Name: Aniket Amar Thopte
Type: User
Company: Hewlett Packard Enterprise
Bio: M.S. Industrial Engineer from UNC Charlotte.
Interested to work in ⦿Supply Chain & Logistics ⦿Quality Control ⦿Manufacturing & Production ⦿Process Engineer
Location: Roseville, California, USA
Blog: https://aniket-thopte.github.io/
Aniket Amar Thopte's Projects
Config files for my GitHub profile.
• Conducted research & evaluated solutions for development & improvement of Amazon’s logistical system of 1-day shipping across US • Discussed and incorporated various factors such as competition/ global politics/ technology induced issues that influence the supply-chain operations of Amazon.Inc and provided solutions to meet the constant needs to react to continuous changing global business environment
Vehicle routing problem (VRP) is a generic name referring to optimization problems in transportation, distribution and logistics industry. Route planning techniques is one of the main tasks of VRP which aims to find an optimal route from a starting point to a destination on a road map. Choosing an appropriate route planning algorithm among the existing algorithms in the literature to apply it in real road networks is an important task for any transportation application. In this project, we first present two of the different route planning algorithms, and then explain how we compare and analyze their performance when they are applied in real road networks.
Performed Clustering Analysis using SAS v9.4 on Power Usage & Consumer Goods Data to draw insights about the dataset.
Regression analysis on fuel consumption data based on different variables & % voting for Bill Clinton in 1992 Presidential Election & Demographic variables using SAS 9.4.
Analyzing Electric Circuit Board Defect Dataset for Statistical Process Control using various Quality Tools & Techniques for the enhancement of Quality Control in a Manufacturing Setting.
Developed multiple predictive models with 90% accuracy for forecasting the daily-hourly bike rental count using Python & Machine Learning techniques like Regression, Clustering, Ensemble, Neural Network to achieve maximum accuracy
•Under-Graduation final year project sponsored by 'Sandvik Asia Private Limited', Pune, MH, India. • Successfully designed & manufactured a ‘Multi–Utility Trailer’ to carry payloads up to maximum 30 tons having varied dimensions and weight distribution.
Electric Load forecasting for a year on hourly basis using 3 different techniques. - linear Regression, - ANN (Using Matlab nntool), -K-Nearest Neighbor. All 3 codes are present with an detailed report on each technique.
Lean 6σ Green Belt Project: Process Improvement at Zoni Footwear Company using DMAIC Approach
Performed Logistic Regression on two different (Movie's Rating and Insurance claim) dataset. Explored statistical significance of various variables with respect to the target variable.
Using SAS Enterprise Miner performed Predictive Modeling Analysis using Decision Tree Technique to study the Consumer Purchase behavior in Supermarket when buying Organic Products.
Hourly probabilistic load forecasting for 1 full year. Dataset from 2002 to 2006 (i.e. 5 years data) on hourly basis. We have to provide 9 percentiles (10,20,…..,90). I have used Gradient Boosting Regressor technique for forecasting the probabilistic load for 2007 year on hourly basis. The code is present in the file, with an detailed report.
Term Project for Production Control Systems Coursework | Production Scheduling using Python (GUROBI Optimizer) on a Die Casting Production Case Study | Full CODE with data and final results along with detailed report is present.
Ranking the list of Laptop Suppliers using rating method, Pair-Wise comparison using Borda Count & Analytic Hierarchy Process.
Univariate data having seasonal nature and forecasting using Seasonal ARIMA. The full code and detailed report is uploaded.