Research Themes
Material Development Tailored with Optimum Process Parameters
While tremendous progress has been made in additive manufacturing over the past 30 years, the focus of new materials and technologies has been on polymeric materials. However, the demand for metallic parts made using AM processes exceeds that of polymeric materials within the global manufacturing sector. The global AM sector has consistently focused on using highly engineered powders which are exceptionally expensive and constitutes a significant portion of the final part cost; on average, 20%. The significantly higher net cost of metallic parts made by AM is a key factor inhibiting market growth. As the result of the powder grade constraints, only a limited number of metals or metal alloys are presently being used in commercial metal additive manufacturing. For AM metal parts to be a viable option for industry, new, high quality reproducible powders with characteristics that are appropriate for AM processes and applications must be developed. HI-AM’s research in Theme 1 will contribute valuable new metal powder options and it will increase processes reliability and repeatability rate by creating dynamic process maps to control the final quality and material properties of the finished part.
Theme Leader
Paul Bishop, PhD, PEng
Dalhousie University
Dept. of Mechanical Engineering
Email: Paul.Bishop@dal.ca
The objective of this project is to generate new powder metal feedstocks, with compositions strategically chosen to have a widespread and immediate impact on the global AM community. These new materials will broaden the mechanical, physical, and corrosion properties attainable within metallic products. This will help position AM as a viable manufacturing approach for a greater number of industrial applications.
Aluminum is an attractive option for AM because of its low inherent density, high strength to weight ratio, and its corrosion resistance. Al is a high value commodity in Canada and developing new Al alloys for AM is a direction that will positively impact national economic growth. This work will concentrate on two key challenges: 1) solidification cracking, and 2) chemistry changes via element evaporation. The research will focus on alloys with chemistries devoid of elements prone to volatilization during laser processing, (i.e. Zn, Mg, etc.) and low melting point eutectics, with consideration of solidification conditions and the strengthening mechanism targeted (heat treatment, dispersoids, or solid solution strengthening).
Principal Investigators:
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Paul Bishop |
Mathieu Brochu |
Hani Henein |
Titanium and its alloys represent a material category of major importance to the global aerospace sector, as it is a lightweight metal with significantly greater strength than most aluminum alloys. The objective of this subproject is to design and process innovative Ti alloy powders via LPF- and LPB-AM to expedite the adoption rate of these alloys within AM. The initial focus of this research is LPF-AM. Here, any new Ti-based powder systems must be designed to (1) impart attractive metallurgical attributes (i.e. mechanical properties, microstructure, corrosion resistance, etc.) within the finished products and (2) facilitate the manufacture of products that are dimensionally accurate, sound, and cost-effective.
Principal Investigators:
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Paul Bishop |
The use of AM for the fabrication of geometrically complex tools and dies is ideal, as the production volumes are low, geometries are complex, and the materials used in fabrication are challenging to process and machine within the confines of conventional forming technologies. The bulk of commercialized activities in this area have been constrained to H13 tool steel. The objective of this sub-project is to investigate the AM of alternate tool steels that embody similar metallurgical traits to H13 as well as other strategic benefits in terms of resistance to wear (grade A8) and shock loading (grade S7) in order to enable AM to be implemented in much wider range of tooling applications. Furthermore, Sc additions have been proposed to offer dramatic increases in strength to Al-Si alloys. Of interest is the increased strength that can be derived from hypoeutectic Al-Si-Sc alloys. The objective of this part of the sub-project is to explore the increases in strength achievable through the rapid solidification of an Al-10Si-0.4 Sc alloy. An additional objective of this sub-project is to characterize 17-4 precipitation hardened stainless steel, which is widely used in numerous fields, such as the aerospace, chemical, and mining industries as well as NiCrBSi or NiBSi with WC composites used in the oil sands and mining industries for wear applications.
Principal Investigators:
Carl Blais |
Hani Henein |
Most studies in nickel alloys have emphasized alloys 625 and 718, as they represent common workhorse alloys within the fabrication of gas turbine engines. Canadian companies operating in this sector are keen to implement these alloys as well as IN939, IN100, and Hastelloy X within the confines of AM. The goal of this subproject is to identify new nickel-based alloys and to find strategies to reduce the detrimental effects of the low melting point phases or reactions that prevent the fabrication of defect-free parts.
Furthermore, the fundamental conditions in which intermetallic materials can be processed by LPBF is studied in this project as well. The knowledge on AM of intermetallics is almost inexistent in the literature. This category of materials has a significant portion of its atomic bonding being covalent in nature, which increase its strength and reduces the ductility. As such, these alloys are less compatible with the thermal cycles imposed during AM. To that extend, the relation between intermetallic alloy and its cracking behavior during rapid thermal cycling is investigated from fundamental principles. Elucidating the paradigms would possibly open processing strategies for these alloys. The alloys investigated includes Ni-aluminide, Ti-aluminide and Fe-aluminide.
