1547 had studied extensively. Indian coal is predominantly drift origin and thus pose different characteristics than insitu coal (mostly available in other countries). The strength parameters are often higher in Indian coal. Therefore, a suitable cuttability index must be developed to predict the performance of the machines. In this paper, the existing performance predictive models for shearer/roadheader are reviewed and a new cuttability index for continuous miner is presented. A model is also proposed to predict the output from continuous miners using the developed cuttability index. 2. LITERATURE REVIEW Any rock cutting machine basically performed based on the rock properties, machine design and application parameters. Rock cutting machines are broadly classified into two groups – (i) cutting with point attack tool and (ii) cutting with disc cutter (Sen et al, 2000). In general, most of the cutting machines like shearer, continuous miner, road header, surface miner works with point attack cutting tool. However, Tunnel Boring Machine and some other large diameter boring machines work with disc cutting system. Point attack tools (picks) are basically mounted on a spindle or circular shaped cutting drum. On rotation of the drum, the picks hammered the rock along with a drag force provided by the movement of the boom carrying the drum. The cutting action of the point attack tool is depicted in Figure 1 (Dey and Ghose, 2008). Figure 1 – Cutting mechanics of point attack tool cutting system (Dey 2018) In general, it is found that the rake angle, wedge angle and clearance angle has important role in rock cutting. Rake angle is more or less kept between 20 to 25 degree. Wedge angle and clearance angle values are fixed depending on the strength and formation of the rock medium (Dey and Ghose, 2009). However, a cutting system can be selected considering – (i) rockmass properties, (ii) final product characteristics and (iii) application type (Dey, 1999). Therefore, any design consideration must possess two basic elements – the machine and the rockmass (Dey and Ghose, 2008). Rockmass is naturally formed and cannot be imitated, but a machine can be designed to suit the requirement (Eskikaya and Tuncdemir, 2007). “The understanding of the cutter-rock interaction is termed as “Cuttability” and “Cuttability” can be defined as the easiness to cut for a particular cutter-rock interaction” (Dey and Ghose, 2011). Thus, “Cuttability” of is influenced by (i) rock/rock mass parameters, (ii) machine parameters and (iii) the type of application, as given in Table 1. Table 1 – Parameters influencing cuttability (Dey and Ghosh, 2010) Geo-technical properties Machine properties Type of Application density, brittleness, unconfined compressive strength, point load index, Young’s modulus, specific fracture energy, toughness index, tensile strength, sonic velocity, abrasivity volumetric joint count, stickiness of material Cutting tool configuration - rake angle, attack angle, clearance angle and tip angle, pick lacing, type of pick number of picks, tip material, machine weight, engine power, nature of coolant for tips Direction of cutting, length, height and width of operating area, operator skill, specific requirements dry/wet, fragmentation desired and output A number of rockmass classification approach to define cuttabaility of different excavation systems are available. Some of the notable cuttability indices are - Discontinue Strength Classification (Franklin et al., 1971). This was followed by Excavation Index (Kirsten, 1982), Geological Factors Rating Scale (Minty and Kearns, 1983), Engineering Classification of Coal Measures (Scoble and Moftuoglu, 1984), Excavatability Index Rating Scheme (Hadjigeorgiou and Scoble, 1990), Diggability Index (Karpuz, 1990), Revised Excavatability Graph (Pettifer and Fookes, 1994), Cuttability index (Dey and Ghose, 2008) and many more. A new cuttability index is developed based on the case studies by the authors and compared the performance with existing models of Bilgin et.al. (1988), Gehring (1989) and Copur et, al. (1997). The details of these models are given in the Table 2
RkJQdWJsaXNoZXIy MTM0Mzk2