DMD-Lab organizes its research around three connected thrusts that link manufacturing science, materials intelligence, and industrial decision-making.
Intelligent Additive Manufacturing
We improve how products are made through physics-grounded and AI-enhanced additive manufacturing.
Focus Areas
- LPBF
- FFF/material extrusion
- process physics
- melt-pool modeling
- hot-end modeling
- in-situ data
- defect behavior
- process optimization
Methods
- Computational modeling
- machine learning
- process monitoring
- design of experiments
- simulation
- experimental validation.
Impact
More reliable additive manufacturing, stronger process control, and faster movement from concept to qualified part.
Predictive Materials and Process Design
We improve how products are measured by connecting material behavior, characterization, and processing history to performance.
Focus Areas
- Polymers
- composites
- recyclable materials
- bio-derived materials
- rheology
- printability
- thermal behavior
- process-property relationships.
Methods
- Materials characterization
- rheometry
- FTIR
- microscopy
- thermal analysis
- mechanical testing
- simulation
- data-driven evaluation.
Impact
Better material selection, improved printability, stronger quality evidence, and more predictable manufacturing outcomes.
Smart Manufacturing and Distribution Systems
We improve how products are moved by connecting manufacturing intelligence, digital systems, and distribution analytics.
Focus Areas
- Digital twins
- data fusion
- human-in-the-loop decision support
- smart manufacturing
- distribution analytics
- Lean distribution
- operational excellence
- workforce development.
Methods
- Data analytics
- workflow modeling
- process mapping
- simulation
- Lean Six Sigma
- decision-support tools
- student-industry projects.
Impact
Faster decisions, improved operational visibility, stronger distribution performance, and practical value for industry partners.