Advanced Concepts in Additive Manufacturing Course

Lesson 1 • AM Workflow from Design to Part

Maps the end-to-end AM workflow: CAD, file preparation, build, post-processing, and inspection. Establishes the process chain students will master throughout the course.

Lesson 2 • History and Evolution of AM

Traces AM from early stereolithography to modern multi-material systems. Provides context for understanding why current process families exist.

Lesson 3 • Core AM Terminology and Metrics

Introduces standard vocabulary: layer thickness, build envelope, resolution, and accuracy. Ensures precise communication across engineering and business teams.

Lesson 4 • Material Classes in AM

Surveys polymers, metals, ceramics, and composites used across AM processes. Links material properties to process compatibility and end-use performance.

Lesson 1 • Topology Optimization Fundamentals

Introduces load-path analysis and material distribution algorithms for minimum-mass structures. Students apply optimization outputs directly to AM build files.

Lesson 2 • Lattice and Cellular Structure Design

Covers unit cell types, relative density, and graded lattice strategies for lightweight parts. Connects lattice geometry to mechanical and thermal performance targets.

Lesson 3 • Support Structure Strategy

Analyzes overhang angles, thermal gradients, and support removal constraints across process families. Students minimize support volume while maintaining build integrity.

Lesson 4 • DfAM Principles and Mindset

Contrasts DfAM with conventional design rules and explains why traditional constraints no longer apply. Shifts student thinking toward AM-native geometry.

Lesson 1 • Vat Photopolymerization Processes

Covers SLA, DLP, and MSLA cure mechanics, resin chemistry, and resolution limits. Connects exposure parameters to dimensional accuracy and mechanical properties.

Lesson 2 • Material Jetting and PolyJet

Explains droplet deposition, multi-material capability, and support wax removal for PolyJet. Highlights applications requiring high accuracy and Shore hardness gradients.

Lesson 3 • Polymer Material Selection Framework

Provides a structured decision matrix linking end-use requirements to polymer AM process and material. Students practice selection through application-based case studies.

Lesson 4 • Polymer Powder Bed Fusion

Details SLS and MJF sintering mechanisms, powder refresh ratios, and part nesting strategies. Students optimize builds for density, accuracy, and material reuse.

Lesson 1 • Post-Processing Metal AM Parts

Covers stress relief, HIP, heat treatment, machining, and surface finishing for metal AM parts. Students sequence post-processing steps to achieve final dimensional and property targets.

Lesson 2 • Metal Alloy Selection for AM

Surveys printable alloys: titanium, nickel superalloys, stainless steels, aluminum, and tool steels. Links alloy weldability, thermal properties, and powder characteristics to process fit.

Lesson 3 • Directed Energy Deposition Systems

Examines laser and electron beam DED, wire-arc AM, and hybrid DED-machining systems. Connects deposition rate, resolution, and repair capability to application selection.

Lesson 4 • Laser Powder Bed Fusion Fundamentals

Covers melt pool dynamics, scan strategies, and keyhole vs. lack-of-fusion defects in LPBF. Students link process parameters to density, microstructure, and residual stress.

Lesson 1 • Defect Classification and Root Cause

Catalogs porosity, cracking, delamination, and warping defects with their process-parameter root causes. Enables students to diagnose and correct build failures systematically.

Lesson 2 • Statistical Process Control for AM

Applies control charts, Cpk analysis, and process capability studies to AM production data. Students establish control limits and trigger corrective actions from SPC signals.

Lesson 3 • Parameter Development Methodology

Introduces design-of-experiments approaches for AM parameter optimization across energy, speed, and environment. Students build structured parameter development plans.

Lesson 4 • In-Process Monitoring Technologies

Surveys melt pool cameras, thermal imaging, acoustic emission, and layer-wise optical tomography. Connects sensor data to defect signatures for real-time process control.

Lesson 1 • Mechanical Property Anisotropy

Quantifies build-direction dependence of tensile, fatigue, and fracture properties in AM parts. Students apply anisotropy data to design decisions and safety factors.

Lesson 2 • Non-Destructive Evaluation of AM Parts

Applies X-ray CT, ultrasonic testing, and dye penetrant inspection to AM part qualification. Students select NDE methods based on defect type, material, and geometry.

Lesson 3 • AM Microstructure Formation

Explains solidification theory, epitaxial grain growth, and columnar-to-equiaxed transitions in AM metals. Links thermal gradient and cooling rate to resulting grain morphology.

Lesson 4 • Residual Stress and Distortion

Covers thermal gradient mechanisms, residual stress measurement, and distortion prediction methods. Students apply simulation and experimental data to minimize part distortion.

Lesson 1 • Quality Management in AM Production

Integrates quality planning, control plans, and traceability systems into AM production workflows. Students develop quality management plans aligned with industry certification requirements.

Lesson 2 • Supply Chain Redesign with AM

Analyzes inventory reduction, on-demand production, and distributed manufacturing enabled by AM. Students map supply chain transformations and quantify lead-time benefits.

Lesson 3 • Part Identification and AM Suitability

Provides a structured screening framework to identify parts that benefit most from AM conversion. Students apply geometric, functional, and economic filters to part portfolios.

Lesson 4 • Total Cost of Ownership Modeling

Breaks down machine, material, labor, post-processing, and overhead costs into a per-part cost model. Students compare AM vs. conventional manufacturing economics at varying volumes.

Lesson 1 • Large-Scale and Concrete AM

Examines gantry-based polymer extrusion, robotic DED, and concrete 3D printing for construction. Students evaluate structural performance and regulatory acceptance pathways.

Lesson 2 • AI and Machine Learning in AM

Applies machine learning to parameter optimization, defect detection, and generative design in AM. Students evaluate ML model types and data requirements for AM use cases.

Lesson 3 • Multi-Material and Functionally Graded AM

Covers hardware architectures and material interface strategies for multi-material AM systems. Students design parts that exploit composition gradients for performance advantages.

Lesson 4 • 4D Printing and Smart Structures

Explains shape-memory polymers, hydrogels, and stimuli-responsive composites used in 4D printing. Students design actuation sequences and evaluate deployment applications.