Principal Investigators:
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Mathieu Brochu |
Kevin Plucknett |
In this sub-project, the use of molybdenum alloys in LPB-AM will be investigated. Such alloys are of significant interest to aerospace engine manufacturers as a viable alternative to aluminide systems, yet little is known about their suitability for AM processing. Research will emphasize fundamental studies wherein solidification maps and the conditions (G and R) needed to achieve high-density products will be elucidated.
Principal Investigators:
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Mathieu Brochu |
Everyday composite materials are becoming lighter and stronger due to stringent industry standards such as CAFÉ 2025. As a result, lightweight, high strength composite structures are being used in many scenarios, ranging from small-scale biomedical industries to large-scale aerospace and tooling sectors. Lightweight materials are conventionally developed through micro-scale modifications, foaming, and by macroscopic material structuring. Functional grading of materials and foams are two of the more common practices for reducing material weight and commonly occur with the use of conventional subtractive manufacturing. However, it has been proven that customized multi-material objects with a complex internal architecture can easily be created through AM using lightweight, functionally graded polymer materials. Project 1.2 will build on this knowledge to investigate the use of metallic powder feedstocks in the same context, when utilizing BJ- and LPF-AM processes. At present, these AM technologies have not been utilized for such applications, due to challenges in binding different metallic materials together, difficulties in feeding different types of metals into AM systems, problems in controlling print resolution, and the collapse of the thin walls associated with porous structures during printing.
The objective of this sub-project to strengthen the Canadian knowledge on the development of metallic FGMs using LPF-AM. To this end, the research team is developing and optimizing the microstructure of filler materials and their corresponding binders for BJ-AM of novel composites.
Principal Investigators:
Hani Naguib |
To successfully develop FGM products, the sensitivity to processing parameters must be established in order to identify the processing window required to achieve the desired properties. The sub-project outcome will be a process map that correlates alloy chemistry, solidification/cooling temporal conditions and non-equilibrium microstructures under process/phase content maps. It will contribute to the databases required for the development of multi-material parts using LPF.The research results of this subproject will have tremendous utility in the tooling industry where the requirements include: high thermal conductivity materials for rapid cooling, as well as abrasion and impact resistance.
Principal Investigators:
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Kevin Plucknett |
Metal alloy powder costs are principally driven by two factors. One is the frequent use of rather exotic, non-conventional fabrication routes that produce particles of an exceptional quality, but at relatively low production rates. The second factor is that most powder production processes generate particles that follow a log-normal size distribution. Since their standard deviation typically falls between 2.0 and 3.0, yield becomes a significant problem given the restraint that only a narrow cut of powders is selectively extracted for current AM operations. Hence, it is not surprising that the metal powder costs will be the largest continuous expense through the life of an AM machine. Therefore, industry is very interested in concepts that have the potential to reduce raw material costs. Although adoption of AM technologies will most likely lead to a decrease in raw material costs through economies of scale, strategies must be devised to reduce material costs and/or maximize their utilization. Such developments are particularly important in the near term as it is expected that a growing number of new materials designed specifically for AM will soon become commercially available (i.e. Nanosteel BLDRmetal J-10, Airbus Group Scalmalloy, Alcoa $60M additive manufacturing center, etc.).
The objective of this sub-project is to understand the printing environment and to characterize the effect of recycling unfused particles in consecutive builds with/without additions of various volume fractions of new (unused) particles. The framework will be developed around a Ti-based alloy given the intense use of this metal in AM, and its acute sensitivity to changing levels of impurities (i.e. O, H, N, C).
Principal Investigators:
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Mathieu Brochu |
Gisele Azimi |
Current powders used in LPB-AM are required to be nominally spherical, and are created using gas or plasma atomization. Powders with irregularly-shaped particles can be produced at a much lower cost than the spherical ones (i.e. water atomization, hydride/de-hydride, Krolle processes etc.). In this sub-project, transforming the irregular low cost alloys to spherical particles is being studied.
Principal Investigators:
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Carl Blais |
Alloyed and tool steel powders are typically utilized in AM to create tooling for conventional material forming technologies. Such parts are produced in very low volumes as they can endure long periods of use and have a complex geometry that is only suitable for the production of a single product design. Studies show that AM parts produced from water-atomized low-alloyed steel powders have similar mechanical properties to those obtained with gas atomized powders. The objective of this sub-project is to build upon these prior investigations to determine the effectiveness of using low-cost atomization techniques as a means of powder production of other alloyed and tool steels.
