Cutting Optimization Research Of Hot Cell Disc Sawing Machine Based On Cutting State

With the trend of work pieces appears to be size miniaturization, complexity of structure, manufacturing precision and style diversification, the requirements of cutting process are increasingly enhanced. Meanwhile, the selection of cutting parameters is closely related to the cutting effects and economic benefits. In this paper, the optimization problems in the process of cutting are studied based on the hot cell disc sawing machine and its control system developed by one research institute. Manual control was a common way applied in the original control system. But due to the complication of cutting process, the parameters of cutting process in practical production were generally selected by technical personnel with the experience and reference manuals, which leaded to the processing craft varying from person to person. As a result, the optimization of cutting process is hardly to be accomplished and the cutting effect consistency of work pieces is poor, which decrease the machining accuracy and increase the maintenance work of the hot cell disc sawing machine. Therefore, according to the different cutting condition, the cutting parameters of the needs to be automatically adjusted, so as to reduce manpower and improve the cutting effect and consistency.Beginning with the cutting craft and process flow, the mechanism of cutting process is analyzed. And then the parameters and influencing factors that reveal the cutting state of hot cell disc sawing machine are confirmed. On the basis of the above work, an overall optimization solution of cutting process, consisting of production running layer, data processing layer and computing control layer, is designed.In the implementation process of cutting optimization solution, according to the cutting mechanism of hot cell disc sawing machine, the mechanism method and finite element method are adopted to analyze the cutting process. Then, the analysis results of this two methods are both verified, laying the foundation for the identification of cutting state and the verification of optimization effect. For the work conditions of the hot cell disc sawing machine are very severe, the temperature sensors and acoustic sensors are not used in the control system. Hence, Gaussian process classification method is adopted to classify and identify the cutting state of hot cell disc sawing machine, selecting the torque of servomotor, cutting depth and cutting speed in cutting process as auxiliary variables. Considering the experience and principles of adjusting cutting parameters in the original hot cell disc sawing machine, experts control method is adopted to simulate human thinking process. And according to the real-time cutting state, forward reasoning strategy is used to infer the cutting parameters suitable for the current cutting condition in order to achieve the purpose of improving the cutting process. Finally, based on the established finite element simulation model, pre-processing and post-processing of the ABAQUS model are conducted with MATLAB. The simulated effects of cutting parameters for cutting process before and after optimization are also compared. The simulation results show that the optimized cutting parameters can improve the deformation of work piece, the distribution of temperature field and cutting force, which can preferably adapt the change of cutting condition and achieve better cutting effect.