RESEARCH

I' have conducted a number of company and education research projects using statistical analysis (e.g., anova, six sigma, regression analysis), simulation programming (e.g., discrete event, systems dynamic, agent-based), and applied operations research (e.g., optimization, exact and metaheuristic programming). My research interest includes the following areas.

Supply Chain and Business Management;
Logistics and Transportation Network;
Risk and Disaster Management
Smart Manufacturing;
Additive Manufacturing/3-Dimentional (3D) Printing

Projects

Multi-modal Transportation Analysis for South Carolina

Team: Kasin Ransikarbum, Jon Lowe, Scott Mason

Timeframe: 2013

In this research, we use big-data and statistical analysis to develop sections in the statewide multi-modal transportation plan for South Carolina (SC) to aid decisions for SC's department of transportation. Analyzed topics include Economic Context of Freight Transportation in SC, Key Corridor Market Areas, Capacity Constraints, State Freight-Related Institutions and Funding Agencies, Impact of Freight Movements on the State’s Economy, Conditions and Performance of the State Freight Transportation System, and Project Level Recommendations

Discrete-Event Simulation and Optimization Modeling for Fabric Manufacturing

Team: Kasin Ransikarbum, Robert Allen, Kevin Taaffe, Scott Mason

Timeframe: 2013 - 2015

In this research, we develop a discrete-event simulation and optimization model for warping, inspection, and weaving process of the fabric company. We study operation performances and capacity-related decisions in machine, staffs, and performances related technical issues. Several experiments include package change experiment, extra dedicated versus shared flexible creeler experiment, impact of product mix to staff decision experiment, breaking point under different circumstances for higher demand, and the location of new machine.

Warehouse Layout Design using Agent-based Simulation

Team: Kasin Ransikarbum, Scott Mason, Jon Lowe

Timeframe: 2015

In this research, we analyze different scenarios for the plant layout design of distribution center (DC) to effectively and efficiently aid a decision maker. We use agent-based simulation model to model the current layout and hypothesized layouts. Next, the 3D animation is developed to verify and validate the model throughput. Statistical analysis is used to predict outcome of the hypothesized warehouse's layout in the study. Software AnyLogic

Supply Chain in Additive Manufacturing (3D Printing)

Team: Kasin Ransikarbum, Sangho Ha, Eunjoo Park, Jongmok Ma, Namhun Kim

Timeframe: 2016

In this research, we conduct an analysis related to operational, tactical, and strategic decisions for Additive Manufacturing (AM). We start from understanding the complexity of AM, analyzing compensation model for 3D printed part with distortion in the Selective Laser Sintering (SLS) platform, assessing topology optimization model for multi-material part, analyzing orientation alternatives using multi-criteria decision making, developing optimization model for 3D printer utilization, and synthesizing AM supply chain.

Disaster Operation Management using Optimization and Metaheuristic

Team: Kasin Ransikarbum, Scott Mason

Timeframe: 2014-2016

In this research, we use operations research (OR) techniques including multi-objective, mixed integer linear programming, goal programming, and metaheuristics to analyze and understand pre- and post-disaster operations. Our aims are to aid decision makers interested to optimally plan for network design during disaster. We use geographic information systems (GIS)-based software to verify and validate our study. In particular, HAZUS software developed by Federal Emergency Management Agency (FEMA) is used to analyze bottleneck of the network in our study.