Research and application of green evaluation method for shearer based on life cycle

In view of the large demand for shearers, the large energy consumption and environmental pollution in theprocessing and manufacturing process, a green evaluation method for shearers based on life cycle evaluation is proposed. Combined with eFootprint software analysis, the process is quantitatively evaluated.First, taking the shearer rocker drive system as the research object, by using the multi-objective analysis theory to conduct robustness optimization design analysis,and determine the weight as an important influencing factor in green evaluation. Second, taking“cradle to gate”as the system boundary to establish a shearer weight information bill of material, and modelthe shearer in the efootprint software, and analyze the list according to the classification of castings, forgings, welding parts. The energy consumption and environmental pollution of each production link of shearer are analyzed quantitatively. Finally, taking the three parts of the shearer’s rocker arm, traction unit and cutting motor as the target and compare the cumulative contribution of each component to different impact indicators in the calculation results.The results show that the rocker arm shell has the largest contribution rate of energy consumption and global warming during the rocker arm process, reaching 49.50% and 52.91%，respectively; during the traction, the shell has the largest contribution rate to energy consumption and global warming, reaching 64.55% and 63.95%, respectively; during motor cutting, the largest contribution rate to energy consumption and global warming is the impact sheet-silicon steel sheet, reaching 58.05% and 63.27%,respectively. This method can solve the problem of green evaluation modeling of complex mechanical products, identify the components that consume the most energy and contribute the most to the environment, and provide companies with green improvement directions and references for the coal mine machinery industry green evaluation.