Cutting temperature measurement and material machinability

Cutting temperature is very important parameter of cutting process. Around 90% of heat generated during cutting process is then away by sawdust, and the rest is transferred to the tool and workpiece. In this research cutting temperature was measured with artificial thermocouples and question of investigation of metal machinability from aspect of cutting temperature was analyzed. For investigation of material machinability during turning artificial thermocouple was placed just below the cutting top of insert, and for drilling thermocouples were placed through screw holes on the face surface. In this way was obtained simple, reliable, economic and accurate method for investigation of cutting machinability

Quality Parameters of Explosively Welded Spring Steel and Carbon Steel

Explosive plating, or welding, is a process where part of the kinetic energy of the detonation of a certain amount of civil explosive material is used to accelerate the plate, which will form a welded joint upon an oblique impact on a stationary plate. The conditions that must be met to achieve a good weld are determined by welding criteria. Today, the most commonly used welding criteria are based on the speed of the collision point and the collision angle. In this paper a research is presented on explosion welding of two different steels and on quality of the obtained welded joint. Carbon steel and spring steel were welded using Amonex 4 explosive in different quantities. Basic characterization of the explosive was carried out: bulk density and detonation velocity were determined. Quality of the welded joint was inspected using the ultrasonic method. Possible intermetallic zones at the joint site created by the effect of increased temperature were examined by optical and scanning electron microscopy. Fracture toughness of the welded plates was determined, as well as hardness. The achieved experimental results were compared to theoretical predictions

Monitoring and neural network modeling of cutting temperature during turning hard steel

In this study, cutting tools average temperature was investigated by using thermal imaging camera of FLIR E50-type. The cubic boron nitride inserts with zero and negative rake angles were taken as cutting tools and round bar of EN 90MnCrV8 hardened steel was used as the workpiece. Since the life of the cutting tool material strongly depends upon cutting temperature, it is important to predict heat generation in the tool with intelligent techniques. This paper proposes a method for the identification of cutting parameters using neural network. The model for determining the cutting temperature of hard steel, was trained and tested by using the experimental data. The test results showed that the proposed neural network model can be used successfully for machinability data selection. The effect on the cutting temperature of machining parameters and their interactions in machining were analyzed in detail and presented in this study