What do you do when you want to replace the exhaust on a 1944 P-51D Mustang warbird and you also happen to be a pioneer in additive manufacturing? You work with Concept Laser and PADT to can and print a replacement stainless steel part. In “Metal Additive Manufacturing Keeps Legend Flying” Engineering.com details the project that involved blue light scanning and 3D Printing of new metal part in modern Stainless Steel, replacing the three-piece weldment with a single part.
They also did a fantastic video about the effort:
If you would like to learn how PADT can help you reverse engineering your legacy geometry and recreate it using Additive Manufacturing, contact us.
There is something about a kid running down a hallway screaming “mom, you HAVE to see this!” #openhousegoals.
Last night was our annual event where we open up the doors of PADT with a family oriented event sharing what we engineers do. We also invited some students from high school and University to share their engineering activities. With over 250 attendees and more than one excited kid running down the hall, we can safely call it a success.
Attendies were able to see our 3D Printing demo room including dozens of real 3D printed parts, learn about engineering, explore how 3D Printing works, and check out our new metal 3D Printer. They were also able to learn about school projects like the ASU Formula SAE race car as well as a prosthetic hand project and research into cellular structures in nature from BASIS Chandler.
Oh, and there was Pizza.
Pictures speak louder than words, so here is a galary of images from the event.
Attending AeroDef this year in Fort Worth? Make sure you register to tour Concept Laser on March 6th before AeroDef! You’ll hear an update on the GE acquisition and presentations on customer applications and machine safety. Registration ends February 24th, 2017, so don’t miss this opportunity!
Speed, superior quality monitoring, and an open architecture that enables innovation – that is what makes Concept Laser’s Direct Metal Laser Melting (DMLM) technology a leader in the metal additive manufacturing industry. Come and hear about how Concept Laser is investing to bring you innovation through new products and processes that will lead to revenue-generating opportunities for your business.
The Tour is March 6th from 8:30am to 11:30pm and includes round trip transportation from the conference and more.
What you will see on the tour:
Direct Metal Laser Melting
In-situ Quality Assurance
Best-in-class safety guidelines when interacting with reactive and non-reactive materials
Metal 3D Printing is one of the more exciting areas of additive manufacturing, and we are learning a lot about how to safely operate our new system. Our very own Dhruv Bhate, PhD shared those lessons learned in this new video:
The video stresses the importance of keeping an inert environment to keep part quality and to ensure a safe operating environment. Our Concept Laser Metal 3D Printer uses high powered lasers to melt metal powder one layer at a time to build 3D Parts. This process produces soot that is highly flammable.
Dhruv shows the process we use to break the part from the machine, clean the chamber of soot, and replace the filter that captures the soot.
To learn more about PADT and how we can help you with your 3D Printing, product development, or Numerical Simulation needs, please visit www.padtinc.com
Use this link to see all of our blog posts on Metal 3D Printing
Our 10-page article on “Modeling the Mechanical Behavior of Cellular Structures for Additive Manufacturing” was published in the Winter 2016 edition of the Metal AM magazine. This article represents a high-level summary of the different challenges and approaches in addressing the modeling specific aspects of cellular structures, along with some discussion of the design, manufacturing and implementation aspects associated with AM.
Click HERE for link to the entire magazine, our article starts on page 51. Digital editions are free to download. Swing by PADT in the new year to pick up a hard copy or look for it at our table when you visit us at trade shows.
To stay in touch with the latest developments at the intersection of AM and Cellular Structures, connect with me on LinkedIn, where I typically post 1-2 blog posts every month on this, or related subjects in Additive Manufacturing.
I have always had an issue with leaving well enough alone since the day I bought my Subaru. I have altered everything from the crank pulley to the exhaust, the wheels and tires to the steering wheel. I’ve even 3D printed parts for my roof rack to increase its functionality. One of the things that I have altered multiple times has been the shift knob. It’s something that I use every time and all the time when I am driving my car, as it is equipped with a good ol’ manual transmission, a feature that is unfortunately lost on most cars in this day and age.