Principal Investigators:
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Carl Blais |
Paul Bishop |
Hani Henein |
Advanced Process Modeling and Coupled Component/Process Design
A key advantage of AM is the freedom in digital design manipulation providing enhanced part functionality through complex internal topology and material composition, without the need for specialized tooling. Metal AM has been proven to lower costs by reducing the design to fabrication cycle and through consolidating assemblies. Unfortunately these lower costs are offset by the high cost the raw materials/feedstock, and the need to use experimental trial-and-error to ensure part quality, reliability and repeatability. Currently, there are no reliable tools to correlate topology optimization and AM process constraints. Modeling and simulation of AM processes have been studied by many groups, however, there are still critical challenges that should be addressed. In particular, there is a need for the integration of reliable models with the topology optimization algorithms. These integrated models must be rapidly executed to be used within controller units for closed-loop control of AM process. The integration is challenging because of the many uncertainties associated with AM processes which all affect the melt pool dynamic significantly. Researchers of Theme 2 will develop innovative platforms/solutions to address these challenges.
Theme Leader
Steve Cockcroft, PhD, PEng
The University of British Columbia
Dept. of Materials Engineering
Email: Steve.Cockcroft@ubc.ca
AM is an innovative and potentially disruptive manufacturing technology because of its ability to fabricate geometrically complex parts at, or near final shape, and to tailor the microstructure, and hence properties spatially. In powder-bed based AM processes, heated powder particles coalesce into a thin molten track that solidifies in the wake of the beam. Currently, the energy transport characteristics of the beam/feedstock interaction are not well understood. Physics based process models are critically needed to describe the energy input profile and powder bed/substrate thermal diffusion and advection (when liquid is present) during AM processing. Quantification of these phenomena that are occurring at the meso-scale then leads the way to the prediction of the macro-thermal field, and then to the coupling of the two, as previously described. The macro-scale models can then be run over a range of conditions to produce the data necessary to develop the fast simulation models.
The data obtained from this sub-project will include quantitative knowledge of the beam/powder/melt pool interaction and the energy transport as a function of the electron beam and laser variables and state of powder.
Principal Investigators:
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Steve Cockcroft |
Mary Wells |
A key question in AM is the interrelationship between the melt consolidation of the powder and its dependency on beam and powder bed characteristics. Understanding these phenomena hinges on describing the transport processes occurring at a meso-scale. Many of the existing models do not account for the granularity of the problem and miss fine-scale physics that are known to affect the melt track characteristics. Knowledge in this area is still in its infancy and lacking a comprehensive understanding of the complex interaction between AM process parameters, the powder, and the previously consolidated layer in order that the fabricated microstructure can be predicted. The objective of this sub-project is to develop a meso-scale model to predict melt consolidation behaviour for a range of AM process parameters.
Principal Investigators:
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Steve Cockcroft |
AM models based on the finite element method have predominantly been used to describe phenomena at micro-to-meso scale. Drawbacks of the limited scale of these simulations are: 1) not taking into account the changing thermos-physical characteristics of the parts as they undergo fabrication, and 2) the impossibility of predicting part deformation and residual stresses that develop on account of the global force equilibrium considerations. Simulating the thermal field evolution will be investigated in this project. A key outcome of this sub-project will be the ability to conduct detailed thermal response in part level and possibly to optimize process parameters. The objective of this subproject is to develop macro-scale 3D model to simulate the thermal field evolution for AM processes.
Principal Investigators:
Yaoyao Fiona Zhao |
The development of comprehensive numerical multi-physics models for laser and EB-based AM processes are crucial to providing a fundamental understanding of these AM processes. Three objectives are pursued in this sub-project: a) developing a 3D thermal stress model to predict the residual stress and deformation generated in EB-DED process at macro-scale; b) developing a 3D thermal stress model to predict the thermal stresses, inelastic strain and thermal field in EB-PBF process at the meso-scale; and; c) developing and verifying a 3D FE model to simulate cavity radiation transport in the build chamber of an ARCAM – Q20, based on build layer cross-sectional area.
Principal Investigators:
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Steve Cockcroft |
Daan Maijer |
The microstructure developed in an AM part is strongly related to the process parameters in AM processes. The interface between the modeling of AM processes and the resultant microstructure and properties of the part are critical. Thus microstructures and properties will be quantified and related directly to process conditions and model predictions that are used to generate the sample.
