Additive Manufacturing

Minor and ASI in Additive Manufacturing

The interdisciplinary Additive Manufacturing program will prepare undergraduates to meet the challenges of careers in additive manufacturing. Undergraduate students have the following degree options:

  • Area of Special Interest (12 credits)
    • Requirements: AMFG401¬†and 9 credits of electives (see Table 1)
  • Minor (18 credits)
    • Requirements: AMFG401 and 15 credits of electives (see Table 1)

Table 1: Undergraduate elective courses, listed by specialty area (AMFG531, AMFG 511 and FEGN 526 require approval by appropriate program directors)

Additive Manufacturing of Structural Materials
MEGN381MANUFACTURING PROCESSES3.0
MEGN412ADVANCED MECHANICS OF MATERIALS3.0
AMFG421DESIGN FOR ADDITIVE MANUFACTURING3.0
AMFG531MATERIALS FOR ADDITIVE MANUFACTURING3.0
AMFG498SPECIAL TOPICS IN ADVANCED MANUFACTURING1-6
AMFG511DATA DRIVEN ADVANCED MANUFACTURING3.0
FEGN525ADVANCED FEA THEORY & PRACTICE3.0
FEGN526STATIC AND DYNAMIC APPLICATIONS IN FEA3.0

Courses

AMFG401. 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. Prerequisites: MEGN200 and MEGN201 or equivalent project classes. 3 hours lecture; 3 semester hours.

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AMFG421. 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.

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  • 1. Execute a topology optimization, interpret results, and re-parameterize geometry to facilitate downstream shape/design refinement.
  • 2. Explain the key factors driving support placement in an AM part.
  • 3. Use software tools to plan the tool path for an AM process.
  • 4. Set part orientation in an AM process to minimize surface area or volume of support material.
  • 5. Simulate the thermal history of a part manufactured using an AM process.
  • 6. Simulate post-production heat treatment for an AM process.
  • 7. Optimize part orientation in a powder-bed AM process to minimize part distortion or maximize in-service fatigue life.
  • 8. Clearly communicate in writing the findings of an AM design verification evaluation.

AMFG422. 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. Prerequisite: MEGN381.

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  • Critique real-time manufacturing processes with regards to information flow, product flow and process times.
  • Identify value adding steps in manufacturing processes in order to better understand where waste lies
  • Recognize real-time wastes in manufacturing processes and facilities and reorganize processes using efficiency models and learned skill-sets to reduce defects found throughout the process
  • Implement lean and six-sigma methodologies to eliminate waste and decrease defects from observed and analyzed processes
  • Utilize R and MiniTab software to create control charts
  • Recognize when to use various applied statistical graphical and numerical representation to understand a process
  • Create analytic reports discussing change implementation plans based on real-time data for upper level management to implement for process efficiency
  • Apply learned skillsets to real-time manufacturing processes and facilities

AMFG423. DESIGN AND ANALYSIS OF EXPERIMENTS. 3.0 Semester Hrs.

This course introduces effective experimental design and analysis methodologies relevant to all engineering and scientific disciplines to maximize the information learned from every experiment (test case) while minimizing the total number of tests. We will be using state-of-art methods steeped in statistics to effectively set up your experiments, understand what the results are telling you, and clearly communicate the results to peers and leadership. We apply a disciplined systems engineering approach across the four major experimental phases: plan, design, execute, and analyze. This hands-on class will focus on understanding concepts and practical applications while relying less on the statistical theoretical development. Prerequisite: MATH 201 is recommended, not required.

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  • At the completion of this course, students will: 1) Formulate an analytically defensible test strategy using foundational principles across the Plan-Design-Execute-Analyze phases of experimentation.
  • 2) Apply statistically-based methods to understand results and quantify risk from single factor experiments.
  • 3) Create and analyze full-factorial test designs with multiple input explanatory variables understanding the critical importance of interactions.
  • 4) Construct appropriate test designs to screen many possible input factors to isolate those few variables that drive system behavior.
  • 5) Construct response surface test designs that build on screening methods to characterize nonlinear behavior often seen in practical applications.
  • 6) Compare alternative experimental designs with statistically-based performance metrics.
  • 7) Assess advanced experimental designs that better fit the actual test environment rather than forcing the problem to conform into a common design.

AMFG498. 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.

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