Union Pacific-22 | Multidisciplinary Design Program

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Union Pacific runs trains all across the United States and with that comes many challenges. As we continue to build our systems, we need to ensure that the data being sent around our network is clean, in sync with other systems, and is easy to query. Students on the Union Pacific team will design and develop the components for building a comprehensive business data store structure and analytics model that will allow easy access to petabytes worth of data from a multitude of devices and systems.

Abstract:
One of America’s most recognized companies, Union Pacific Railroad (UP) connects 23 states in the western two-thirds of the United States by rail, providing a critical link in the global supply chain. Keeping 7,700 locomotives operating smoothly over 32,200 route miles requires significant data infrastructure.

Currently, UP analyzes data from 3 different systems to understand where trains are, how efficiently they are running, etc. There is a significant need to comprehend the data from these disparate systems to create a comprehensive and common data backbone that can solve problems in a precise and opportune fashion.

The student team of data analysts and developers, supported by current expert UP users, will evaluate the business use cases and the data that will be needed to build this system. The goal is a complete Big Data solution with a data store backbone and a predictive model that can be expanded and used to run various advanced analytics.

The 2022 UP Cohort team will design and develop the components for building a comprehensive business data store structure and analytics model.

Students on this team will create a backbone for data from the systems listed below. TCS (Train Scheduling System built using Oracle, Mainframe)

CADx (Computer-Aided Dispatching system (CADX built using C++, Oracle)
GPS data

This backbone data store will be used by Union Pacific’s Finance, Marketing, Network Planning, Asset Utilization, and Operations departments to answer asset-utilization efficiency questions like where the train or railcar is, how can the cycles be reduced to improve capacity, how can we optimize the fuel consumptions, where do we need to plan additional crews and locomotives etc. The solutions to these will help maximize revenue and drive the operating KPIs for the company.

Full Project Details

General Programming (1-2 students)

Specific Skills: General Programming skills with a focus on the backend. Completion of EECS 281. Experience with Java, Scala, Python, or C++.

Likely Majors: CS, DATA

Database Design (2-3 students)

Specific Skills: Advanced database design skills. Prior coursework and/or practical experience EECS 484: Database Management Systems prioritized. Experience with Oracle, SQL Server or Teradata. Experience in writing simple and complex SQL/HQL queries. Development experience with RDBMS or No SQL.

Likely Majors: CS, DATA

Data Science (1-2 students)

Specific Skills: Database design for maximal flexibility; GIS based data; Data Visualization; Synthesizing data sources; Data Mining

Likely Majors: DATA, MIDAS

Business Process Design (1 student)

Specific Skills: Business process analysis – (must have some knowledge of programming)

Likely Majors: IOE, BBA (with CS Minor), CS (with BBA minor)

Sponsor Mentor

Chloe Wheaton

Chloe Wheaton is currently a Systems Engineer in Union Pacific focusing on the big data effort for CORE project, which comprises a data store for railroad operational and financial analytics. In her current role, she is actively involved in systems design and data engineering, creating data pipeline, batch processing development using Spark-Scala and HQL, and performing data analytics and visualizations using Python, Zeppelin and Tableau. She joined Union Pacific in 2014, prior to that was a Summer Intern and Remote Year-round Intern for Union Pacific while pursuing a master’s degree. She obtained her Master of Science in Information in 2013 from University of Michigan, Ann Arbor. Prior to that, she was working for a machine translation company spearheading the application development team.

Executive Mentor

Andrew Henrichsen

Andrew Henrichsen joined Union Pacific in 2003 in UP’s Equipment Accounting Group. In the last fifteen plus years with the railroad, Andy has accumulated multiple IT responsibilities including production support for more than 100 systems. The systems are largely financial in nature and impact business activities from the collection of all freight revenue totaling more than $20 billion to costing systems to operational data for reporting and network planning activities. With responsibilities for so many systems that produce revenue, cost, and operational statistics Andy’s teams are active in Union Pacific’s Big Data efforts. Prior to joining Union Pacific, Andy was a developer for Fiserv writing banking software for the largest distributor of commercial banking software in the United States. Andy has a Bachelor of Science degree in Management Information Systems from Iowa State University and a Master of Business Administration from the University of Nebraska Omaha.

Faculty Mentor

Bill Arthur

Bill is a Lecturer III in the Department of Electrical Engineering and Computer Science at the University of Michigan. Most recently he has been teaching EECS 183: Elementary Programming Concepts. He previously worked in various roles in automotive manufacturing at Ford Motor Company and U.S. Manufacturing Corporation, and has mentored Union Pacific MDP projects before. (For more information, visit https://web.eecs.umich.edu/~warthur/)

Course Substitutions: Honors, ChE Elective, CS MDE/Capstone, CE MDE, Data Science Capstone, EE MDE, IOE Senior Design, IOE Grad Cognate, SI Elective, SI Grad Cognate

Citizenship Requirements: This project is open to all students on campus.

IP/NDA: Students will sign standard University of Michigan IP/NDA documents.

In Person/Remote Participation Options: All project work will take place on campus in Ann Arbor, with an opportunity to visit Union Pacific’s headquarters in Omaha, NE as University, State of Michigan, and local policies allow. Additionally, summer Internships (in Omaha, NE) are required for students who participate on this team. See “Internship/Summer Project Activities” below for more information.

As local safety protocols allow, students on this team must be able/willing to be physically present on campus in Ann Arbor and able/willing to work at the Union Pacific office in Omaha, Nebraska during the summer internship.

Internship/Summer Project Activities: 2022 Summer Internships (in Omaha, NE) are required for students who participate on this team. Students will have one (1) week from internship offer to accept the combined project/Union Pacific offer. By accepting a project offer, students are accepting an internship offer conditional of the criteria noted below.

All project students must participate in the Union Pacific summer internship program. All students must:

Pass a drug test
Cumulative University of Michigan GPA > 3.0 preferred

Offer letters will include pay rates, dates, and conditions of the internship.