Abstract
Sensors and process control systems are essential for process automation and optimization. Many sectors have adapted to the Industry 4.0 paradigm, but copper smelters remain hesitant to implement these technologies without appropriate justification, as many critical functions remain subject to ground operator experience. Recent experiments and industrial trials using radiometric optoelectronic data acquisition, coupled with advanced quantitative methods and expert systems, have successfully distinguished between mineral species in reactive vessels with high classification rates. These experiments demonstrate the increasing potential for the online monitoring of the state of a charge in pyrometallurgical furnaces, allowing data-driven adjustments to critical operational parameters. However, the justification to implement an innovative control system requires a quantitative framework that is conducive to multiphase engineering projects. This paper presents a unified quantitative framework for copper and nickel-copper smelters, which integrates thermochemical modeling into discrete event simulation and is, indeed, able to simulate smelters, with and without a proposed set of sensors, thus quantifying the benefit of these sensors. Sample computations are presented, which are based on the authors’ experiences in smelter reengineering projects.
Highlights
Modern metallurgical installations such as steel plants and copper smelters require a range of plant sensors and process control systems to attain their highest efficiency
This, in part, helps understand that certainly more developments are attained in the iron and steel industry relative to copper
The computational framework described in this paper will help close the gap, regarding hyperspectral imaging (HI) and laser-induced breakdown spectroscopy (LIBS) and other radiometric sensors, as it enables the implementation of these technologies and justifies their further development within the copper industry
Summary
Alessandro Navarra 1, *, Ryan Wilson 1 , Roberto Parra 2 , Norman Toro 3,4 , Andrés Ross 5 , Jean-Christophe Nave 5 and Phillip J. Faculty of Engineering and Architecture, Universidad Arturo Prat, Almirante Juan José Latorre 2901, Antofagasta 1244260, Chile. Received: 9 October 2020; Accepted: 13 November 2020; Published: 17 November 2020
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