Proceedings of the International Seminar on Mineral Processing Technology - 2006, Chennai, India. pp. 499 - 504. Modeling Study of Beach Placer Minerals using Artificial Neural Network: A Case Study Pallavika, V.K. Kalyani l and V.J. Loveson Central Mining Research Institute, Dhanbad — 826 001 1 Corresponding Author's Email: vkkalyani@yahoo.com Abstract In recent years, artificial neural network (ANNs) have been found to be an attractive tool for steady-state/dynamic process modeling, and model based control in situations where the development of phenomenological or the empirical models just given either becomes impractical or cumbersome. ANN technology is well suited to solve problems in the mineral industry, and is expected to have a significant impact in many technological areas. Beneficiation plants for beach sand minerals are often very complex in nature with a number of alternative flow sheets are possible for the same mineral sand deposits. Computer simulation is a very useful tool to study the different flowsheets and the combination of the flowsheet parameters. Such simulation study can be useful to predict the performance of the beneficiation plant when it is still on the drawing board. At the stage of experimentation, simulation can greatly help in substantially reducing the number of experiments necessary to arrive at the optimum flowsheet. In the present paper, a three layer feed forward artificial neural network (ANN) model, trained using the error back propagation algorithm, has been established to simulate the beneficiation of beach placer minerals. The network model validates the experimentally observed trends. The optimal model parameters in terms of network weights have been estimated and can be used for computing parameters of the process over wide-ranging experimental conditions. INTRODUCTION In recent years, artificial neural network (ANN) has been used widely for steady-state/dynamic process modeling, and model based control in situations where the development of phenomenological or the empirical models developed, either becomes impractical or cumbersome (Hernandez et. al 1992, Narendra et. al 1990). The ANN technology is well suited to solve problems in the mineral industry, and is expected to have a significant impact in many technological areas (Hunt et.al 1992, Tendulkar et. al 1998). Beach sand is one of the major sources of heavy minerals like Ilmenite, Rutile, Zircon, Monazite, Sillimanite (Prabhaker et.al 2004), Garnet, Leucoxene and other amphibole and pyroxene group of silicate minerals. After the discovery of the Monazite in Quilon beach sands by Schorrberg, a German scientist, the beach placer industry started flourishing in India. Conventionally, beach placer beneficiation process consists of choosing and sizing appropriate process equipment, as well as fixing the nominal operating procedures (Kalyani et.al , 2005). Availability of a process model assumes considerable importance in the process design activity. For a given process, a "first principle (phenomenological)" model can be constructed from the knowledge of mass, momentum, energy balances etc, as well as from other mineral processing principles. Owing to the lack of a good understanding of the underlying phenomena, development of 499