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Artificial neural network based tool wear estimation on dry hard turning processes of AISI4140 steel using coated carbide tool

Rajeev D., Dinakaran D., Singh S. C. E.

Bulletin of the Polish Academy of Sciences. Technical Sciences

2017

Vol. 65, nr 4

553--559

Nowadays, finishing operation in hardened steel parts which have wide industrial applications is done by hard turning. Cubic boron nitride (CBN) inserts, which are expensive, are used for hard turning. The cheaper coated carbide tool is seen as a substitute for CBN inserts in the hardness range (45–55 HRC). However, tool wear in a coated carbide tool during hard turning is a significant factor that influences the tolerance of machined surface. An online tool wear estimation system is essential for maintaining the surface quality and minimizing the manufacturing cost. In this investigation, the cutting tool wear estimation using artificial neural network (ANN) is proposed. AISI4140 steel hardened to 47 HRC is used as a work piece and a coated carbide tool is the cutting tool. Experimentation is based on full factorial design (FFD) as per design of experiments. The variations in cutting forces and vibrations are measured during the experimentation. Based on the process parameters and measured parameters an ANN-based tool wear estimator is developed. The wear outputs from the ANN model are then tested. It was observed that as the model using ANN provided quite satisfactory results, and that it can be used for online tool wear estimation.

Influence of cooling on the performance of the drilling process of glass fibre reinforced epoxy composites

Ramesh B., Elayaperumal A., Satishkumar S., Kumar A., Jayakumar T., Dinakaran D.

Archives of Civil and Mechanical Engineering

2016

Vol. 16, no. 1

135--146

Non-laminated composites find application in construction of bridges, ballistic applications, etc. However, literature on the drilling of non-laminated composite materials and literature on the drilling of thick composite materials under different cooling methods (dry, external and internal) is scarce. Hence the present study is aimed to investigate the influence of different cooling methods on quality characteristics (drill temperature and damage factor) while drilling glass fibre reinforced epoxy (GFRE) non-laminated 20 mm thick pultruded composite rods having 80% fibre weight fraction and 0° fibre orientations with respect to the drill. The drilling experiments using TiN/TiAlN coated tungsten carbide twist drills of diameter 10 mm were conducted using response surface methodology (RSM). The experimental values obtained for quality characteristics are empirically related to process parameters by developing a response surface model using Design-Expert software. The effects of process parameters on quality characteristics were analysed by using response surface graphs. The process parameters (feed, spindle speed and coolant pressure) are also optimized within the selected range. The optimal parameter levels are confirmed by validation test. From this investigation, it is evident that the internal cooling method is significant for obtaining high hole quality.