Matt Schaefer, Ph.D.

Associate Professor

Milwaukee WI UNITED STATES
Allen Bradley Hall of Science: S144
Mechanical Engineering

Dr. Matt Schaefer is an associate professor in MSOE's Mechanical Engineering Department.

Contact

Multimedia

Education, Licensure and Certification

Ph.D.

Materials Science & Engineering

Marquette University

1997

M.S.

Mechanical Engineering

Marquette University

1990

B.S.

Mechanical Engineering

Marquette University

1984

Biography

Dr. Matt Schaefer is an associate professor in the Mechanical Engineering Department at MSOE. He teaches Instrumentation and Control of Systems, Intro to Engineering Design, Materials Science, Engineering Materials, Instrumentation, and advises Senior Design. Prior to joining MSOE in 2005, he taught at the University of Wisconsin-Milwaukee and Marquette University. He also gained industry experience at Briggs & Stratton and General Electric Co. He was awarded the 2016 Outstanding Junior Faculty Award from the Manufacturing Division of ASEE and the 2017 Faculty Appreciation Award from the MSOE Student-Athlete Advisory Committee. He earned his bachelor's and master's degrees in mechanical engineering from Marquette University and his doctorate in materials science and engineering from Marquette University.

Areas of Expertise

Stem

Materials

Accomplishments

Faculty Appreciation Award, MSOE Student-Athlete Advisory Committee

2017

Outstanding Junior Faculty Award, Manufacturing Division of ASEE

2016

Affiliations

Society of Automotive Engineers (SAE) International : Member
American Society for Engineering Education (ASEE) : Member
American Society of Mechanical Engineers (ASME) : Member

Social

Media Appearances

MSOE Defending Champs Return with Brand New Build

Formula Hybrid

2018-05-01

Defending champs from last year’s Formula Hybrid competition, the Mozee Motorsports team from the Milwaukee School of Engineering, went back to the drawing board to build this year’s parallel hybrid, says faculty advisor Dr. Matthew Schaefer.

“It was just time to start over from scratch,” says Schaefer, who is back in Loudon this week for his fifth time at the competition, fourth as the team’s adviser. Only the tires and steering wheel are returning from last year’s car, he says.

Event and Speaking Appearances

Use of Casting Simulation and Rapid Prototyping in an Undergraduate Course in Manufacturing

Manufacturing Division: ASEE Annual Meeting New Orleans, LA, June, 2016

The Cards Wager Assignment: Betting Homework Points on Statistical Process Control

Manufacturing Division: ASEE Annual Meeting New Orleans, LA, June, 2016

Failure Analysis in Mechanical Design: Fatigue, Fracture and being a good Engineering C.S.I.

ASME Milwaukee Chapter Meeting Waukesha, WI, March, 2015

Research Grants

WSGC Travel Grant

For MSOE ROV team $3000

2016 and 2017

Selected Publications

Use of Casting Simulation and Rapid Prototyping in an Undergraduate Course in Manufacturing Processes

ASEE Annual Meeting in New Orleans

Mathew Schaefer

2016

Mechanical Engineering students at Milwaukee School of Engineering (MSOE) study manufacturing processes in the junior year. Part of their study in this course is a project to create an original casting. This project encompasses several steps. First is to design the part and the associated mold system (gates & risers) for sand-casting the part. Next, students analyze performance of their mold layout through the use of SolidCast casting simulation software and make improvements to the initial mold layout. A final version of the casting design is submitted to the MSOE rapid prototyping center for fabrication of the casting patterns. The last step is to make an aluminum sand-cast part, in a small-scale foundry in MSOE’s labs. The project emphasizes the basic premise of the course; a manufactured part must be designed within the limitations and capabilities of the manufacturing process.

Successful completion of the project covers several key course outcomes, including: 1) understand the steps involved in basic green-sand casting process along with its capabilities and limitations, 2) apply this knowledge to design a component and mold layout, 3) understand the characteristics of a good versus poor mold layout, 4) apply modern computing methods as a means to do design of an effective mold for sand casting. With the successful implementation of SolidCast™ and rapid prototyping methods into this project, students learn course outcomes at a much higher level. In the past, the lab was an informative exercise where students made sand cast parts. Now it is a true engineering design experience for the students. They are able to approach mold design as a fluids problem, a heat transfer problem, and a manufacturing quality and cost problem.

The Cards Wager Assignment: Betting Homework Points on Statistical Process Control

ASEE Annual Meeting in New Orleans

Mathew Schaefer

2016

Suppose one weekend you are at the Bellagio Casino playing blackjack and the pit boss comes over and makes a proposition. It seems one of the dealers has been cheating and switched some cards in his shoe (a “shoe” holds 6 standard decks of cards). The pit boss tells you the bad shoe is either at table 1 or table 2, at the far end of the casino. The other table has a good shoe, which contains standard cards. The pit boss, being a gambling type, makes you the following offer; If you correctly pick which one is the bad shoe he will pay you $300. If you pick and are incorrect you owe him $150. Do you take the bet?

This problem serves as an outstanding analogy for teaching concepts of statistical process control in a junior level mechanical engineering course in Manufacturing Processes. This hypothetical wager serves as an extra credit problem in which students literally wager homework points for an opportunity to take a shot at the extra credit problem.

Students want to maximize their homework grade just as corporations want to maximize their profits. Trying to make a profit requires some risk up front and some intelligent monitoring of the manufacturing processes used to make a product. Process monitoring costs money. Investing more in process monitoring leads to greater confidence that “good product” is being made but only if the process data is analyzed intelligently.

Statistical process control is all about determining if some real population (parts or cards) matches some ideal population. For “The Cards Wager Assignment” above, students may choose to wager ($150 = 15 homework points) for the chance to win extra credit homework points ($300 = 30 points). But the heart of the problem is that students may also pay extra to look at cards from the shoe. Every 10 cards chosen costs 1 homework point. More cards inspected may lead to a more confident answer. However, spending too much on looking at cards will cut into their potential homework grade profits. The best option for the student is to look at just enough cards and analyze their data intelligently to make a confident choice.