Manufacturing Technology Today

S. Samanta ¹, D. Datta ²

Affiliations
1 Mech Engg Dept, North Eastern Regional Institute of Science and Technology (Deemed University), Nirjuli-791109, Arunachal Pradesh, IN
2 Mech Engg Dept, Bengal Engg and Science University, Shibpur, Howrah-71103, West Bengal, IN

Abstract

Advanced composite structures have been used widely in many applications such as aerospace, sport equipments and automobile parts. These are very susceptible to transverse impact. These may cause significant damage in terms of matrix cracking and delamination. In the present research the stress history by impact on kevlar composite plates are obtained using general-purpose commercial FEM software Like ANSYS LS-DYNA. The stresses are then substituted in the appropriate failure criterion from which the damage is obtained as a result of impact. Necessary codes (in FORTRAN and MATLAB Environment) have been developed to read the ANSYS/LS-DYNA results to find and image the damaged zone.

Keywords

Impact, Delamination, FEM and Fibre Reinforced Plastics.

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A. Mandal ¹, S. Samanta ¹, K. Roy ¹, B. Roy ¹, K. Astitwa ¹

Affiliations
1 Dept. of Mechanical Engg., North Eastern Regional Institute of Science and Technology, Nirjuli, IN

Abstract

Pulsed Nd:YAG laser beam has great ability for micro-machining of ceramic materials because of high laser beam intensity at low mean beam power, good focusing characteristics due to very small pulse duration, small kerf widths and narrow heat affected zones. In the present research, micro-grooving of alumina ceramic plate by pulsed Nd:YAG laser beam machine is studied. Selection of optimum machining parameter combinations for obtaining accuracy is the challenging task in laser micro-grooving operation. Nowadays several numerical methods are widely used for either modeling or optimizing the performance of the manufacturing technologies. That has been advanced due to the large diffusion of the personal computer and the numerical algorithms. This paper represents an attempt to develop an appropriate machining strategy for obtaining most accurate dimension of the micro-groove and to prepare a database for assistance during laser micro-grooving operation. A feed-forward back-propagation neural network is developed to model machining process. The three most important process parameters-lower width, upper width and depth of the groove-have been considered as measures of process performance. The model is capable of predicting the response parameters as a function of five different control parameters i.e. lamp current, pulse frequency, pulse width of the duty cycle, assist air pressure and cutting speed.

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