Principal Investigators:
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Hani Henein |
The transport-based models and the finite element-based continuum mechanics models, while offering insight into the thermo-mechanical response of AM parts, are too slow and cannot be used for process parameter dispatch, part design optimization and dynamic process control. For dynamic process control, melting and solidification occur over short time scales requiring fast sampling frequencies of radiometric and image-based data, in the order of tens-to-hundreds of kHz to ensure that the acquisition has enough temporal sensitivity to perturbations. This implies that the process model should have at least the same order of magnitude in terms of computation time to be able to react in order to respond to process perturbations. To achieve an appropriate computational speed, a surrogate reduced-order thermal model will be developed and deployed for process predictive and process feedback control. Fast process predictive thermo-mechanical models for stress field simulation have potential for being used in digital topology design optimization strategies and in predictive control approaches to reduce the design of the experiment phase needed to optimize process parameters.
Development of fast process simulations and surrogate reduced-order thermal models capable of high-speed process predictions and closed-loop control implementation is pursued in this sub-project.
Principal Investigators:
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Daan Maijer |
Thermo-mechanical modeling is beneficial for predicting residual stress and deformation of printed parts. Such models minimize trial and error experimental tests. Computational cost is the major challenging issue for process modeling. Therefore, the objectives of this project are to develop a fast predictive model and accelerate the simulation and modeling without losing much accuracy in predicting the final residual stress and deformation of the manufactured parts.
Principal Investigators:
Ehsan Toyserkani |
There are three areas of potential improvement that could be realized prior to AM fabrication: 1) part geometry compensation for in-situ deformation; 2) lattice structure design for AM processing; and 3) process parameter optimization for microstructural control. The rapid development of AM technology offers new opportunities for light-weighting using lattice structures. AM processes are able to fabricate parts with high shape complexity, material complexity and hierarchical complexity. Lattice structure design is motivated by the desire to put material only where it is needed for a specific application. From a mechanical engineering viewpoint, key advantages offered by lattice structure design are high strength accompanied by relatively low mass, and tailored specific mechanical and thermal properties. These advantages make lattice structures desirable in the aerospace, automobile and medical industries. However, most research in lattice design rarely considers the manufacturability and process capabilities of AM at the design stage. It should be emphasized that even though AM technology has alleviated many of manufacturing constraints for lattice design, it still has limitations. Different materials and different AM processes pose different manufacturing constraints on the lattice structures that can be obtained with acceptable quality. Most common constraints are the cell size, strut thickness, type and distance of overhang, and volume fraction of the lattice structure. There is a critical need to link lattice structure design with AM capabilities and constraints to ensure that the designed lattice structure can be achieved for a given process technology and meet the designed objectives.
Assessing and controlling the geometry of a manufactured part is a critical aspect of any manufacturing technology. Although AM processes allow for considerable design freedom to make complex parts, they suffer from the lack of availability of reliable geometry assessment, control and optimization methods. Most AM processes currently require several steps involving trial-and-error/tacit steps before and after printing, to obtain a part corresponding to a given requirement. In this subproject, the part build geometry assessment methods for AM will be further developed to enable the broader industrialization of the technology.
Principal Investigators:
Ahmed Qureshi |
The scope of subproject 2.3.2 is to study the mechanics of additively built lattice materials and the deviations of the expected mechanical behavior due to the presence of defects. Since these disruptions depend on the interplay between the base material and the material architecture, we explore these phenomena considering elastoplastic and hyperelastic base material properties. The objectives of the subproject are investigated in metallic and polymeric lattices:
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Metallic lattices (incorporating elastoplastic base material)
In metallic lattices, our main interest is to characterize, to quantify, and to determine the impact of manufacturing induced defects on the mechanics of metallic lattice materials built with Selective Laser Melting under manufacturing constraints of cell size, minimum strut thickness, and porosity. The statistically quantified defects serve to generate predictive models that can better capture the properties of the as-built lattice and that guide the structural design of metallic lattice materials. - Polymeric lattices (incorporating a hyperelastic base material)
We are here extending the first objective to lattices that consist of a solid polymeric phase. Defects that disrupt the mechanical performance of metallic lattices can induce new functionalities in soft lattice materials made of a polymeric solid. After selecting a given cell topology, we will uncover principles that help us understand how non-linearity can result in the emergence of complex – yet exploitable – behavior in soft systems.
The knowledge generated from this subproject will be utilized to guide the design of 3D printed components made of metals and soft polymers.
Principal Investigators:
Damiano Pasini |
Yaoyao Fiona Zhao |
The objective of this sub-project is to study the mismatch between predicted properties from the design perspective using the intralattice software and the actual results obtained upon printing of lattice struts. The key components of this project involve determination of the critical cross sectional area, followed by statistical relationship linking the design file and geometry to the printing process and the obtained properties. This will be looked for various printing angles and configuration. The effect of resulting surface defects and dimensional deviations in lattice struts on its deformation behavior would be studied.
