Colorado School of Mines is proud to announce the Fall 2018 launch of a brand-new interdisciplinary degree program in Advanced Manufacturing!
The program will include a 12-credit-hour Professional Graduate Certificate, designed to give working professionals a competitive edge in the advanced manufacturing space with in-depth knowledge and practical application of additive manufacturing techniques and principles, structural materials for AM, statistical and machine learning tools for data-driven materials manufacturing, and designing parts for AM methods. The four required courses for the Professional Graduate Certificate will initially be offered on campus (morning or evening time slots), with a near-term plan to create equivalent online course modules.
Another option for graduates is the 30-credit-hour Master of Science, Non-Thesis (MSNT) degree. In addition to taking the core courses that form the basis for the Certificate, MSNT students will be able to specialize in one of two current tracks (Additive Manufacturing of Solid Materials and Data-Driven Materials Manufacturing) by choosing complementary electives from a list that spans seven departments at Mines.
Two options for undergraduates round out the program: a Minor and an Area of Special Interest.
The program’s strength is grounded in the expertise of Mines professors from Mechanical Engineering, Metallurgical and Materials Engineering, Computer Science, Electrical Engineering, Physics, and Applied Mathematics and Statistics. Additionally, Mines has committed approximately $1M in a brand-new teaching lab and teaching-designed platforms to offer students hands-on access to cutting-edge AM technology.
ADAPT founding members Craig Brice of Lockheed Martin Space Systems and Bryce Meredig of Citrine Informatics were among the 40 leading expert participants in the TMS–MForesight workshop on Harnessing Materials Innovations to Support Next Generation Manufacturing Technologies in October 2017 in Pittsburgh, Pennsylvania. Craig Brice also served on the workshop organizing committee.
The goal of the interactive, professionally facilitated workshop was to forecast and brainstorm opportunity areas and enabling technologies related to materials science and engineering innovations that are likely to impact the next wave of U.S. manufacturing. The ideas generated by this workshop are documented in Harnessing Materials Innovations to Support Next Generation Manufacturing Technologies, available for free download through TMS. In addition to presenting thought-provoking insights into the potential future of manufacturing innovation, this technical report outlines actionable pathways and tactics identified to reach that future. This project was organized by TMS, on behalf of MForesight: Alliance for Manufacturing Foresight.
MForesight: Alliance for Manufacturing Foresight is a federally-funded consortium focused on enhancing U.S. manufacturing competitiveness by providing insights to decision makers on emerging technology trends and related priorities to inform policy and investments in advanced manufacturing. For information on events, projects, and activities, please visit the MForesight website.
On Feb. 22, Colorado Congressman Ed Perlmutter visited Colorado School of Mines to tour the ADAPT Center and the Center for Space Resources. ADAPT Executive Director Aaron Stebner led the tour, showing Congressman Perlmutter ADAPT’s state-of-the-art characterization equipment and describing our cutting-edge data analysis and design of experiments capabilities enabled by adapt.citrination. View all pictures
ADAPT member company Moog has donated an EOS M270 Direct Metal Laser Sintering (DMLS) system to Colorado School of Mines to further advance additive manufacturing research collaboration between the ADAPT Center and the Laser Machining Group led by Dr. Jeff Squier. This generous donation will serve as a tool for the development and characterization of additively manufactured nonreactive metals and as a test bed for integrating with AM a first-of-its-kind femtosecond laser imaging and machining system.
ADAPT is the focus of the feature article in the January issue of Additive Manufacturing. “How Machine Learning Is Moving AM Beyond Trial and Error” by Peter Zelinski highlights ADAPT’s machine learning approach to materials manufacturing and discovery in AM.