Advanced Manufacturing
Graduate Program at Colorado School of Mines

Advanced Manufacturing
Graduate Program at Colorado School of Mines

Program Overview

As manufacturing returns to the U.S., driven in part my technological and logistical advances that make operations more cost-competitive, industries will require a workforce well-trained in the latest tools and techniques and ready to innovate further. Mines’ advanced manufacturing programs focus on 3D printing or technologies that create objects one fine layer at a time. This allows for parts that are lighter, stronger and more intricate and can reduce the need for large and costly equipment.

Faculty with extensive experience in industrial manufacturing environments prepare students to apply cutting-edge techniques to a host of industries, including aerospace, biomedical, defense and energy.

The 12-credit-hour graduate certificate serves as the core of the master’s program. Students receive an introduction to additive manufacturing processes, learn about the materials used (with a focus on polymers, ceramics and metals), understand how to design parts for these innovative methods and apply data informatics and programming skills to real-world problems.

Students in the professional master’s program choose 21 credits in electives in addition to the core courses, delving further into the various aspects of advanced manufacturing. Mines offers dozens of courses in this area, including Analysis of Metallurgical Failures, Finite Element Analysis for Advanced Design Applications, Lean Manufacturing and Advanced Robot Control, just to name a few.

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Mines Minute: Additive Manufacturing

From fidget spinners to complex machines, additive manufacturing is revolutionizing modern manufacturing. Master’s student Connor McLean gives a rundown of the Additive Manufacturing program at Colorado School of Mines.

Program Details

Certificate

  • A completed bachelor’s degree in a relevant field from an accredited institution
  • Statement of goals/purpose: share your professional, academic and personal goals and why you believe Colorado School of Mines is the best place to achieve those goals
  • Resume or Curriculum Vitae (CV)
  • For international applicants or applicants whose native language is not English, please review the ENGLISH PROFICIENCY requirements

Professional Master’s

  • Candidates must have completed a bachelor’s degree in a relevant field from an accredited institution
  • A minimum grade-point average of 3.0 on a 4.0 scale is preferred
  • Statement of purpose letter: present your professional and personal goals
  • Resume/CV
  • For international applicants or applicants whose native language is not English, please review the ENGLISH PROFICIENCY requirements

For additional information, please refer to the Admissions Requirements page

Graduate Certificate, 12 credit hours

  • Core Requirements, 9.0
    • AMFG 401 or AMFG 501 Additive Manufacturing, 3.0
    • Two of the three remaining core courses, 6.0
      • AMFG 531 Materials for Additive Manufacturing, 3.0
      • AMFG 421 or AMFG 521 Design for Additive Manufacturing, 3.0
      • AMFG 511 Data Driven Advanced Manufacturing, 3.0
  • Electives, 3.0

Professional Master’s, 30 credit hours

  • Core Requirements, 9.0
    • AMFG 401 or AMFG 501 Additive Manufacturing, 3.0
    • Two of the three remaining core courses, 6.0
      • AMFG 531 Materials for Additive Manufacturing, 3.0
      • AMFG 421 or AMFG 521 Design for Additive Manufacturing, 3.0
      • AMFG 511 Data Driven Advanced Manufacturing, 3.0
  • Electives, 21.0 (Up to 6 credit hours may be replaced with project-based independent study)

» VIEW CATALOG

AMFG501. ADDITIVE MANUFACTURING. 3.0 Semester Hrs.

(II) Additive Manufacturing (AM), also known as 3D Printing in the popular press, is an emerging manufacturing technology that will see widespread adoption across a wide range of industries during your career. Subtractive Manufacturing (SM) technologies (CNCs, drill presses, lathes, etc.) have been an industry mainstay for over 100 years. The transition from SM to AM technologies, the blending of SM and AM technologies, and other developments in the manufacturing world has direct impact on how we design and manufacture products. This course will prepare students for the new design and manufacturing environment that AM is unlocking. The graduate section of this course differs from the undergraduate section in that graduate students perform AM-related research. While students complete quizzes and homework, they do not take a midterm or final exam. Prerequisites: MEGN200 and MEGN201 or equivalent project classes. 3 hours lecture; 3 semester hours.

AMFG511. DATA DRIVEN ADVANCED MANUFACTURING. 3.0 Semester Hrs.

(I) Although focused on materials manufacturing, this course is intended for all students interested in experimental design and data informatics. It will include both directed assignments to reinforce the concepts and algorithms discussed in class and a term project that will encourage students to apply these concepts to a problem of their choosing. Some programming background would be beneficial but is not necessary; the basics of python and the sklearn machine learning toolkit will be covered in the first weeks of the course. 3 hours lecture; 3 semester hours.