Principal Investigators:
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Mathieu Brochu |
In-Line Monitoring/Metrology and Intelligent Process Control Strategies
Process quality and repeatability, resulting from random and environmental disturbances, are critical impediments for widespread AM adoption. A key solution to compensate for these disturbances is to use closed-loop control systems and algorithms to monitor the process, and to tune actuating signals accordingly. However, implementing this approach is challenging as there are many input physical parameters that govern metal AM processes. Furthermore, the output of the process is composed of many factors such as microstructure, hardness, geometry etc. Several non-destructive and in-situ monitoring methods have been investigated for different AM technologies with various degrees of success, however, further work is required to deal with the “big data” that can potentially be collected during AM processes, and to detect the process defects automatically based on the collected data. The researchers of Theme 3 are developing novel in- and off-line quality assurance protocols combining machine learning algorithms and sophisticated monitoring and metrology devices to establish the relationship between in-process feedback data and post-process part characterization. The end result will push AM technology toward “Certify-as-you-build” platforms.
Theme Leader
Ehsan Toyserkani, PhD, PEng
University of Waterloo
Dept. of Mechanical and Mechatronics Engineering
Email: etoyserk@uwaterloo.ca
Metal LPB-, LPF-, EWF-, PAT-AM processes have a vast number of process parameters influencing the melt pool. On the other hand, the narrow temporal opportunity to capture data, analyze, and respond to perturbations results in difficulty in implementing modeling and controls in these systems. This lack of control results in porous defects, delamination and cracking zones, and poor surface quality. Currently, most quality control measurements are conducted offline, and if any defects are discovered, an iterative design of experiment (trial-and-error) is implemented until the process outcomes are successful; this iterative approach has a high associated cost. Theme 3 researchers are developing/adopting a new generation of monitoring and control strategies. These strategies will permit relevant data collection, processing, and analysis for the design controls algorithms, quality assurance, and part certification strategies. Real-time quality control will ensure the AM process can be instantly adjusted to reduce part defects, improve efficiency and reduce costs.
Measurements of the geometry and radiation emitted by the laser-material interaction can be used to provide insight into process dynamics. This is to be accomplished by a sensor which captures both visible and IR data and processes the data to extract the critical process parameters. A model is also developed, which can be implemented with a controller to allow for reliable predictive control of LMP. The end-result of this sub-project will be a sensor monitoring system and model which can be used together for control.
Principal Investigators:
Amir Khajepour |
In-process vision data acquisition for AM typically involves a camera capturing the images of individual layers as the part is being built. Image processing examines the 2D geometry of the individual layer to detect defects. A 3D map can be constructed by combining measurements from previous layers. The process-reconstructed vision and radiometric 2D/3D architecture can be compared with the CAD digital design, as well as with part CT scan data from post-processing measurements. For LPF, a high power laser diode illumination source and high speed CMOS camera will be set up to focus on areas of interest in the process zone, where data will be extracted to refine process parameters based on potential perturbations or parameter drift. Laser illumination will enable clear vision through plasma plume and high intensity radiance without pixel saturation. In addition, for LPB and BJ, a structured lighting laser displacement system will be implemented to scan areas of interest in the fabricated layer, to extract information on powder spread defects, as well as layer fabrication defects.
Principal Investigators:
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Ahmed Qureshi |
Using eddy current sensors in the AM process is not effective due to the difficulty in distinguishing the surface noise from sub-surface defects. In this sub-project strategies will be taken into consideration to make the use of eddy current sensors for detection of sub-surface defects and features in LPF-AM systems possible. The end result of this sub-project is to deploy the novel detector in the commercially available LPF-AM systems to monitor defects in real-time.
Principal Investigators:
Behrad Khamesee |
Ehsan Toyserkani |
Porosities can occur in the metal matrix as a result of intended features or designs, or as part of process instability, resulting in porous defects. These porous defects are detrimental to part quality, as they provide a location for crack initiation and propagation, thus reducing the strength of the part. An ultrasonic sensing system is being developed as a non-contact ultrasonic interrogation technique, to detect information on the interior or surface of the solid, liquid or gaseous titanium alloy samples produced by the LPB-AM process.
Principal Investigators:
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Ehsan Toyserkani |
Due to process variability and complexity, metal AM processes suffer from low productivity and excessive variability in part performance. This limits their adoption in critical applications. In addition to the melt pool geometry, it is important to monitor thermal history to detect solidification and cooling rates. Monitoring these rates is challenging due to the fluctuating material emissivity during part build. The use of multiple real-time control sensors will create a stream of “big data” that will require special machine learning algorithms.
