Indian Institute of Technology Bombay

About: Indian Institute of Technology Bombay is a education organization based out in Mumbai, India. It is known for research contribution in the topics: Catalysis & Computer science. The organization has 16756 authors who have published 33588 publications receiving 570559 citations.

Characterization and modeling of burr formation in micro-end milling

Abstract: Mechanical micromachining is increasingly finding applications in fabrication of components in various fields, such as, biomedical devices, optics, electronics, medicine, communications and avionics. In order to ensure adequate functionality, there are stringent requirements for form and finish in case of biomedical devices like cochlear implants and metallic optics. This necessitates that the post machined surface must be burr free. To address these issues in micromachining, this paper presents results of an experimental study to investigate the influence of main process parameters i.e. speed, feed rate, depth of cut, tool diameter and number of flutes on the formation of the various types of burrs i.e. exit burrs and top burrs produced during micro-end milling operation. The experiments performed using Taguchi method shows that three types of burr formation mechanisms prevail during micro-end milling operations; these are: lateral deformation of material, bending and tearing of the chip. Also, three types of burrs were observed include: Poisson burr, rollover burr in down milling and tear burr in up milling. Further, it is observed that the depth of cut and the tool diameter are the main parameters, which influence the burr height and thickness significantly. However, the speed and the feed rate have small to negligible effect on the burr thickness and height. Besides the experimental analysis, the paper presents an analytical model to predict the burr height for exit burr. The model is built on the geometry of burr formation and the principle of continuity of work at the transition from chip formation to burr formation. Note that prediction of burr height in micro-end milling is extremely challenging due to the complex geometry of material removal and microstructural effects encountered during cutting at that length scales. The model fares well and the prediction errors range between 0.65 and 25%.

Palladium complexes of abnormal N-heterocyclic carbenes as precatalysts for the much preferred Cu-free and amine-free Sonogashira coupling in air in a mixed-aqueous medium

Abstract: A series of new PEPPSI (Pyridine Enhanced Precatalyst Preparation Stabilization and Initiation) themed precatalysts of abnormal N-heterocyclic carbenes for the highly desirable Cu-free and amine-free Sonogashira coupling in air in a mixed-aqueous medium is reported. Specifically, the PEPPSI themed (NHC)PdI2(pyridine) type precatalysts, 1b–4b, efficiently carried out the highly convenient Cu-free and amine-free Sonogashira coupling of aryl bromides and iodides with terminal acetylenes in air in a mixed aqueous medium. Complexes, 1b–4b, were synthesized by the direct reaction of the corresponding imidazo[1,2-a]pyridinium iodide salts, 1a–4a, with PdCl2 in pyridine in the presence of K2CO3 as a base while the imidazo[1,2-a]pyridinium iodide salts, 1a–4a, were in turn synthesized by the alkylation reactions of the respective imidazo[1,2-a]pyridine derivatives with alkyl iodides. The density functional theory (DFT) studies revealed that these imidazol-3-ylidene[1,2-a]pyridine derived abnormal carbenes are strongly σ-donating and consequently significantly weaken the catalytically important labile trans pyridine ligand in 1b–4b.

Efficient formation of storage classes for warehouse storage location assignment: A simulated annealing approach

Abstract: Class-based storage policy distributes products among a number of classes and for each class it reserves a region within the storage area. The procedures reported in the literature for formation of storage classes primarily consider order-picking cost ignoring storage-space cost. Moreover, in these procedures items are ordered on the basis of their cube per order index (COI), and items are then partitioned into classes maintaining this ordering. This excludes many possible product combinations in forming classes which may result in inferior solutions. In this paper, a simulated annealing algorithm (SAA) is developed to solve an integer programming model for class formation and storage assignment that considers all possible product combinations, storage-space cost and order-picking cost. Computational experience on randomly generated data sets and an industrial case shows that SAA gives superior results than the benchmark dynamic programming algorithm for class formation with COI ordering restriction.