Sivasrinivasu Devadula

Kerf profile generated by abrasive waterjet (AWJ) machining process has always been an interesting area as it dictates the quality of the part. However, due to the non-deterministic nature of the process, it is a challenging task to predict it. On the other hand, understanding and controlling the kerf profile in multi-layered structures (MLSs) is a further difficult task as various layers made of different materials respond to erosion in a different manner and results in a completely different kerf shape (barrel or x-shaped kerf profile) due to the material removal mechanisms dependency on the material property of the specific layers, jet divergence and position of specific layer. Therefore, it is important to understand and develop predictive models of resulting kerf profile in MLSs so that they can be used in controlling the accuracy of the resulting kerf which in turn dictates the final part accuracy. The attempts in this direction are very limited although some modeling efforts are reported in homogeneous materials (metals, ceramics). For the first time, an analytical model for predicting the kerf profile generated in MLS machining with AWJ was presented in this research work. Discretized form of Hashish model was used for determining depth of cut. The effect of jet divergence from the experimentally obtained values, upon passing through the upper layer has been considered. The developed predictive model was validated by the kerf shapes obtained from the experimental trials on metal-adhesive-rubber MLS. Kerf profiles obtained from the simulations have captured the resulted convergent-divergent (X-shaped) profile, while cutting metal-rubber laminate composite, effectively. Furthermore, the effectiveness of the proposed analytical model was demonstrated by generating the various kerf shapes generated at various jet traverse rates.

The CMS experiment will change it’s silicon tracker completely during phase-II upgrade. There is need to develop light and high precision and durable mechanical structure for silicon modules. The prime purpose of this should also be reducing material in the silicon tracker detector. The group at IIT Madras is involved in R&D of production of this structures. We have produced high precision bridge made of AL-CF material and carbon fiber stiffener.

The CMS experiment will change its silicon tracker completely during phase-II upgrade. There is need to develop light and high precision and durable mechanical structure for silicon modules. The prime purpose of this should also be reducing material in the silicon tracker detector. The group at IIT Madras is involved in R&D of production of this structures. The prime purpose of this should also be reducing material in the silicon tracker detector. We have produced high precision Al-CF bridges, stumps and Pipe connector 47 degrees for HgCAL detector.

Engineering parts usually deviate from their intended shapes during their manufacturing due to the inaccuracies of machine tools, deformation of various elements of machine tool, cutting tools and workpiece. Resulting geometric errors affect the functionality and assembly of the parts significantly. This demands a reliable strategy to accurately assess the errors during the final part quality inspection. Among all the geometric features, circular feature is very common on the majority of the engineering parts. Hence, the measurement and evaluation of circularity with a high degree of accuracy are of utmost importance. In the present work, a hybrid approach is proposed to accurately evaluate the circularity error. This approach comprises a least squares method (LSM) and a novel probabilistic global search Lausanne (PGSL) technique. The LSM is used to reduce the search space initially. Within the reduced search space, the PGSL performs efficient, fine and global search. In the process of establishing minimum zone circles to the measured data of the circular features, the proposed approach dynamically updates the probability distribution function of the circularity parameters continuously. The update procedure ensures that the probability of moving towards the potential optimal solutions is increased. The algorithm has been tested using several benchmark datasets for its generalization capability and robustness. The proposed strategy is found to be efficient in yielding accurate results. Therefore, the algorithm can be implemented in computer-aided circularity measuring instruments in order to minimize acceptance of bad parts and rejection of good parts.