Prashanth D

About

Work

Volvo Cars, India Tech Hub
|

Business Analyst Intern

Highlights

Analyzed supply chain data using SQL to identify bottlenecks, improving outbound logistics efficiency by 10%.

Designed Power BI dashboards to visualize KPIs, enabling real-time decision-making for key stakeholders.

Automated reporting workflows to reduce manual effort by 40% and enhance data accuracy.

Utilized IBM Maximo for asset management and planning, improving coordination between logistics and maintenance teams.

COE Toyota and Morris Garage
|

Intern

Highlights

Collaborated with Toyota and MG workshops to optimize vehicle diagnostics and service procedures, developing a predictive maintenance model in Power BI that reduced downtime by 30%.

item Applied Kaizen and Six Sigma principles to enhance maintenance processes and uphold high-quality standards in vehicle repair and service.

Volunteer

Agastya, GDSC RVCE
|

Volunteer

Highlights

participated in Social Welfare Events like Paper Drive, Utsarga, Akshara, and Plantation Drive.

Education

R.V College of Engineering

Bachelor of Engineering

Mechanical Engineering

Grade: 7.6

St Joseph's Pre-University College

Grade: 84.33

Awards

Gold Medal in Ideathon Event

Awarded By

Mechanical Department

Elite certificate

Awarded By

NPTEL

successful completion of course 'Design Technology and Innovation'

Skills

Languages

Python, C++.

Libraries

Numpy, Pandas, Matplotlib.

Tools

GIT, MySQL.

Platforms

Windows, Arduino, NodeMCU.

Core

Operation Research and management, Supply Chain analytics, Product Life cycle.

Other Technologies

Data Analytics, Excel, Power BI, SolidWorks, ANSYS, CNC Training, Machine Learning, IoT.

Projects

Supply Chain Optimization - AtliQ Mart

Summary

Analyzed AtliQ Mart's supply chain to enhance OTIF delivery metrics across three cities, track performance by city and customer, identify service gaps, and provide insights into popular product categories to improve operational efficiency.

Metal Defects Prediction

Summary

Predicted surface metal defects using image inputs by training a supervised learning model on various defect types, enabling accurate predictions up to 90% for different user inputs. The model was trained on labeled datasets, allowing it to classify and identify defects based on new image data.

eCommerce Insights

Summary

Analyzed eCommerce data to extract meaningful insights on customer behavior and sales trends, helping to drive better decision-making. Developed detailed visualizations that improved data interpretation, enabling stakeholders to quickly understand complex patterns and relationships.

IoT Gas Leakage Detection System

Summary

Developed an IoT system for real-time gas leak detection, triggers safety measures such as cutting off power, activating exhaust fans, and sounding alarms. A mobile app was designed to provide real-time notifications, enhancing safety through prompt alerts.