AMFG521. DESIGN FOR ADDITIVE MANUFACTURING. 3.0 Semester Hrs.

(II) Design for Additive Manufacturing (DAM) introduces common considerations that must be addressed to successfully design or re-design parts for additive manufacturing methods. Industry-leading hardware and FEA software will be used to explore all phases of the DAM workflow, including topology optimization, additive process simulation, distortion compensation, and in-service performance. 3 hours lecture; 3 semester hours.

AMFG522. LEAN MANUFACTURING. 3.0 Semester Hrs.

Throughout the course, students will learn to apply skillsets to real world problems, focusing on lean and six-sigma principles and methodologies. The course is taught with a focus on the DMAIC structure of implementation (Define, Measure, Analyze, Improve and Control) for improving and implementing process efficiencies in industry. The course is split into three general subject areas; 1) Lean manufacturing principles, 2) six-sigma and statistical process control (SPC) methodologies and 3) Implementation techniques focusing on graphical and numerical representation of processes using R. Students will receive an in-depth overview of Lean manufacturing principles and will perform case studies at local industries to implement learned skill-sets. Next, students will step-through several hands-on activities using real products to investigate six-sigma and perform SPC analysis, identifying shifts in process data and learning how to shift processes into capable processes. Lastly, students will learn about various implementation techniques for industry and will perform an in-depth analysis of the course topics based on the industry tours performed.

AMFG531. MATERIALS FOR ADDITIVE MANUFACTURING. 3.0 Semester Hrs.

(II) This course will cover various structural materials used in additive manufacturing (AM) processes. Focus will be on polymer, ceramic, and metallic compositions. General chemistry of each material will be covered with additional focus on the behavior of these materials when processed using AM. The course will span the entire AM lifecycle from feedstock fabrication to fabrication by AM to post processing and inspection of as-fabricated material. Students will have hands-on exposure to AM processes and will conduct laboratory studies of AM material properties. Additionally, students will conduct a semester-long research project exploring some aspect of AM materials. 3 hours lecture; 3 semester hours.

AMFG598. SPECIAL TOPICS IN ADVANCED MANUFACTURING. 1-6 Semester Hr.

(I, II) Pilot course or special topics course. Topics chosen from special interests of instructor(s) and student(s). Usually the course is offered only once. Prerequisite: none. Variable credit; 1 to 6 credit hours. Repeatable for credit under different titles.

Materials For Additive Manufacturing 

  • MEGN 511 Fatigue And Fracture 3.0
  • MEGN 515 Computational Mechanics 3.0
  • MLGN 505 Mechanical Properties Of Materials 3.0
  • MTGN 514 Defect Chemistry And Transport Processes In Ceramic Systems 3.0
  • MTGN 531 Thermodynamics Of Metallurgical And Materials Processing 3.0
  • MTGN 536 Optimization And Control Of Metallurgical Systems 3.0
  • MTGN 557 Solidification 3.0
  • MTGN 560 Analysis Of Metallurgical Failures 3.0
  • MTGN 564 Advanced Forging And Forming 3.0
  • MTGN 565 Mechanical Properties Of Ceramics And Composites 3.0
  • MTGN 580 Advanced Welding Metallurgy 3.0
  • MTGN 583 Principles Of Non-destructive Testing And Evaluation 3.0
  • PHGN 585 Nonlinear Optics 3.0
  • AMFG 531 Materials For Additive Manufacturing 3.0
  • AMFG 511 Data Driven Advanced Manufacturing 3.0
  • AMFG 421 Design For Additive Manufacturing 3.0
  • AMFG 521 Design For Additive Manufacturing 3.0

Design For Additive Manufacturing 

  • FEGN 525 Advanced Fea Theory & Practice 3.0
  • FEGN 526 Static And Dynamic Applications In Fea 3.0
  • FEGN 527 Nonlinear Applications In Fea 3.0
  • FEGN 528 Fea For Advanced Design Applications 3.0
  • AMFG 531 Materials For Additive Manufacturing 3.0
  • AMFG 511 Data Driven Advanced Manufacturing 3.0
  • AMFG 421 Design For Additive Manufacturing 3.0
  • AMFG 521 Design For Additive Manufacturing 3.0
  • AMFG 4xx/5xx Lean Manufacturing 3.0
  • MEGN 592 Risk And Reliability Engineering Analysis And Design 3.0
  • CEEN 401/501 Life Cycle Assessment 3.0
  • EBGN 576 Managing And Marketing New Product Developments 3.0

