Drilling is the most frequently employed operation of secondary machining for fiber-reinforced materials owing to the need for joining structures. Delamination is among the serious concerns during drilling. Practical experience proves the advantage of using such special drills as saw drill, candle stick drill, core drill and step drill. The experimental investigation described in this paper examines the theoretical predictions of critical thrust force at the onset of delamination, and compares the effects of these different drill bits. The results confirm the analytical findings and are consistent with the industrial experience. Ultrasonic scanning is used to evaluate the extent of drilling-induced delamination. The advantage of these special drills is illustrated mathematically as well as experimentally, that their thrust force is distributed toward the drill periphery instead of being concentrated at the center. The allowable feed rate without causing delamination is also increased. The analysis can be extended to examine the effects of other future innovative drill bits. 相似文献
The purpose of this work is to present the development and experimental performance assessment of a new generation of spade drill bits. Rigorous point geometry and drilling force models that describe the topology of the drill and its cutting behaviour have guided the development of these new drills with unique topological features. It is shown, both analytically through simulations and through a systematic experimental study, that the performance of the newly developed topologies exceeds that of the commercially available designs. The new spade bits yield lower thrust and torque over the whole range of pragmatic operating conditions. 相似文献
The useful life of a cutting tool and its operating conditions largely control the economics of the machining operations. Hence, it is imperative that the condition of the cutting tool, particularly some indication as to when it requires changing, to be monitored. The drilling operation is frequently used as a preliminary step for many operations like boring, reaming and tapping, however, the operation itself is complex and demanding.
Back propagation neural networks were used for detection of drill wear. The neural network consisted of three layers input, hidden and output. Drill size, feed, spindle speed, torque, machining time and thrust force are given as inputs to the ANN and the flank wear was estimated. Drilling experiments with 8 mm drill size were performed by changing the cutting speed and feed at two different levels. The number of neurons in the hidden layer were selected from 1, 2, 3, …, 20. The learning rate was selected as 0.01 and no smoothing factor was used. The estimated values of tool wear were obtained by statistical analysis and by various neural network structures. Comparative analysis has been done between statistical analysis, neural network structures and the actual values of tool wear obtained by experimentation. 相似文献