The behavior of electron beam processes is complex and difficult to fully capture using modeling strategies. The work in sub-project 3.2.1 will focus on the development of experimentally-driven models for understanding the melting mode transition between lack of fusion, conduction and keyhole mode. Various approaches such as statistical, multi-input-multi-output models, grey-box models, as well as physics-based models will be explored to explain the observed phenomena. The models will be refined to perform beam path optimization for reduced surface roughness and reduced pore occurrence. If sensing can be deployed, these models will be enhanced using sensor-generated data to improve on the existing assumptions with more realistic process descriptors. The optimization and control strategies will be deployed towards the production of samples with complex architectures.
Principal Investigators:
Mihaela Vlasea |
Developing controllers that manage the dimensional accuracy and desired part microstructure, while effectively increasing process speed, repeatability, and reliability is pursued in this sub-project. Furthermore, machine-learning algorithms will be developed that will be customized to enable a smart data-picking paradigm from a large stream of data forms sensors that could be about 4 GB/s.
Principal Investigators:
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Ehsan Toyserkani |
The properties of parts manufactured using powder bed metal AM processes, in terms of part strength, porous characteristics, and geometrical fidelity, are directly affected by the specifications of the powder layer. Some of the powder layer specifications include: powder size and shape distribution, layer thickness, and applied powder compaction force. The Sub-projects will investigate methods to control the compaction force, particularly the distribution of mechanical stress applied by the roller on the powder build bed that affects the powder packing density. The lack of control over compaction densities results in many issues, such as: instability in the melt pool and inconsistency in part density, porosity and mechanical strength. There are also modeling challenges in correlating the powder layer specifications to the final AM part properties. Most models assume the powder shape is perfectly spherical, powder size as being a discrete distribution, the powder is incompressible, and that particles have a constant coordination number (number of contact points with surrounding particles). These assumptions are used to simplify models and may not predict the appropriate powder packing properties. The research in this sub-project will be aligned with a technology patented by HI-AM members.
In this sub-project, a reliable model for powder compaction will be developed (via custom scripted discrete element modeling (DEM)), along with a powder compaction detection system for various powder spreading mechanisms. The model and detection system have the potential to be included in commercially available systems, including LPB and BJ. In addition, in this project, a reliable model for the pore network will be developed for future simulations of the dynamic liquid-powder interactions, along with software algorithms to control the binder droplet characteristics (via pattern recognition) for jetted materials onto powder substrates.
Principal Investigators:
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Mihaela Vlasea |
Kaan Erkorkmaz |
Powder compaction can be achieved using a variety of mechanical compaction approaches such as: changing the rotational and linear velocity of a counter-rotating roller used to disperse powders, or by using a mechanical powder layer-wise compaction arm, or a vibration-inducing piezoelectric actuator. In addition, powder compaction and disturbance can be induced further through binder-powder interactions. The effect of these methods on the AM-made parts’ quality will be investigated to simulate and quantify their effect on part densification and to test the feasibility to design a reliable closed-loop control system for compaction density testing.
Principal Investigators:
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Mihaela Vlasea |
Kaan Erkorkmaz |
Industry currently uses a limited number of path planning algorithms/protocols (e.g. raster path determination), based on proprietary algorithms that accommodates desired part characteristics. However, for parts with multi-materials and special internal architectures, such as molds and turbojet nozzles, novel adaptive path planning protocols are needed to fulfil AM promises.
The objective of this sub-project is to identify the optimal path for deposition, such that the AM takes place with the highest possible productivity, and within safe and acceptable production envelopes for the process and machine tool. The study is a scientific and technological first in understanding the trajectory optimization problem by modeling the thermal and stress defects of build material.
Principal Investigators:
Yusuf Altintas |
The adaptive path planning protocols for LPBF and DED will be formulated based on a discrete-time system and it will encompass the adaptability property using a soft computing approach, particularly neural network, dynamic models, and black-box models. This will include two steps: 1) validation and optimization of the models developed in project 3.4.1, and 2) development of computing predictive protocols/controllers. Model-based platforms developed in 3.4.1 will be validated using an experimental design approach to optimize the dimensional accuracy, maximum cooling/solidifications rates and residual stresses. The target material is Ti and steels, subject to change based on material availability.
Principal Investigators:
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Mihaela Vlasea |
Innovative AM Processes and AM-Made Products
An important advantage of using AM processes is the ability to create complex shapes that are impossible to make by conventional manufacturing methods. Examples include, but are not limited to, multi-material molds with conformal channels, functionally graded materials, cellular structures, and optimized orthopedic implants. Another advantage of AM is that its processes can also be used to repair high-value parts. Being able to repair parts rather than replacing them is forecasted to revolutionize the supply of spare parts. Large numbers of parts would no longer need to be readily available (saving costs) and delays related to part availability would be eliminated (saving time and cost). To accelerate the industrialization of AM and to update its design and application, strategic process roadmaps should be developed. One process challenge that impedes this up-take is the low speed of the AM platforms where the powder catchment efficiency is low causing major powder loss during the production. The research outcomes of Theme 4 will provide innovative new methods to address these issues and to facilitate wider adoption of metal AM processes.
