Real-time tool monitoring and machinability models for drilling steels



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Texas Tech University


In-process tool failure poses a serious threat to unmanned manufacturing systems, such as flexible machining centers. Developing effective means to monitor and manage tool usage and replacement, in order to avoid off-quality product and/or system damage, presents a significant problem for manufacturing research. This research effort addresses this problem relative to drilling processes involving steel. The research consisted of a laboratory experiment involving four independent variables; cutting speed ranging from 32 to 65 sfpm, feed ranging from 0.0025 to 0.015 ipr, drill diameter ranging from 0.2969 to 0.5781 in., and steel hardness ranging from 146 to 330 BHN; and four dependent variables; tool life, torque and thrust on the drill, and surface roughness of the holes drilled. The experiment was designed as a central composite design with 30 treatment combinations. Tool life varied from 3.98 to 265.5 mins. The data were fit for four primary models; tool life, torque, thrust, and surface roughness. Model fits ranged from an R-square of about 0.70 to about 0.92 for these models. The study was based upon about 10,000 holes drilled which resulted in about 300 feet of low carbon steel drilling. The steel was received at about 146 BHN and was heat-treated at different combinations of time and temperature to attain four other levels of hardnesses, 180, 220, 270, and 330 BHN. The tool performance models were used to develop a thrust-based real time, tool-monitoring algorithm. The algorithm was demonstrated using a portion of the data that was collected during the experiment.



Drill presses -- Maintenance and repair, Machine-tools -- Maintenance and repair