May 2019 Student Simulation Competition - Contest Overview

Overview of Contest:

There are two ways to enter the Simio Student Case Competition. You can either enter directly or through class participation. This contest, we had 20 teams enter directly (57 students) and 18 instructors with 190 teams (740 students) for a total of 210 teams (797 students).

We also had representation from the following 13 countries:

• Chile
• China
• Columbia
• El Salvador
• France
• Germany
• Guatemala
• India
• Mexico
• South Africa
• Spain
• Thailand
• USA

The 797 students came from these 27 schools:

• CETYS Universidad
• Chulalongkorn University
• College of Engineering Trivandrum
• ITAM
• IUT de Nantes
• Kansas State University
• NC State University
• Otto-von-Guericke-Universität Magdeburg
• Penn State Behrend
• Rochester Institute Of Technology
• Sichuan University
• Texas A&M University
• The Pennsylvania State University
• UES
• Universidad Arturo Prat
• Universidad Católica del Norte
• Universidad de Jaén
• Universidad de los Andes
• Universidad de San Carlos de Guatemala
• Universidad EIA
• Universidad Panamericana
• University of Central Florida
• University of Pittsburgh
• University of Washington Seattle
• University of Witwatersrand
• Western Michigan University
• Zhejiang University

Summary of the Problem:

Super Intensive Megastore with Integrated Operations (S.I.M.I.O.) utilizes cutting edge technology and advanced analytics to minimize cost.  This is reflected in the level of sophistication of their distribution center operations.  Real time information actively guides decision making.  Verification, optimization, and automation are a part of daily life.  Due to the complexity of the operation, it is difficult to predict how additional investment will function after implementation.  Specifically, how should orders be prioritized and dispatched to minimize labor costs?  The best way to answer system performance questions is to create a detailed digital twin of the system, simulate activity, and observe/quantify the outcomes.

Labor is the major cost driver and a constrained resource; the system can be divided along labor areas of:  Put away (including vehicle constraints), Select, and Replenish. The focus of this problem will be put away.  The primary goal will be to evaluate different dispatching methods to improve metrics like pallets per hour, utilization, cost and travel distance.  We are looking for ways to achieve a specified target to help evaluate additional hardware to handle more of the inbound demand. The model must be implemented using data-driven techniques to make it easy to change parameters.

Read the full problem!

Judging Criteria:

The judging was based on:

• Quality/clarity of the presentation
• Analysis/use of input data
• Modeling detail/approach
• Model internal documentation
• Verification and Validation
• Quality of animation
• Experimentation/exploration of alternatives
• Analysis of results
• Quality of the recommendations
• Overall project quality and Executive Summary

For more detail, see the Contest Judging Criteria.

Judging Panel:

 

Academic and Commercial:

Mustafa Gocken Assistant Professor at Adana Science and Technology University (Turkey)	Michael Zimmer Sr. Business Consultant at Vidant Health (USA)	Andrew Miller Industrial Engineer at BAE Systems, Inc (USA)
Louis Luangkesorn Assistant Professor of Industrial Engineering at University of Pittsburgh (USA)	Ivan Vilaboa Professor at Buenos Aires Institute of Technology (Argentina)

 

Simio LLC:

David Sturrock VP of Operations	Alex Molnar Application Engineer	Caleb Whitehead Application Engineer	Adam Sneath Application Engineer Intern

May 2019 Contest Winners