Optimization of a Laboratory-Scale Froth Flotation Process Using Response Surface Methodology

This article was downloaded by: [Tata Steel] On: 05 January 2014, At: 22:34 Publisher: Taylor & Francis Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK Coal Preparation Publication details, including instructions for authors and subscription information: Optimization of a Laboratory- Scale Froth Flotation Process Using Response Surface Methodology V. K. Kalya
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  This article was downloaded by: [Tata Steel]On: 05 January 2014, At: 22:34Publisher: Taylor & FrancisInforma Ltd Registered in England and Wales Registered Number: 1072954Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH,UK Coal Preparation Publication details, including instructions forauthors and subscription information: Optimization of a Laboratory-Scale Froth Flotation ProcessUsing Response SurfaceMethodology V. K. Kalyani a  , Pallavika a  , T. Gouri Charan b  &Sanjay Chaudhuri ba  IT Centre , Central Mining Research Institute ,Dhanbad, India b  Central Fuel Research Institute , P.O. FRI,Dhanbad, IndiaPublished online: 25 Feb 2010. To cite this article:  V. K. Kalyani , Pallavika , T. Gouri Charan & SanjayChaudhuri (2005) Optimization of a Laboratory-Scale Froth Flotation ProcessUsing Response Surface Methodology, Coal Preparation, 25:3, 141-153, DOI:10.1080/07349340590962793 To link to this article: PLEASE SCROLL DOWN FOR ARTICLETaylor & Francis makes every effort to ensure the accuracy of all theinformation (the “Content”) contained in the publications on our platform.However, Taylor & Francis, our agents, and our licensors make norepresentations or warranties whatsoever as to the accuracy, completeness,or suitability for any purpose of the Content. Any opinions and viewsexpressed in this publication are the opinions and views of the authors, andare not the views of or endorsed by Taylor & Francis. The accuracy of theContent should not be relied upon and should be independently verified withprimary sources of information. Taylor and Francis shall not be liable for anylosses, actions, claims, proceedings, demands, costs, expenses, damages,  and other liabilities whatsoever or howsoever caused arising directly orindirectly in connection with, in relation to or arising out of the use of theContent.This article may be used for research, teaching, and private study purposes.Any substantial or systematic reproduction, redistribution, reselling, loan,sub-licensing, systematic supply, or distribution in any form to anyone isexpressly forbidden. Terms & Conditions of access and use can be found at    D  o  w  n   l  o  a   d  e   d   b  y   [   T  a   t  a   S   t  e  e   l   ]  a   t   2   2  :   3   4   0   5   J  a  n  u  a  r  y   2   0   1   4  OPTIMIZATION OF A LABORATORY-SCALEFROTH FLOTATION PROCESS USINGRESPONSE SURFACE METHODOLOGY V. K. KALYANIPALLAVIKA IT Centre, Central Mining Research Institute,Dhanbad, India T. GOURI CHARANSANJAY CHAUDHURI Central Fuel Research Institute, P.O. FRI, Dhanbad, India Froth flotation is a universally accepted process for the beneficiationofcoalfines.However,the processvariables,collectordosage,frother dosage, and pulp density need to be optimized for each coal. In thepresent work, response surface methodology has been appliedfor optimization of yield at a desired ash level. Using this technique,interaction, contours, and three-dimensional diagrams have beendevelopedtoobservethebehavioroftheindependentvariablesaswellas interaction of the variables. A three-dimensional diagram has alsobeen developed to visualize the behavior of the desirability function.In this paper, attempts have been made to evaluate the performanceof the froth flotation process using response surface methodology. Keywords :  Optimization; Froth flotation; Coal fines; Responsesurface methodology Received October 13, 2004; accepted February 23, 2005.The authors express sincere thanks to Mark S. Klima,  Coal Preparation  RegionalEditor, for advicewithoutwhichthe paper could not havebeenaccepted in  Coal Preparation .Address correspondence to V. K. Kalyani, Scientist & Head, IT Centre, CentralMining Research Institute, Barwa Road, Dhanbad - 826001, India. E-mail: Coal Preparation  , 25: 141–153, 2005Copyright  Q Taylor & Francis Inc.ISSN: 0734-9343 printDOI: 10.1080/07349340590962793    D  o  w  n   l  o  a   d  e   d   b  y   [   T  a   t  a   S   t  e  e   l   ]  a   t   2   2  :   3   4   0   5   J  a  n  u  a  r  y   2   0   1   4  INTRODUCTION Indian coking coals, in general, are poor in quality with high ash content.They need beneficiation prior to utilization in steel industries. The frothflotation process [1] is a universally accepted physicochemical processfor the beneficiation of coal fines. In the froth flotation process, theselective separation of solids is based on the degree of surface hydropho-bicity. The surface characteristics of different types of particles dependon the pH, allowing cationic or anionic surfactants to be selectivelyabsorbed. This will render one particle type hydrophobic, while the other stays hydrophilic. In the beneficiation of coal fines by froth flotation, thecoal fines are generally hydrophobic in nature and the minerals arehydrophilic. The coal fines [2] are conditioned with a low dose of conditioning oil and fed to the flotation cell. Hydrophobic particles,usually the valuable components, attach to small air bubbles added intoa mixture of fine solids and water, which float to the surface and are col-lected as flotation concentrate, while the hydrophilic particles remain inthe bottom of the flotation cell and are collected as tailings. The study of a process or system often focuses on the relationship between theresponse and the input factors. If the input factors are quantitativeand are few in number, then response surface methodology is an effectivetool for studying the relationships between them.Response surface methodology (RSM) is a collection of statisticaland mathematical techniques useful for developing, improving, andoptimizing different processes. It also has important applications inthe design, development, and formulation of new products, as well asin the improvement of existing product design. In most RSM problems,the form of the relationship between dependent and the set of inde-pendent variables is unknown. Thus, the first step in RSM is to find a suitable approximation for a functional relationship between dependentand independent variables. Usually, a low order polynomial in someregion of the independent variables is employed. If there is a curvaturein the system, then a polynomial of higher degree is used. Second-order models are widely used in response surface methodology as they haveseveral advantages. They are very flexible and can take on a wide varietyof functional forms so they will work well as an approximation to the trueresponse surface. Moreover, it is easy to estimate the parameters in a second-order model using the method of least squares. Centralcomposite designs are used extensively in building a second-order  142 V. K. KALYANI ET AL.    D  o  w  n   l  o  a   d  e   d   b  y   [   T  a   t  a   S   t  e  e   l   ]  a   t   2   2  :   3   4   0   5   J  a  n  u  a  r  y   2   0   1   4


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