Tag: MTU online

Manufacturing Engineering Programs From MTU Go Online.

A young manufacturing engineering professional touches a computer monitor while in a factory setting.

The Department of Manufacturing and Mechanical Engineering Technology (MMET) has recently announced two new online programs: the MS and the PhD in Manufacturing Engineering. Previously, these programs were available only on campus. 

Both Michigan Tech’s online master’s degree and PhD program, designed in partnership with industry, stress manufacturing competitiveness. This competitiveness is central to smart manufacturing, modeling, simulation, sustainability, additive manufacturing, and advanced materials. All of these areas are crucial to Industry 4.0.

The programs’ practical core curriculum, which covers both the breadth and depth of manufacturing engineering, is inspired by Society of Manufacturing Engineer’s Four Pillars of Manufacturing Knowledge:

  • Materials and manufacturing processes
  • Product, tooling, and assembly engineering
  • Manufacturing systems and operations
  • Manufacturing competitiveness

Flexible Manufacturing Engineering Degrees for Working Professionals

But according to John Irwin, Professor and Department Chair of MMET, these programs are not solely for manufacturing engineers.

That is, similar to Michigan Tech’s online manufacturing engineering certificate, these in-demand programs have been designed to attract people from a wide range of undergraduate backgrounds. Students might come from mechanical engineering, electrical or computer engineering, materials science and engineering, manufacturing engineering technology, biomedical engineering, and robotics.

In other words, many can enroll in and then benefit from these degrees, which provide the tools and knowledge to take the next step: earning SME certifications, which are available in Lean, Additive, and Robotics Manufacturing.

In addition, the master’s and the PhD programs are both flexible and customizable. You may choose from three pathways for the 30-credit master’s degree (thesis, report, or course-work only). Also, there are two options for the doctoral degree (60 credits or 30 credits). Options depend on whether you begin with an undergraduate or a master’s degree. Beyond the core courses, you can also choose electives from four fundamental manufacturing areas. Thus, you can customize a degree that matches your educational and professional goals.

These online programs allow students from Michigan and beyond to benefit from this rigorous curriculum while working part or full-time. In fact, both programs are designed so that those enrolled can collaborate with their employers to complete workplace-based projects or conduct thesis or dissertation research.

 Students in the GD&T course work virtually in teams taking a component of a system from their workplace to perform tolerance analysis and conversion of traditional dimensions to GD&T in order to improve part functionality and minimize manufacturing errors.

John Irwin, Professor and Department Chair of MMET

In-Demand Knowledge for Current and Future Manufacturing Engineering Challenges

In 2021, the waves of the pandemic started to quickly unravel supply chains across the world. Manufacturing plants slowed or even closed, ports experienced unprecedented back-ups, and transportation costs and inflation raised prices dramatically.

According to NAM’s (National Association of Manufacturer’s) Q3 2023 Manufacturer’s Outlook Survey, 72.1% of the respondents indicated that the biggest challenge facing manufacturers was attracting and retaining a quality workforce. 

And manufacturing engineers are obviously a crucial part of that quality workforce. The US BLS stated that the job growth for industrial engineers (one possible career path) between 2023-2033 is 12%. This growth is much faster than average. Currently, there are over 241,977 manufacturing engineers employed in the US, but there still is a need for more. 

Why? The drive to incorporate Lean manufacturing processes, advances in additive manufacturing, the digital transformation of the manufacturing industry, and the reshoring of manufacturing in the US have all magnified the demand for manufacturing engineers.

In particular, the manufacturing industry needs engineers with expertise in IOT (Internet of Things) technologies and smart factory solutions, which are essential to manufacturing competitiveness. Michigan Tech, in fact, has a long history in advanced these and other manufacturing solutions.

That is, both the MS and PhD in manufacturing support efforts highlighted by Automation Alley, Michigan’s Industry 4.0 knowledge center. This center has helped manufacturers of all sizes understand the rapid technological changes associated with digital technology in manufacturing, so that both Michigan and the nation remain globally competitive.

Quality means doing it right when no one is looking.

Henry Ford, American industrialist, founder of the Ford Motor Company

Get Started On Your Program Now.

Michigan Tech’s online manufacturing programs can help you accelerate your career while making a difference in Industry 4.0.

There is still time to begin a graduate program for Spring 2025. Alternatively, you can start with an online graduate certificate in manufacturing engineering, and then apply these credits towards an advanced degree.

For Spring 2025, MMET is offering Industry for 4.0 Concepts (MFGE 5200), Design for Additive Manufacturing (MFGE 5300), which are core courses for both the certificate and master’s degree. Industrial Safety (MFGE 5500), a core course for the master’s program, is also on deck.

For more information about these programs, please contact David Wanless, Associate Teaching Professor MET and Program Director; and visit the web page on Global Campus.

Linear Algebra Bridge Course Returns for Fall 2024

 A 3-D representation of Linear Algebra equations.

