Preetam Kulkarni Email & Phone Number

Arlington, Texas, United States

• Created a prototype of a crowd logistics mobile app using Google AppSheet to help farmers transport their produce• Developed an agent-based model (ABM) of a centralized and decentralized crowd logistics network using Python and NetLogo• Implemented sequential sampling to generate a Random Forest and Catboost model of an ABM of a crowd logistics network• Developed a participatory ABM using Python’s Tornado and MESA packages and deployed it using cloud9 on AWS EC2 instance• Conducted sentiment analysis on feedback from undergraduate students on participating in a simulation experiment• Mentored and collaborated with graduate students in developing participatory ABMs on GitHub

Clarion, Iowa

• Implemented engineering deviation tracking and facilitated quality issue resolution through 8D for PDP projects• Executed Advanced Part Quality Planning activities for OFP and PDP projects• Conducted Design Process Assembly Reviews (DPAR) and PPAP submissions for purchased components• Facilitated system, design and process failure modes and effects analysis (FMEA)• Performed critical supplier risk assessment and created mitigation plans for PDP projects

Clarion, Iowa

• Developed an interactive dashboard linking machine failures to assembly stations• Implemented workflow and process map for deviation tracking• Collaborated with suppliers to resolve quality issues

Middle Amana, Iowa

• Created process maps and developed control plans for dimensional quality control of refrigerator doors• Supported relaunch of a product (3X) and have written Standard Operating Procedure (SOP)• Used DOE, SPC and root cause analysis to identify quality defects and implement corrective actions• Conducted trial runs to modify manufacturing processes and reduced annual service incident rate by ~0.3% • Won “Whirlpool Bravo” award for development and implementation of Door Value Stream Quality System

Ames, Iowa

Developed stochastic and deterministic optimization models for inventory control in MATLAB

Pune Area, India / Solihull, United Kingdom

• Analyzed and improved data consistency by 40% in GSPAS – assembly process management tool that uses standard language• Reviewed and eliminated Non-Value-Added (NVA) operations in GSPAS resulting in a 30% reduction in cycle time allocation• Verified digital pre-assembly of various Jaguar Land Rover vehicles and reduced the virtual build lead time by 60%• Delivered knowledge transfer sessions on DELMIA V5 and GSPAS to a group of 10 employees in four sessions• Won an award for developing work instructions in GSPAS for the assembly of ‘AJ133’ engine

Doctor Of Philosophy - Phd, Industrial Engineering, 4

Master’S Degree, Industrial Engineering, 3.91

Bachelor’S Degree, Mechanical Engineering, 82.1 %