Mechanical Engineer Engineering

Harshul Shah

Chicago, Illinois ***** +1-773-***-****

LinkedIn id: https://www.linkedin.com/in/harshulrshah/ ************@*****.*** Dedicated team player with leadership and communication skills. Seeking an opportunity to leverage my talents as an Engineer at your company. I have the follow-through and positive attitude that will allow me to achieve company targets, utilizing knowledge, internship experience and skills.

Education

University of Illinois at Chicago, Illinois (UIC) May 2020 Master of Science in Mechanical Engineering CPA: 3.5 / 4.0 Dharmsinh Desai University, Nadiad, India (DDU) May 2018 Bachelor of Technology in Mechanical Engineering CPA: 7.92 / 10.0 Skills, Certification & Membership

• Technical Skills:

• Software: AutoCAD, MATLAB, Simulink, CREO, Solid works, Microsoft Office, Python, C,C++ language.

• Language: Proficient in English, Hindi, Gujarati

• Certificate course: Autodesk AutoCAD [Engineering Design course (2D)] Apr 2015 Engineering Experience

Johnson controls-Hitachi Air Conditioners India Limited, Kadi, India Mechanical Engineering Intern Jan 2018 – Mar 2018

• Contributed in Designing the workflow and managed the assembly line for split air conditioners to increase productivity using spreadsheets.

• Achieved 5S standard & Six Sigma method in the assembly lines & learned about assembly and manufacturing of different RAC units and industrial refrigeration systems.

• Created a design layout of assembly parts storage and distribution system to improve efficiency of work force. Ainnovative International Ltd., Ahmedabad, India

Manufacturing Engineering Intern Jan 2017 – Jan 2018

• Advanced in manufacturing, assembly, quality control and packaging process for Water jet cutting machine.

• Facilitate on multiple project for a client requiring water jet machine with custom configurations using CAD design. Port Academic Center, UIC, Chicago, USA

Engineering Tutor Jan 2019 – Dec 2019

• Assist fellow athletes at UIC athletic center to guide them in right direction for achieving their academic goals.

• Achieve better grades by assisting in different ways to study. Project Experience

Mobile Actuating Ankle Foot Orthosis:(UIC) May 2019 – Dec 2019

• Designed the harness, motor housing and software of the mobile Ankle Foot Orthosis.

• We achieved a lighter, cost effective design than the state of the art, still in testing phase and achieve 5Nm torque. Slider Crank Mechanism:(UIC) May 2019 – Dec 2019

• Designed a multibody flexible connecting rod constraints of slider crank mechanism using SIGMA/SAMS software.

• Analyzed rigid body structure for forward and inverse dynamics. Autonomous Vehicle: (UIC) Jan 2019 – May 2019

• Worked in a group to develop a code and algorithm on Duckiebot an autonomous bot to follow lane, obstacle training and traffic rules implementation using python and computer vision.

• Achieved result where it could manage to recognize lanes and, could execute various actions depending on obstacles or signals detected.

PID control of DC motor with digital encoder: (UIC) Jan 2019 – May 2019

• Configured, designed tested a PID algorithm for speed and position control through Arduino IDE.

• Used H-bridge to connect motor and digital encode and used lab equipment, circuit boards to build it.

• Motor shaft positional accuracy up to 5% of desired value achieved and speed control in both directions. Robotic Bot Simulation: (UIC) Jan 2019 – May 2019

• Developed a code in python to make bot follow line and given directions

• Achieved BUG algorithm using IR sensor and global and local positioning coding.

• Obtained 85% accuracy for bot to stay on path input. Implementation of PID controller for Hardware in loop (HIL):(UIC) Aug 2018 – Dec 2018

• Designed a PID controller to control mass force plant using MATLAB and Arduino Uno environment.

• Implemented lowpass filter to convert PWM output from analog input. Face Recognition Based Attendance System:(UIC) Aug 2018 – Dec 2018

• Designed an algorithm and code for face recognition system using deep learning and Viola Jones features and hogg feature extraction method during Computer Vision final term project.

• Conducted experimental trials and system was able to give 90% accurate results, where it could recognize face, and match with prestored database to match the features extracted.

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