The goal of this theme is to create, test and standardize feedstock metal and metal alloys to broaden the scope of metal parts that can be easily and cost effectively adapted to metal AM processes.

Project 1.1: Development of Next Generation Alloys

• Sub-project 1.1.1) Development of thermally stable aluminum alloys for LPB-AM

• Sub-project 1.1.2) Development of titanium alloys for LPF-AM and LPB-AM

• Sub-project 1.1.3) Development of tool steels for LPB- and LPF-AM

• Sub-project 1.1.4) Development of nickel alloys for LPB-AM

• Sub-project 1.1.5) Development of refractory metals for LPB-AM

Project 1.2: AM Processing of Multi-Material Systems

• Sub-project 1.2.1) Novel Composites for BJ-AM to Develop Foam-Based Structures

• Sub-project 1.2.2) Alloy Alteration for Functionally Graded Materials (FGMs) used in LPF-AM

Project 1.3: Cost Reduction Strategies

• Sub-project 1.3.1) Recyclability of powder feedstocks for LPB-AM

• Sub-project 1.3.2) Plasma spherodization of low cost powders

• Sub-project 1.3.3) Cost-effective feedstock

The goal of this theme is to develop novel, robust, and efficient numerical models that will become the new tools for simulating different aspects of the Laser- and electron-beam-based powder-bed and powder-fed AM processes, along with melt-feedstock interactions and its effects on the finished parts.

Project 2.1 Multi-Scale Modeling of AM

• Sub-project 2.1.1) Beam-powder/melt pool interaction and energy transport: experimental validation

• Sub-project 2.1.2) Meso-scale thermal field evolution in melt pool substrate

• Sub-project 2.1.3) Macro-scale thermal field evolution

• Sub-project 2.1.4) Macro-scale stress field evolution

• Sub-project 2.1.5) Microstructural modeling and experimental validation

Project 2.2: Accelerated Real-Time Simulation Platforms

• Sub-project 2.2.1) Fast Process Thermal-Field Simulation

• Sub-project 2.2.2) Fast Process Stress-Field Simulation

Project 2.3: Pre-Processing for Optimization of AM Process Parameters

• Sub-project 2.3.1) Pre-processing for dimensional control

• Sub-project 2.3.2) Lattice structure design for AM processing

• Sub-project 2.3.3) Component build geometry optimization for AM processing

The goal of this theme is to develop novel in- and off-line quality assurance protocols to establish the relationship between in-process feedback data and post-process part characterization. Machine learning algorithms, along with sophisticated monitoring and metrology devices, will effectively monitor defects and disturbances in real-time allowing for adjustments in process parameters through advanced controllers. The end result will push AM technology toward “Certify-as-you-build” platforms.

Project 3.1: Innovative in-situ and ex-situ monitoring strategies for AM-made product quality analysis

• Sub-project 3.1.1) Development of non-contact dynamic melt pool characteristic measurement via radiometric monitoring for LPB and LFF-AM

• Sub-project 3.1.2) Development of continuous and layer-intermittent imaging capabilities for LPF, LPB, and BJ

• Sub-project 3.1.3) Develop non-contact capability to detect sub-surface properties using eddy current inductive measurements

• Sub-project 3.1.4) Laser ultrasonic sensing for LPB and LPF

Project 3.2: Real-time control and machine learning algorithms for laser powder-bed and powder-fed AM processes

• Sub-project 3.2.1) Knowledge-based lumped models

• Sub-project 3.2.2) Develop intelligent controllers

Project 3.3: Intelligent closed-loop control of compaction density for powder-bed based AM processes

• Sub-project 3.3.1) Measurement system development and validation of combined powder spread linked with sintering model

• Sub-project 3.3.2) Closed-loop control of compaction density and experimental validation

Project 3.4: Process-based adaptive path planning protocols for LPF-AM

• Sub-project 3.4.1) Combined trajectory optimization and thermal analytical models

• Sub-project 3.4.2) Adaptive path planning protocols/controllers and experimental validation

The goal of this theme is to use the fundamental knowledge generated in Themes 1 through 3 to accelerate the development of innovative metal AM process parameters and finished-part performance roadmaps that can be certified to ensure the quality and repeatability of AM built parts.

Project 4.1: Innovative AM processes with integrated Magnetic systems

• Sub-project 4.1.1) Magnetically driven vacuum-based powder delivery processing head for LPF-AM

• Sub-project 4.1.2) Levitated additive manufacturing

Project 4.2: Development of innovative architectural/cellular/lightweight/smart products

• Sub-project 4.2.1) Metal AM for orthopaedic and implants technologies

• Sub-project 4.2.2) Development of smart molds with embedded optical sensors and conformal channels

Project 4.3: Development of innovative FGM products

• Sub-project 4.3.1) Direct manufacturing of FGM advanced part using PTA-AM

• Sub-project 4.3.2) Direct manufacturing of FGM molds using LPF-AM

Project 4.4: Advanced LPF-AM and PTA-AM for repair and remanufacturing

• Sub-project 4.4.1) Repair strategies with LPF-AM

• Sub-project 4.4.2) Repair strategies using EWF-AMCo-op-16 (Y3 at McGill)

• Sub-project 4.4.3) Repair strategies using PTA-AM