Statistical testing of availability for mining technological systems with air quality constraints. (22nd May 2018)

• Record Type: Journal Article
• Authors: Stehlík, Milan; Economou, Polychronis; Papić, Ljubiša; Aronov, Joseph; Nicolis, Orietta; Antoch, Jaromír; Cézová, Eliška; Kiseľák, Jozef
• Other Names: Nicolis Orietta guestEditor.; Pascual Rodrigo guestEditor.
• Is Part Of: Applied stochastic models in business and industry. Volume 34:Number 3(2018)
• Page Start: 278
• Page End: 292
• Publication Date: 2018-05-22
• Subjects: air pollution -- availability -- gamma distribution -- mine -- productivity -- sustainability -- technological system; Stochastic analysis -- Periodicals; Stochastic processes -- Periodicals; Business mathematics -- Periodicals; Finance -- Mathematical models -- Periodicals; Industrial management -- Mathematical models -- Periodicals; 338.00151923
• DOI: 10.1002/asmb.2337
• Languages: English
• ISSNs: 1524-1904

Abstract

Abstract: We develop a mining technology statistical model showing that even environmentally sustainable mining can be still very profitable. We put constraints on mining activities for elevated levels of particulate matters (eg, PM2.5 and PM10) in the air. We show that upper quantiles (eg, 95%) of productivity slightly decrease with respect to maximal number of failures, and this high‐productivity feature is robust with respect to variation of underlying statistical parameters. We illustrate the model on two currently active mining sites, the Chuquicamata copper mine in Chile and the opencast coal mine Libouš in the Czech Republic. Two generic working scenarios have been obtained. We show that, under very realistic conditions for both countries, the Czech Republic and Chilean mining companies can regulate mining activities for high thresholds of air pollutants without a substantial loss of productivity. Sensitivity analysis with respect to parameters is provided.