I have had plastic shift knobs, a solid steel spherical shift knob, a black shift knob, a white shift knob, and of course some weird factory equipment shift knob that came with the car. What I have yet to have is a 3D printed shift knob. For this project, not any old plastic will do, so with the help of Concept Laser, I’m going straight for some glorious Remanium Star CL!
One of the great things about metal 3D printing is that during the design process, I was not bound by the traditional need for a staple of design engineering, Design For Manufacturing (DFM). The metal 3D printer uses a powder bed which is drawn over the build plate and then locally melted using high-energy fiber lasers. The build plate is then lowered, another layer of powder is drawn across the plate, and melted again. This process continues until the part is complete.
The design for the knob was based off my previously owned shift knobs, mainly the 50.8 mm diameter solid steel spherical knob. I then needed to decide how best to include features that would render traditional manufacturing techniques, especially for a one-off part, cost prohibitive, if not impossible. I used ANSYS Spaceclaim Direct Modeler as my design software, as I have become very familiar with it using it daily for simulation geometry preparation and cleanup, but I digress, my initial concept can be seen below:
I was quickly informed that, while this design was possible, the amount of small features and overhangs would require support structure that would make post-processing the part very tedious. Armed with some additional pointers on creating self supporting parts that are better suited for metal 3D printing, I came up with a new concept.
This design is much less complex, while still containing features that would be difficult to machine. However, with a material density of 0.0086 g/mm^3, I would be falling just short of total weight of 1 lb, my magic number. But what about really running away from DFM like it was the plague?
There we go!!! Much better, this design iteration is spec’d to come out at 1.04 lbs, and with that, it was time to let the sparks fly!
Here it is emerging as the metal powder that has not been melted during the process is brushed away.
The competed knob then underwent a bit of post processing and the final result is amazing! I haven’t been able to stop sharing images of it with friends and running it around the office to show my co-workers. However, one thing remains to make the knob functional… it must be tapped.
In order to do this, we need a good way to hold the knob in a vise. Lucky for us here at PADT, we have the ability to quickly design and print these parts. I came up with a design that we made using our PolyJet machine so we could have multiple material durometers in a single part. The part you need below utilizes softer material around the knob to cradle it and distribute the load of the vise onto the spherical lattice surface of the knob.
We quickly found out that the Remanium material was not able to be simply tapped. We attempted to bore the hole out in order to be able to press in an insert, and also found out the High Speed Steel (HSS) was not capable of machining the hole. Carbide however does the trick, and we bored the hole out in order to press in a brass insert, which was then tapped.
Finally, the shift knob is completed and installed!
How can the mechanical behavior of cellular structures (honeycombs, foams and lattices) be modeled?
This is the second in a two-part post on the modeling aspects of 3D printed cellular structures. If you haven’t already, please read the first part here, where I detail the challenges associated with modeling 3D printed cellular structures.
The literature on the 3D printing of cellular structures is vast, and growing. While the majority of the focus in this field is on the design and process aspects, there is a significant body of work on characterizing behavior for the purposes of developing analytical material models. I have found that these approaches fall into 3 different categories depending on the level of discretization at which the property is modeled: at the level of each material point, or at the level of the connecting member or finally, at the level of the cell. At the end of this article I have compiled some of the best references I could find for each of the 3 broad approaches.
1. Continuum Modeling
The most straightforward approach is to use bulk material properties to represent what is happening to the material at the cellular level [1-4]. This approach does away with the need for any cellular level characterization and in so doing, we do not have to worry about size or contact effects described in the previous post that are artifacts of having to characterize behavior at the cellular level. However, the assumption that the connecting struts/walls in a cellular structure behave the same way the bulk material does can particularly be erroneous for AM processes that can introduce significant size specific behavior and large anisotropy. It is important to keep in mind that factors that may not be significant at a bulk level (such as surface roughness, local microstructure or dimensional tolerances) can be very significant when the connecting member is under 1 mm thick, as is often the case.
