As the intelligent machine and manufacturing system plays an important role in the near future, the monitoring system in turning process is required to improve the productivity during the cutting process. Hence, the aim of this research is to propose and develop the in-process monitoring system of the tool wear and the cutting states of chip and chatter for the carbon steel in CNC turning process by utilizing the sensor fusion which are the force sensor, the sound sensor, the accelerometer sensor and the acoustic emission sensor. Their signals have been integrated via the neural network with the back propagation and the pattern recognition technique to monitor the tool wear and detect the cutting states which are the continuous chip, the broken chip and the chatter occurred. The experimentally obtained results showed that the in-process monitoring system proposed and developed in this research can be effectively used to estimate the tool wear level and identify the chip breaking and the chatter with the higher accuracy and reliability.
For economical and environmental reasons, the aim of this research is hence to monitor the cutting conditions with the dry cutting, the wet cutting, and the mist cutting to obtain the proper cutting condition for the plain carbon steel with the ball end milling based on the consideration of the surface roughness of the machined parts, the life of the cutting tools, the use of the cutting fluids, the density of the particles of cutting fluids dispersed in the working area, and the cost of cutting. The experimentally obtained results of the relation between tool wear and surface roughness, the relation between tool wear and cutting force, and the relation between cutting force and surface roughness are correspondent with the same trend. The phenomena of surface roughness and tool wear can be explained by the in-process cutting forces. The models of the tool wear with the cutting conditions and the cutting times are proposed to estimate the tool cost for the different cooling strategies based on the experimental data using the multiple regression technique. The cutting cost is calculated from the costs of cutting tool and cutting fluid. The mist cutting gives the lowest cutting cost as compared to others. The experimentally obtained proper cutting condition is determined based on the experimental results referring to the criteria.
In order to realize the environmental hazard, this paper presents the investigation of the machinability of ball-end milling process with the dry cutting, the wet cutting, and the mist cutting for aluminum. The relations of the surface roughness, the cutting force, and the cutting parameters are examined based on the experimental results by using the Response Surface Analysis with the Box-Behnken design. The in-process cutting force is monitored to analyze the relations of the surface roughness and the cutting parameters. The proper cutting condition can be determined easily referring to the minimum use of cutting fluid, and the minimum surface roughness and cutting force of the surface plot. The effectiveness of the obtained surface roughness and cutting force models have been proved by utilizing the analysis of variance at 95% confident level.
The aim of this research is to propose and develop the in-process monitoring system of the tool wear for the carbon steel (S45C) in CNC turning process by utilizing the multi-sensor which are the force sensor, the sound sensor, the accelerometer sensor and the acoustic emission sensor. The progress of the tool wear results in the larger cutting force, the higher amplitude of the acceleration signal, and the higher power spectrum densities of sound and acoustic emission signals. Hence, their signals have been integrated via the neural network with the back propagation technique to monitor the tool wear. The experimentally obtained results showed that the in-process monitoring system proposed and developed in this research can be effectively used to estimate the tool wear level with the higher accuracy and reliability.
In order to reduce the use of cutting fluid and the environmental hazard, this paper presents the investigation of the machinability of ball-end milling process with the dry cutting and the mist cutting for carbon steel on 5-axis CNC machining center. The relations of the surface roughness, the flank wear, and the cutting parameters, which are the spindle speed, the feed rate, and the depth of cut, are examined and analyzed based on the experimental results by using the Response Surface Analysis with the Box-Behnken design and the analysis of variance. The in-process cutting force is also monitored to analyze the relations of the surface roughness, the flank wear, and the cutting parameters. The dynamometer is installed on the table of 5-axis CNC machining center to measure the in-process cutting forces. The proper cutting condition for the dry cutting and the mist cutting can be determined easily referring to the minimum surface roughness of the surface plot, which is calculated by the surface roughness model obtained from the Response Surface Analysis. The effectiveness of the obtained surface roughness model has been proved by utilizing the analysis of variance at 95% confident level.
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