cassiterite -- Geometallurgy; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2019.06.259
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: Assessing the success of sensor-based sorting in the raw materials industry currently requires time-consuming and expensive empirical test work. In this contribution we illustrate the prospects of successful sensor selection based on data acquired by scanning electron microscopy-based image analysis. Quantitative mineralogical and textural data from more than 100 thin sections were taken to capture mineralogical and textural variability of two different ore types from the Hämmerlein Sn–In–Zn deposit, Germany. Parameters such as mineral grain sizes distribution, modal mineralogy, mineral area and mineral density distribution were used to simulate the prospects of sensor-based sorting using different sensors. The results illustrate that the abundance of rock-forming chlorite and/or density anomalies may well be used as proxies for the abundance of cassiterite, the main ore mineral. This suggests that sorting of the Hämmerlein ore may well be achieved by either using a short-wavelength infrared detector — to quantify the abundance of chlorite — or a dual-energy X-ray transmission detector to determine the abundance of cassiterite. Empirical tests conducted using commercially available short-wave infrared and dual-energy X-ray transmission sensor systems are in excellent agreement with simulation-based predictions and confirm the potential of the novel approach introduced here. Graphical abstract: Image 1 Highlights: Novel approach for the selection of sensors suitable for sensor-based sorting. Approach validated by empirical test work for Sn–Zn–In ores of the Hämmerlein deposit. Improvement of resource and energy efficiency in the raw materials industry. Avoids time-consuming and expensive test work. Important tool for realizing predictive geometallurgical models.