Junior Data Scientist and Splunk Consultant

• Sep 2021 - Present

Master Thesis

• May 2019 - Nov 2019

Title: Development of an adaptive quality management model for agile automotive assembly of E-Vehicles in Industry 4.0 by analyzing production data. Motivation: In order to sustain in the current market, especially the automotive industry. It is important to offer products as per individual requirements. In order to achieve this agile methodology is required. Therefore, this project achieved a methodology for quality management in an effective way that reduces the time for inspection activities, unnecessary flows by utilizing the degree of freedom available in an agile environment (such as Drones, AGV, AR, etc.) • Developed an adaptive quality management model for agile automotive assembly in Industry 4.0 environment • Developed intelligent planning system for inspection activities by analyzing assembly data • Analyzed production data for improvement of inspection activities for reduction of cycle time using agile degrees of freedom Show less

Project work/Intern

• Apr 2018 - Dec 2018

Title: Development of methodology for car door assembly process with modern Laser technology in an agile environment. Motivation: To sustain current market conditions especially automotive, it is necessary to produce products effectively with good quality. Thereby, manufacturing products at high tolerance can be cost-effective at the same time it is necessary to inculcate quality to the product. Therefore this project achieved cost-effective and effective mounting of car door by designing an artificial intelligence model using a deep neural network • Extracted product data by Autodesk Inventor, laser scanner, and transformed the dataset using Python • Performed data analysis for development of adaptive door hinge using Python, Polyworks • Developed adjustable concept for car door hinge by machine learning algorithms and Artificial Neural Network (ANN) Show less

Internship Trainee

• Sep 2017 - Dec 2017

• Performed data analysis on production data with statistical software using Cornerstone, Minitab, Python • Prepared dataset of production process and carried out statistical data evaluation and visualized the data using Excel and Python • Applied machine learning algorithm for clustering the stainless-steel sheets considering Mechanical and chemical properties • Performed data analysis on production data with statistical software using Cornerstone, Minitab, Python • Prepared dataset of production process and carried out statistical data evaluation and visualized the data using Excel and Python • Applied machine learning algorithm for clustering the stainless-steel sheets considering Mechanical and chemical properties

Junior Engineer

• Jul 2014 - Nov 2015

• Worked on process optimization for Bellows extrusion process using Lean tools and Six sigma methodology. • Extracted production data from multiple sources, cleaned and transformed large datasets using MySQL, Minitab, Python • Reported KPIs to senior management daily by building dashboards for production process • Carried out Design of experiments (DoE) for obtaining optimal parameter of machines • Implemented and refined manufacturing process by applying lean manufacturing principles to remove bottlenecks and reduce the cycle time of process • Performed the processes simulations (SPC) using MiniTab and MS Excel • Design and development of the production process for bellows production (PPAP, PFMEA) Show less