Data-driven Materials Manufacturing 

  • CSCI 507 Introduction To Computer Vision 3.0
  • CSCI 508 Advanced Topics In Perception And Computer Vision 3.0
  • CSCI 575 Machine Learning 3.0
  • EENG 509 Sparse Signal Processing 3.0
  • EENG 511 Convex Optimization And Its Engineering Applications 3.0
  • EENG 515 Mathematical Methods For Signals And Systems 3.0
  • EENG 517 Theory And Design Of Advanced Control Systems 3.0
  • MATH 530 Statistical Methods I 3.0
  • MATH 551 Computational Linear Algebra 3.0
  • MEGN 544 Robot Mechanics: Kinematics, Dynamics, And Control 3.0
  • MEGN 545 Advanced Robot Control 3.0
  • MEGN 587 Nonlinear Optimization 3.0
  • MEGN 588 Integer Optimization 3.0
  • MEGN 688 Advanced Integer Optimization 3.0
  • AMFG 531 Materials For Additive Manufacturing 3.0
  • AMFG 421 Design For Additive Manufacturing 3.0
  • AMFG 521 Design For Additive Manufacturing 3.0
  • AMFG 511 Data Driven Advanced Manufacturing 3.0
  • AMFG 4xx/5xx Lean Manufacturing 3.0

 

 Colorado ResidentOut-of-State Student
Tuition**$17,154$38,466
Fees*$2,378$2,378
Room & Board$16,700$16,700
Books & Supplies$1,500$1,500
Misc. Expenses$1,800$1,800
Transportation$1,300$1,300
Total$41,013$62,325
**Cost per credit hour$1,087$2,269

*Allowance for fees based on mandatory fees charged to all students. Does not include fees for orientation, library, yearbook, refrigerator rental, voice messaging, ect.

At less than 4.5 credit hours, you may be ineligible for financial aid.