On Monday, September 16, 2024, Teresa Woods is once again teaching her ten-week, noncredit, asynchronous, online course: Linear Algebra: A Bridge Course for Prospective Applied Statistics Students.

If you’re unfamiliar with the term bridge course, it is a short, intensive, preparatory course. Bridge courses help learners acquire the necessary knowledge and skills to enter advanced study, which might mean an undergraduate program, graduate degree, or graduate certificate. Often, these courses are meant for students who have been provisionally accepted into a program.

Woods’ course is an effective, low-cost option for prospective students who need the linear algebra requirement to enroll in MTU’s Online Master of Science in Applied Statistics program. However, those interested in brushing up on their linear algebra, so that they can later apply to the MSAS program could also take it.

The course’s very practical curriculum covers the fundamentals of linear algebra as they are used in applied statistics. Some of the topics include, but are not limited to, the following:

  • systems of equations
  • vectors
  • matrices
  • orthogonality
  • subspaces
  • the eigenvalue problem

Students will benefit from an interactive learning experience that will make the concepts stick. That is, the course involves helpful instructor-led videos, extensive auto-graded exercises in Pearson’s MyLab Math, periodic review assignments, and regular instructor feedback.

What is Linear Algebra?

Algebra is a broad field encompassing the study of mathematical symbols and the rules for manipulating them. It includes various sub fields, such as elementary algebra, abstract algebra, and number theory.

Linear algebra, a specialized branch of algebra, focuses on the study of vectors, vector spaces (or linear spaces), matrices, eigenvalues and eigenvectors, linear transformations, and systems of linear equations. This foundational area of mathematics has applications in several fields, such as physics, computer science, engineering, economics, and applied statistics.

  • In physics, experts use linear algebra to describe physical systems, including quantum mechanics, classical mechanics, and relativity.
  • In engineering, those working in control theory, signal processing, and structural analysis recruit linear algebra tools.
  • Computer scientists use this branch of algebra in computer graphic creation, machine learning, data mining, and optimization problems.
  • Also, those in the field of economics apply linear algebra when modeling economic systems, analyzing input-output models, and optimizing resource allocation.

What is the Relationship Between Linear Algebra and Applied Statistics?

And, of course, linear algebra plays a key role in applied statistics.

Applied statistics is the implementation of statistical methods, techniques, and theories to real-world problems and situations in science, engineering, business, medicine, social sciences, and more.

It involves collecting, summarizing, analyzing, interpreting, and presenting data to make informed decisions, analyze scenarios, solve problems, and answer questions.

Applied statisticians often use linear algebra to analyze and then visualize data.

Applied statisticians also use advanced techniques, such as machine learning algorithms, to extract insights and patterns from large datasets. They work in a wide range of places: research institutions, the government, business and finance, universities, healthcare systems, and more.

These experts regularly apply linear algebra, primarily because of its ability to handle large datasets and complex calculations efficiently. 

What Are Some Real-World Examples of Linear Algebra and Applied Statistics?

Here are a few scenarios in which linear algebra and applied statistics work together:

  • A statistician working for Netflix might collect and then simplify data on user ratings for various movies. Next, they would represent that data as a matrix and train the model. By uncovering patterns in the ratings, they could then use the model to generate an effective recommendation system. This approach is also widely used in e-commerce sites and music streaming services.
  • Furthermore, a real estate agent might use linear regression, a common method for determining outcomes, to predict how housing prices will increase or decrease in the next year. This information would help them price houses in their portfolio, estimate their commission, and so on.
  • In the healthcare sector, professionals use linear algebra and applied statistics. Principal Component Analysis (PCA) helps reduce the complexity of a large dataset by identifying key patterns and relationships between variables. Through this approach, health officials can then predict and intervene on disease outbreaks more effectively.
  • And, of course, linear algebra and applied statistics work together in several processes involving elections. These include voter segmentation and targeting, predictive modeling, analyzing voting patterns, polling analysis, and redistricting and gerrymandering.

About Your Instructor

Teresa Woods, associate teaching professor in Mathematical Sciences, is helming this course. Woods also advises students and serves as assistant to the department chair.

Woods’ received her Master’s of Science in Mathematical Sciences from Michigan Tech in 2017. Her master’s report “ANALYSIS OF ALEKS MATHEMATICS PLACEMENT TEST DATA” combined her two areas of expertise (and passions): mathematics and educational assessment. That is, she holds both an MS in Mathematical Sciences and an MS in Education (with a focus on adult learning.)

If you take this course, you’ll benefit from an instructor who has considerable experience in teaching, a wealth of enthusiasm for elementary linear algebra, and a rich history in designing and delivering online courses. 

Reach Out if You’d Like to Learn More.

Need advice on whether this course is right for you? If so, please contact Teresa Woods at tmthomps@mtu.edu. Or if you have questions about our online MSAS program, contact Amanda at globalcampus@mtu.edu.