Department of Mechanical Engineering Indian Institute of Technology Bombay

PhD Defence of Mr. Kajal Khan (174107003): 11.02.2025 (Tuesday): 0300 PM - 0500 PM: ME Department Auditorium

Venue:

ME Department Auditorium

February 11, 2025

The final defence viva-voce examination / presentation of the PhD student Mr. Kajal Khan is arranged as per the following schedule.

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Date/Day of Viva-voce Examination: 11.02.2025 (Tuesday)
Time: 0300 PM - 0500 PM
Venue: ME Department Auditorium

Name of student: Kajal Khan, ANSYS INc.
Roll No.: 174107003
Thesis title: Modeling of Heat Transfer and Thermomechanical Stresses in Laser Powder Bed Fusion Process

External examiner: Professor Swarup Bag, ME Department, IIT Guwahati [To join online]
Internal examiner: Professor Salil Kulkarni, ME Department, IIT Bombay
Co-supervisor: Dr. L. Srinivasa Mohan, ANSYS Inc.
Supervisor: Professor Amitava De, ME Department, IIT Bombay
Chairperson: Professor Kishore Chatterjee, EE Department, IIT Bombay
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A short abstract of the thesis and a brief resume of Kajal are given below.

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Abstract

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Powder bed fusion with laser (PBF-L) is an additive manufacturing (AM) process that involves manufacturing of a part layer-by-layer by localized melting and solidification of metal powders. However, predicting and controlling melt pool characteristics, as well as residual stress and distortion at part-scale, is challenging yet crucial for preventing build failures and improving manufacturing yield. The present work addresses these key aspects in PBF-L using novel computational and analytical techniques. Firstly, a finite element-based 3D heat transfer model with adaptive remeshing is developed to simulate multi-track, multi-layer PBF-L processes. The model incorporates a novel dimensional analysis to predict melt pool geometries based on laser parameters and material properties. The accuracy of the computed results is validated against experimental data, demonstrating the model's capability to predict defects like melt track discontinuities and lack-of-fusion. The adaptive remeshing technique enhances computational efficiency by reducing time and memory requirements without compromising accuracy. Secondly, a novel analytical model is proposed to estimate through-thickness longitudinal residual stress distributions for part-scale PBF-L processes. The model uses a unique functional relationship to predict peak residual stress as a function of process parameters, enabling fast and practical stress estimation. The analytical predictions are rigorously tested against numerical and experimental results, showing good agreement and offering a cost-effective tool for stress evaluation in large-scale builds. Finally, a novel approach is presented to enable numerical modeling of part scale residual stress and distortion with peak longitudinal and transverse residual stress for a deposited layer as initial stress, which are obtained from back-of-the-envelope functional relations. The numerically computed results of residual stress and distortion are tested rigorously with the corresponding experimentally measured results from literature for part scale PBF-L of common powder alloys which shows a fair reliability and efficiency of the proposed model.

Short CV of Mr. Kajal Khan

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Kajal Khan completed his B.Engg degree in 2012 from Indian Institute of Engineering Science and Technology (formerly known as Bengal Engineering and Science University, Shibpur), Shibpur, West Bengal and M.Tech degree in 2014 from IIT Bombay, Mumbai, Maharashtra. He has authored around 10 journal and conference papers in reliability and additive manufacturing. His research area includes joining science and technology, additive manufacturing and numerical modelling of manufacturing processes. He serves as a reviewer to multiple journals on welding and additive manufacturing. He joined IIT Bombay Ph.D programme as an external student in 2018.

Kajal Khan currently works as a Senior Application Engineer in Ansys based in Pune, India, with over a decade of experience specializing in Ansys Structural Simulations. With expertise in advanced manufacturing and electronics reliability, Kajal supports a diverse range of industries across the APAC region, including automotive, High-Tech and Aerospace & Defence. Previously he also worked in General Motors Technical Center India during 2014-15.

PhD Defence of Mr. Kajal Khan (174107003): 11.02.2025 (Tuesday): 0300 PM - 0500 PM: ME Department Auditorium

Department of Mechanical Engineering

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