1546 PREDICTING THE PERFORMANCE OF CONTINUOUS MINER THROUGH A NEW CUTTABILITY INDEX * Kaushik Dey 1, A. K. Patra1, C.U. Kumar1 1Department of Mining Engineering, Indian Institute of Technology Kharagpur, India, (*Presenting author: kausdeyiit@gmail.com) ABSTRACT Coal is a prime fuel rock used for electricity generation in most of the third world countries. However, depletion of near surface deposits is compelling the mining authorities to extract coal from the deep-seated deposits. To achieve the in underground coal mines. Indian coals relatively constitute of low Sulphur and high ash. Often it exhibits some higher strength properties over other coal sources. Therefore, the applicability and economics of deployment of road header remain uncertain. Currently no appropriate models are available for the performance prediction of continuous miner (CM) in Indian coal. The popular cuttability indices are commonly established for predicting the performance of road headers. On the deployment of continuous miner, coal mining authorities started to adopt the same for the CM. But, road headers are designed and applied to hard rock excavation and thus not truly represent continuous miner. This paper presents some of the cuttability indices developed for road headers. The different properties influencing the performance of a cutting machine is also listed. The influencing properties can be classified as – (1) geotechnical properties, (2) machine properties and (3) mining parameters. Data, comprising these properties, are collected from field and laboratory tests. Unfortunately, the CMs monitored are of similar model and thus, the machine properties are excluded. Mining parameters are also kept similar due to the panel dimensions are similar for all the cases. Therefore, only the rock properties are considered in this analysis. A cuttability index, Continuous Miner Cuttability Index (CMCI) is modelled through conditional multivariate analysis. CMCI is correlated with the production from CM and a model is developed to predict the production. CMCI may be used across the variation of the CM. The production prediction model is only valid for the experimented machine. The similar regression analysis may be carried out for other machines to establish the coefficients for prediction purpose. KEYWORDS Underground Coal, Continuous miner, cuttability index, performance prediction, rockmass classification 1. INTRODUCTION India is the second largest coal producer in the world. India has produced 1047.5 million tonne of coal in the year 2024-25 [http://Coal.gov.in]. Majority of the coal (97%, 1015.7 million tonne) is being produced from the surface mines, whereas only 3% is produced from underground mines. However, despite this huge production India also imports 244 million tonne of coal from Indonesia, Australia, South Africa Russia, USA and other countries [http://Coal.gov.in]. As India shares only 2.4% land cover with 20% population in the world, availability of surface area for mining is limited. Thus, surface mining of coal deposits is difficult for the deep-seated deposits due to requirement of large surface area. Therefore, the deepseated deposits are being mined by underground mining method. With the depletion of near-surface deposits, the production from the underground mining needs to be increased to meet the demand. Considering this mechanized excavation systems, namely shearer and continuous miner, has been deployed in the underground coal mines. Longwall shearer was first introduced in 1978 at Moonidih Colliery and Continuous miner was deployed in Anjun Hill Mine of Chirimiri Area in 2002. The continuous miner and shearer had their successful deployment in China and European coal and
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