Engineering Mechanical

Gopinath Pakala

Curriculum Vitae

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Ambitious and motivated towards Mechanical engineering, especially in the field of product development and design construction. Particularly, meticulous to details, specifications and working in tandem with creative ideas discretely and adhere to precise instructions. Successfully executed cross disciplinary projects such as “bike rack”, “smart robotic gripper” and “super sonic jet”. Presently, undergoing on online courses for my personal development. Also trying my fortune to seek a suitable job and contribute myself for the growth and development of your esteemed organization in particular and benefit the society in general. I am eager to develop my skills in mechanical engineering. Education:

Master’s in Mechanical Engineering

Linkoping University (Sweden) Aug 2016 – Feb 2019

Courses: Machine Elements, Structural Optimization, Road Vehicle Dynamics, Advanced Materials (additive manufacturing), Polymer Materials, Multibody Dynamics, Project Management. Bachelor’s in Mechanical Engineering

GITAM University (India) Jul 2011 – Jun 2015

Courses: Automobile Engineering, Fluid Mechanics, Theory of Machines 1 & 2, Thermodynamics, Machine Design 1 & 2, Hydraulic Machine & Systems, Manufacturing and welding. EDX online- Electric and Conventional Vehicles

ChalmersX Institute of Technology Apr 2019 – Jul 2019 Course details: Automotive powertrains, Combustion engine powertrains, Electric powertrains Key Skills:

Technical software’s: CATIA V5, Creo, AutoCAD, ANSYS, Mode Frontier, Trinitas Other programs: CES EduPack, MATLAB, Simulink, Python, MS Office, MS Word, MS EXCEL, MS Access, MS Outlook. Soft skills: Committed team player, Proactive problem solver, Listener & learner, Report writing with presentation. Experience:

Product Modelling (CAD tools)

Linkoping University Mar 2018 – Jun 2018

Implemented design methodologies for construction of complex part’s design with parametric functions.

Executed rules-based programming in VBA for making 3D CAD models flexible and intelligent.

Spearheaded the team in virtual development of designing part level to product level automated CAD models. Tools: CATIA, VB script in Excel.

Project Course Advanced - Design Engineering and Product Development (Robotic gripper) ABB Aug 2017 – Jan 2018

Succeeded in achieving a smart robotic gripper concept by achieving idea to finished products by working under an agile team.

Developed and verification of designed parts using simulations for life cycle analysis.

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Used the CAD files after successful Design For Assembly and DFM testing to produce 3D printable parts. Tools: CATIA, CES Edupack, MATLAB, Ultimaker 3D Printer. Collaborative Multidisciplinary Design Optimization (Supersonic jet) Linkoping University Aug 2017 – Oct 2017

Incorporated model-based engineering and optimization of an aircraft with multi objectives.

Established connection among various tools such as CAD with CAE in generating efficient surrogate models to reduce simulation time by 50% and enhanced the performance with cost targets.

Devised a suitable design of experiments upon testing several to find the optimal solution for the project with increase in profits by over 25% from the initial model. Tools: CATIA, MATLAB, Excel, ModeFrontier, ANSYS.

Product Development (Bike rack)

Linkoping University Aug 2016 – Oct 2016

Established the key specifications based on the customer and the competitors in the market in developing a bike rack by collaborating with a cross-functional teams.

Transformed simple technical problems systematically using general methodology for concept proposal from needs and requirements through functional analysis.

Ensured risk analysis and concept evaluation for generation and selection of conceptual ideas. Master Thesis - Applied Machine learning for Generation of 2D Technical Drawings (R&D) Linkoping University Mar 2018 – Dec 2018

Part of research project from the Mechanical Design department at Linkoping University.

Accomplished 2D drawings in CAD using design automation for creating initial data.

Investigated and incorporated various machine learning algorithms useful for production drawings.

Delivered a framework for implementing machine learning algorithm connected with design automation for real-world usage.

Tools: CATIA, VB script, python, TensorFlow, Keras. Languages:

English: Fluent Telugu: Native Hindi: Fluent

References:

Mehdi Tarkian (Associate Professor at Linkoping University) Carl Johan Thore (Associate Professor at Linkoping University)

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