Theme Leader
Mathieu Brochu, PhD, ing.
McGill University
Dept. of Materials Engineering
Email: mathieu.brochu @mcgill.ca
Currently, LPF-AM suffers from low powder catchment efficiency. This is mainly due to a large powder stream divergence angle causing a mismatch between the melt pool area and the powder-stream impinged into the melt pool area. This challenge may be addressed through the implementation of a magnetic focusing module integrated in the processing head of LPF-AM. In addition, there is an opportunity to develop a novel LPF-AM-based process, in which the initial material substrate will be levitated using magnetic fields. The basic principle for magnetic levitation is to supercool the object until it becomes a superconductor that has diamagnetic feature; then subject the object to a magnetic field for levitation. The main advantage of this technique is that the scope of manufactured parts will not be limited by the supporting platform, an appealing option for many applications in aerospace and automotive.
In this sub-project, improving the powder catchment efficiency for LPF-AM using a regulated magnetic field around the powder stream to push particles towards the centre was investigated. The numerical and experimental results suggest that the proposed methodologies/setups are not sensitive adequately to increase the powder catchment efficiency.
Principal Investigators:
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Ehsan Toyserkani |
Behrad Khamesee |
In this sub-project, two objectives are pursued in parallel: 1) embedding optical sensors in LPB-AM printed functional parts, and 2) developing look-up tables of cellular structures with feature optimization. These two objectives will eventually converge into one for the purpose of creating smart/functional lightweight prototypes. The cellular structures would be optimized to simplify embedding sensors for sensing multiple parameters such as temperature, stress, etc.
Principal Investigators:
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Ehsan Toyserkani |
In conventional LPF-AM, one face of substrate cannot be accusable due to the need for a platform or substrate to support the fabricated 3D objects during the process. The objective of this sub-project is to develop a magnetic levitation system that can be easily incorporated into LPF-AM, to enable the conductive metal nucleus to be freely levitated in space to achieve full position deposition.
Principal Investigators:
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Behrad Khamesee |
Ehsan Toyserkani |
AM is creating new possibilities for developing architectural materials, through the design and realization of new geometries of lattice structures. Per definition, architectural materials are a combination of two or more materials, or of materials and space, assembled in a way to have attributes not offered by any one material alone. The novel design and build opportunity emerging from the integration of Theme 1 outcomes will create architecture materials with different properties and material attributes. Three design variables of these materials exist: Component (choice of materials to be combined), relative volumes (volume fraction of each component) and configuration (shape and relative placing of the components).
Advancing the capabilities of using architectural materials in AM will provide a new opportunity in the field of medical structures. Medical structures would benefit from the lighter weight materials made using lattice structures to improve heat dissipation in parts such as confocal molds and heat exchangers.
The Theme 4 team will integrate the knowledge of traditional materials used in implants (SS316, TI6Al4V, CoCr) and the optimization abilities gained from Themes 1 to 3, to circumvent some of the key challenges such as: homogeneous microstructure development, distortion and defect control.
Many manufacturing processes require the careful control of surface temperatures and heat transfer rates to increase production and improve product quality. Injection molding, blow molding, die casting and extrusion are all examples of manufacturing processes that can benefit from incorporating methods of increased and balanced heat transfer within the tooling. LPB-, LPF-, EWF- and BJ-AM have a proven ability to produce highly complex cooling channels capable of reducing cooling times. Research has shown that AM fabricated conformal cooling tool inserts reduced cooling and cycle time by 19-20% over conventional machined inserts. AM also allows the fabrication of smart structures by embedding sensors into these cooling channels during fabrication.
This sub-project will utilize the knowledge generated from theme 2 to manufacture new and innovative implant structures. The results will materialize in new technology that can mimic bone tissue properties, through a tuned mixture of random and periodic variation of lattice materials that can enhance bone ingrowth. The mechanical properties of these implants will be tuned to match the variation of the elastic modulus of the surrounding bone tissue, so as to reduce concurrently bone resorption induced by stress shielding, subsidence, and bone-implant interface micromotion. The implant design will account for the impact of manufacturing defects that emerge during the AM process.
