Design and Development of Flexible Screen for Processing Industries and its Performance Prediction using Machine Learning Techniques

Abstract

In the material processing industry, screening is one of the crucial physical separation methods to separate the undersized fine particles from the oversized coarse particles. The availability of low-grade coal and iron ore with high impurities has urged the improvisation of processing equipment such as screening machines with higher efficiency without utilising water. Previous studies showed that wet processing of coal and iron ore was carried out with enormous quantities of water and also required a water treatment circuit in the plant to treat the tailings. Dry processing has significant merits in preventing water consumption, eliminating waste, and tailing water treatment. The major problems of the existing dry processing linear vibratory screening machine are lower efficiency caused by the screen clogging, high velocity, reduced residence time, and inflexibility in changing the angular position and frequency of the screen. The efficiency of the existing linear vibrating screen available at the JSW (Jindal Steel Works) steel plant, as well as that available in the Department of Mining Engineering, NITK Surathkal (lab scale), was around 65.00%. So, a new screening machine was designed and developed to overcome all the limitations of the existing linear vibratory screening machine. The new screening machine was developed with a circular mode of vibration for dry screening of moist coal and iron ore of size fraction −4mm + 0 mm. A screen mesh of 2 mm aperture size was used to separate the fine coal and iron ore particles of size fraction −2 mm + 0 mm individually. The new screening machine has the flexibility to vary the operational parameters, such as the angle in an upward sloping direction and the vibration frequency of the screen, and it can work as a feeder. Experimental investigations were conducted at the JSW R&D laboratory to assess the efficiency of screening coal and iron ore of varying moisture content of 4%, 6%, and 8% in the new screening machine. Before the screening, the angle and frequency were set by adjusting the angle bolts and frequency drive, respectively. During the screening, the samples were fed to the screen at 8.33 kg/min and undersize particles were icollected. The collected samples were weighed, and the screening efficiency was calculated for coal and iron ore samples. The test results showed that the screening machine could provide higher efficiency for screening iron ore than coal material. Further, the screening efficiency of coal and iron ore was predicted using a machine learning (supervised learning) prediction model such as polynomial regression and backpropagation artificial neural network (ANN) models. The results showed that for all experimental conditions, compared to the second-order polynomial regression modelling, the ANN modeling was a better mathematical modeling technique suitable for predicting the screening machine’s performance. Further, the residual analysis of each prediction model was analysed and validated using a normal probability plot and histogram. Additionally, the developed screening machine’s operational parameters were optimised using the Taguchi L27 Design of Experiments technique to obtain a high response parameter, i.e., screening efficiency. For the optimisation study, the operational parameters considered were moisture content, angle, and frequency. The Taguchi L27 optimisation results yielded a higher screening efficiency of 84.40% for coal and 94.53% for iron ore. Furthermore, the Pareto chart and normal effect plot were developed using a fractional Design of Experiments (DOE) to evaluate the significant operational parameter for the screening machine. The results of the fractional Design of Experiments on coal and iron ore show the moisture content as the most significant operational parameter, followed by the angle and frequency. Additionally, the feeding performance of coal and iron ore was improved by transforming the screening machine into a feeding machine by replacing the screen mesh with a thin solid plate. The results showed that the developed machine could be utilised as a multifunctional machine for efficient screening with less clogging and also as an efficient feeder.