Geoff Brennecka

Geoff Brennecka

Rank - Associate Professor

Email - gbrennec@mines.edu

Phone - 303-384-2238

Craig Brice

Craig Brice

Rank - Professor of Practice

Email - craigabrice@mines.edu

Phone - 303-384-2114

Charles (Chip) Durfee III

Charles (Chip) Durfee III

Rank - Professor

Email - cdurfee@mines.edu

Phone - 303-273-3894

Greg Jackson

Greg Jackson

Rank - Professor

Email - gsjackso@mines.edu

Phone - 303-273-3609

Jeffrey C. King

Jeffrey C. King

Rank - Professor

Email - kingjc@mines.edu

Phone - 303-384-2133

Dinesh Mehta

Dinesh Mehta

Rank - Professor

Email - dmehta@mines.edu

Phone - 303-273-3713

Alexandra Newman

Alexandra Newman

Rank - Professor

Email - anewman@mines.edu

Phone - 303-273-3688

Anthony Petrella

Anthony Petrella

Rank - Associate Professor

Email - apetrell@mines.edu

Phone - 303-384-2274

Sridhar Seetharaman

Sridhar Seetharaman

Rank - Professor

Email - sseetharaman@mines.edu

Phone - 303-273-3053

Jeff Squier

Jeff Squier

Rank - Professor

Email - jsquier@mines.edu

Phone - 303-384-2385

Gongguo Tang

Gongguo Tang

Rank - Associate Professor

Email - gtang@mines.edu

Phone - 303-384-2468

Eric Toberer

Eric Toberer

Rank - Associate Professor

Email - etoberer@mines.edu

Phone - 303-273-3171

Michael Wakin

Michael Wakin

Rank - Professor

Email - mwakin@mines.edu

Phone - 303-273-3607

Hua Wang

Hua Wang

Rank - Associate Professor

Email - huawang@mines.edu

Phone - 303-384-2326

Zhenzhen Yu

Zhenzhen Yu

Rank - Assistant Professor

Email - zyu@mines.edu

Phone - 303-273-3798

Xiaoli Zhang

Xiaoli Zhang

Rank - Associate Professor

Email - xlzhang@mines.edu

Phone - 303-384-2343

Career Outcomes

  • Additive manufacturing engineer
  • Additive manufacturing project engineer
  • Advanced manufacturing engineer
  • Computer hardware engineer
  • Cost engineer
  • Design for Additive Manufacturing (DfAM) engineer
  • Development quality engineer
  • Engineered plastics product and applications development process engineer
  • Engineering manager
  • Equipment engineer
  • Hardware engineer
  • Hybrid electronics materials engineer
  • Industrial engineer
  • Innovation engineer
  • Instrument controls engineer
  • Laser additive manufacturing engineer
  • Lithography engineer
  • Manufacturing and integration science researcher
  • Manufacturing engineer
  • Manufacturing innovation engineer
  • Manufacturing process engineer
  • Materials engineer
  • Materials processing engineer
  • Mechanical cost engineer
  • Mechanical manufacturing engineer
  • Medical device design and manufacturing
  • Metallurgical engineer
  • Microfabrication process engineer
  • Operational excellence engineer
  • Packaging engineer
  • Printed electronics engineer
  • Process engineer
  • Product development engineer
  • Production engineer
  • Propulsion development engineer
  • Prototyping engineer
  • Quality engineer
  • Research and development engineer
  • Stress engineer
  • Structures manufacturing engineer
  • Sustainability manufacturing
  • Systems engineer
  • Technical sales engineer
  • Turbomachinery manufacturing engineer
  • Validation engineer
  • Welding engineer

According to the U.S. Bureau of Labor Statistics, employment of industrial engineers is projected to grow 10 percent from 2019 to 2029, faster than the average for all occupations. That’s 30,000 new jobs. “Many companies will be seeking to make use of new technologies to automate production processes in many different kinds of industries,” says the BLS. “Those with knowledge of manufacturing engineering may have the best prospects for employment.”

Plastics Technology magazine, in an article from December 2019, pointed out five additive manufacturing trends to watch in 2020. They predicted greater industrial-scale adoption of additive manufacturing, increased automation, closer collaborations, an emphasis on sustainability and expansion of end markets, particularly in biomedical, consumer goods, automotive, aerospace and electronics.

While the manufacturing industry is at continued risk for disruption due to tariffs, a tight labor market and the COVID-19 pandemic, the uncertainties also offer plenty of opportunities.

“Additive manufacturing has gained plenty of ‘street cred’ through COVID-19 as small and large manufacturers, many that were quietly making unique products that could, of course, be made only through additive manufacturing,” according to SME, an association of professionals, educators and students in the manufacturing industry, which hosts the RAPID + TCT showcase of 3D technology companies. “The big 3D printer manufacturers themselves were also at the top of the news hour on a daily and weekly basis — from HP to Stratasys to 3D Systems and up and coming startups such as Carbon, Desktop Metal, MatterHackers, and even some smaller, lesser-known, but equally strong startup players that may not have been on your radar.”

“Many companies have shifted their efforts toward digital projects that build agility and scalability to help them to manage risk,” according to Deloitte’s 2020 manufacturing industry outlook. “Applying artificial intelligence, cloud computing, advanced analytics, robotics, and additive manufacturing to the value chain can increase visibility and transparency, allowing manufacturers to make faster changes to operations to respond to market-based threats or opportunities.”

In November 2020, 3D printing solutions company Essentium announced the results of its third annual study, which revealed that the use of large-scale additive manufacturing has more than doubled in the past year for 70 percent of manufacturing companies. The company also found that the number of companies that have shifted to using AM for full-scale production runs of hundreds of thousands of parts has doubled from 7 percent in 2019 to 14 percent in 2020.

“During the Covid-19 pandemic, AM proved it can step in to make quantities of supplies at scale, or at least the mold to make the product, to keep the assembly lines moving. The survey found 57 percent of manufacturers increased 3D printing for production parts to keep their supply chains flowing during the crisis. 3D printing investment plans have also changed at many companies: 24 percent of respondents have gone all-in; 25 percent of manufacturers are ramping up to meet supply chain needs; and 30 percent of respondents are evaluating industrial-scale 3D printing to fill supply chain gaps.”

“The survey highlighted the increasing expectation for more reliable and affordable 3D printing materials to deliver on AM’s promising range of benefits. The survey showed continued agreement that the manufacturing industry could save billions of dollars in production costs once 3D printing technology matures (90 percent of manufacturers agree). The majority (84 percent) of respondents think that companies investing in AM will have a clear competitive advantage in the next five years, while 87 percent believe 3D printing will increasingly drive local manufacturing. However, to achieve these benefits, materials innovations will be critical to overcome obstacles, including the high cost of 3D printing materials (37 percent) and unreliable materials (24 percent).”

Grad School Insights

Student Testimonial

Connor McLean

As a grad student, I’ve had the opportunity to design and build a 3D printer that uses high-powered lasers to sinter metal powder together. I’m creating it on an open-source platform so students at any level will be able to use it and learn more about additive manufacturing, materials and printing processes.

Connor McLean
Master’s Student, Advanced Manufacturing

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