Principal Investigators:
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Damiano Pasini |
Sub-project 4.2.2 uses the background AM-based technologies developed at University of Waterloo and McGill University to develop efficient design optimization methods to improve the manufacturability of the conformal cooling channels, to optimize the location of sensors, and to improve the heat dissipation performance. Modeling approaches developed in Theme 2 are being used and integrated with existing thermal and mechanical simulation software for conformal channel design.
Principal Investigators:
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Yaoyao Fiona Zhao |
Ehsan Toyserkani |
Material degradation by corrosion and/or wear is a major problem across many industrial sectors including: transportation, mining and mineral processing, oil and gas, defence, chemical processing, etc. Developing new materials that are more resistant to corrosion and wear is a priority with extensive economic impact potential. Functionally graded materials (FGM) are materials with tailored compositions and microstructures in the as-built condition. Using FGM in AM will enable the tailoring of properties to obtain the desired part functions. Possible material gradients include selective control of physical, chemical, or mechanical properties. The novel materials are typically fabricated by direct energy deposition methods where multi-deposition nozzles for powder or feeder for wire are simultaneously used to selectively deposit a different metal or alloy at the specific location during manufacturing. The realization of functional, innovative FGM products will involve gaining a clear understanding of three steps: 1) classification of gradient, 2) determination of manufacturing strategies, and 3) global control of additive manufacturing. Theme 4 researchers will integrate the research outcomes of subproject 1.2.2 into the manufacturing of FGM parts, including metal matrix composites (MMCs), with applications in the direct manufacturing of wear-resistant parts, or the repair/cladding of worn and/or corroded parts.
The resource sector (oil/gas and mining) would gain critical benefits from the use of FGM printed AM structures. The use of a WC reinforced Nickel based matrix as a coating has already enhanced the wear resistance of digging tools but a tailored compositional transition from the base material would further increase their in-service lifespan. FGM use requires knowledge of developing strategies for working with multi-hopper in AM processes. In this sub-project, strategies for AM of FGM parts using AM-plasma transfer arc using two hoppers will be developed.
Principal Investigators:
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Hani Henein |
Part cooling time after plastic injection counts for almost 44% of cycle time. Reducing cooling time would substantially increase productivity. LPF-AM has the capability of producing FGM molds composed of Cu-embedded in a tool steel matrix to reduce the cooling time. The Cu acts as a heat sink, providing fast cooling to substantially reduce cycle time. The tool steel on the molding active surface provides the mechanical strength and wear resistance required for the tool.
Principal Investigators:
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Kevin Plucknett |
Part repair using AM can be achieved with considerable cost savings in comparison to complete part replacement. Consequently, there is a significant drive towards developing and utilizing laser-based and E-beam based AM technologies in repair. Laser powder deposition will allow site-specific repair or surface modification, such that minimal finish machining is required after cladding. The use of AM for repairing parts is a new concept providing an opportunity to develop novel approaches for a variety of metallic alloy substrates (i.e. for materials based on Al, Fe, Ni, or Ti). The use of FGM would allow for a range of subtle compositional changes (i.e. to enhance corrosion resistance) through to composite structures containing additional components (i.e. hard ceramic phases such as TiC, TiB2, SiC, WC, etc.) The team is investigating the new alloys developed in Project 1.1 as potential new options as a filler material for the repair of parts with matching compositions.
The objective of this sub-project is to evaluate the repair interface, conducted by LPF-AM, and its effect on the service environment: 1) the reparability and deposition compatibility of the substrate, 2) the deposited material mechanical performance, and 3) the wear and corrosion response.
Principal Investigators:
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Kevin Plucknett |
This sub-project will utilize the EBWF-AM process to investigate the reparability of high temperature materials that have a high affinity with gaseous contaminant, such as some titanium alloys and superalloys.
Principal Investigators:
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Mathieu Brochu |
This subproject will use plasma transfer arc AM with the same procedures explained in 4.4.1 and 4.4.2.
REPAIR PROCESS
This project provides a strategy for scan-assisted repair by additive manufacturing. A small interface gathering a number of algorithms is used for identification of damages and repair by subtractive and additive manufacturing.
MATERIALS
This project also addresses the application of Fused Filament Fabrication (FFF) to Metal Matrix Composites. The FFF is one of the AM processes that can benefit from the strategy being developed in the summary above. FFF is gaining interest in Additive Manufacturing of components. While it has largely grown based on the use of polymers, the feasibility to incorporate other classes of materials is an attractive option. When metals are incorporated into the polymer, FFF provides the opportunity to retain the fine structure of the rapidly solidified powder. In order to take full advantage of FFF for application in the resource sector, both metallic and ceramic powders will be mixed into a polymer filament that will subsequently be used for 3D printing.
Principal Investigators:
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Hani Henein |