Statistical optimisation parameter for lean grade self-reducing nuggets by surface response modelling to produce pig iron. (3rd July 2017)

• Record Type: Journal Article
• Authors: Biswas, C.; Samanta, S.; Bhattacharyya, A.; Chaudhuri, M. G.; Dey, R.
• Is Part Of: Transactions. Volume 126:Number 3(2017)
• Page Start: 172
• Page End: 181
• Publication Date: 2017-07-03
• Subjects: Iron nuggets -- Solid state reduction -- Extent of reduction -- Box Behnken Design (BBD) -- Melting; Ore-dressing -- Periodicals; Metallurgy -- Periodicals; Mineral industries -- Periodicals; 622.7
• DOI: 10.1080/03719553.2016.1204083
• Languages: English
• ISSNs: 0371-9553

Abstract

Abstract : Iron ore fines, lean grade coal and coke dust fines have always challenged the metallurgists to develop a suitable process for its optimum use. The aim of this study is to utilise the inferior quality of iron ore fines, coal and plant waste coke dust for reduction. At first mechanical properties of iron ore nuggets are assessed through shatter and abrasion test and subsequent to which cold bonded self-reducing nuggets are directly reduced in standard reducing furnace. The maximum extent of reduction achieved in the present study is 87.2%. The reduced specimens are further characterised using XRD, SEM, EDX and chemical analysis method. Finally, the statistical model of Box Behnken Design (BBD) method is successfully utilised to optimise the process parameter for reduction experiments. The optimised sample thus obtained is subjected to melting for laboratory scale pig iron production. Better slag metal separation is achieved when calcined lime is used as a flux. The microstructure of the metallic iron is studied and it shows ferrite phase with dispersed carbon.