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Abstract

Mining is an equipment-intensive industry that utilizes machinery both in production and mineral processing. As an essential part of sustainable development, mining is subject to environmental management from many aspects. The decision-making process integrated into all stages of mining has to be based on reliable data. Available technology enables to track and monitor the production stages in mining by using various sensors and systems. Data related to mining and mineral processing activities have different characteristics and therefore might be handled in different IT infrastructures. However, the integration of these different data infrastructures is of key importance for management. Mineral processing plant equipment is potentially a data source of process type of data, unique by its volume and frequency. Analyzing process type of data, such as sensors, is a challenging task for engineers that work in a dynamic work environment. Belt conveyors located in the mineral processing plants transport material between different stages such as crushing and grinding which are monitored by sensor systems. The data collected by these sensors is commonly visualized on SCADA screens and can provide real-time data about the operation. This study focuses on the available sensor data of belt conveyors in a mineral processing plant with an aim to manage the dust generated during material transportation. The belt conveyors and the water spraying systems are equipped with tags that provide data for daily management. A data integration tool was developed to create an alarm system to track whether the dust suppression systems were active during material was conveyed in the mineral processing plant. As a result, violations of dust suppression were identified, and the alarm system was integrated into the environmental management system of the operation.

Keywords

Data integration Dust suppression Plant data 

References

  1. Alphonsus, E.R., Abdullah, M.O.: A review on the applications of programmable logic controllers (PLCs). Renew. Sustain. Energy Rev. 60, 1185–1205 (2016)CrossRefGoogle Scholar
  2. Bascur, O., Soudek, A.: Real-time integration of mining and metallurgical information for efficient use of energy and water. In: XXV International Mineral Processing Congress (IMPC), pp. 3123–3131. Brisbane, Australia (2010)Google Scholar
  3. Chardin, B., Lacombe, J.-M., Petit, J.-M.: Data historians in the data management landscape. In: Technology Conference on Performance Evaluation and Benchmarking, pp. 124–139 (2012)CrossRefGoogle Scholar
  4. Kaplan, R.S., Norton, D.P.: Translating Strategy into Action—The Balanced Scorecard. Harvard Business School Press (1996)Google Scholar
  5. Papalexandris, A., Ioannou, G., Prastacos, G., Soderquist, K.E.: An integrated methodology for putting the balanced scorecard into action. Eur. Manag. J. 23(2), 214–227 (2005)CrossRefGoogle Scholar
  6. Smit, A.: Development of an integrated asset management system for a metallurgical plant. In: Value Tracking Symposium, pp. 157–165. Brisbane, Australia (2002)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Mining Engineering DepartmentMiddle East Technical UniversityAnkaraTurkey

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