The level of error introduced by a continuum assumption is likely to vary by process: processes like Fused Deposition Modeling (FDM) are already strongly anisotropic with highly geometry-specific meso-structures and an assumption like this will generate large errors as shown in Figure 1. On the other hand, it is possible that better results may be had for powder based fusion processes used for metal alloys, especially when the connecting members are large enough and the key property being solved for is mechanical stiffness (as opposed to fracture toughness or fatigue life).
2. Cell Level Homogenization
The most common approach in the literature is the use of homogenization – representing the effective property of the cellular structure without regard to the cellular geometry itself. This approach has significantly lower computational expense associated with its implementation. Additionally, it is relatively straightforward to develop a model by fitting a power law to experimental data [5-8] as shown in the equation below, relating the effective modulus E* to the bulk material property Es and their respective densities (ρ and ρs), by solving for the constants C and n.
While a homogenization approach is useful in generating comparative, qualitative data, it has some difficulties in being used as a reliable material model in analysis & simulation. This is first and foremost since the majority of the experiments do not consider size and contact effects. Secondly, even if these were considered, the homogenization of the cells only works for the specific cell in question (e.g. octet truss or hexagonal honeycomb) – so every new cell type needs to be re-characterized. Finally, the homogenization of these cells can lose insight into how structures behave in the transition region between different volume fractions, even if each cell type is calibrated at a range of volume fractions – this is likely to be exacerbated for failure modeling.
3. Member Modeling
The third approach involves describing behavior not at each material point or at the level of the cell, but at a level in-between: the connecting member (also referred to as strut or beam). This approach has been used by researchers [9-11] including us at PADT  by invoking beam theory to first describe what is happening at the level of the member and then use that information to build up to the level of the cells.
This approach, while promising, is beset with some challenges as well: it requires experimental characterization at the cellular level, which brings in the previously mentioned challenges. Additionally, from a computational standpoint, the validation of these models typically requires a modeling of the full cellular geometry, which can be prohibitively expensive. Finally, the theory involved in representing member level detail is more complex, makes assumptions of its own (e.g. modeling the “fixed” ends) and it is not proven adequately at this point if this is justified by a significant improvement in the model’s predictability compared to the above two approaches. This approach does have one significant promise: if we are able to accurately describe behavior at the level of a member, it is a first step towards a truly shape and size independent model that can bridge with ease between say, an octet truss and an auxetic structure, or different sizes of cells, as well as the transitions between them – thus enabling true freedom to the designer and analyst. It is for this reason that we are focusing on this approach.
Continuum models are easy to implement and for relatively isotropic processes and materials such as metal fusion, may be a good approximation of stiffness and deformation behavior. We know through our own experience that these models perform very poorly when the process is anisotropic (such as FDM), even when the bulk constitutive model incorporates the anisotropy.
Homogenization at the level of the cell is an intuitive improvement and the experimental insights gained are invaluable – comparison between cell type performances, or dependencies on member thickness & cell size etc. are worthy data points. However, caution needs to be exercised when developing models from them for use in analysis (simulation), though the relative ease of their computational implementation is a very powerful argument for pursuing this line of work.
Finally, the member level approach, while beset with challenges of its own, is a promising direction forward since it attempts to address behavior at a level that incorporates process and geometric detail. The approach we have taken at PADT is in line with this approach, but specifically seeks to bridge the continuum and cell level models by using cellular structure response to extract a point-wise material property. Our preliminary work has shown promise for cells of similar sizes and ongoing work, funded by America Makes, is looking to expand this into a larger, non-empirical model that can span cell types. If this is an area of interest to you, please connect with me on LinkedIn for updates. If you have questions or comments, please email us at firstname.lastname@example.org or drop me a message on LinkedIn.
Updated (8/30/2016): Two corrections made following suggestions by Gilbert Peters: the first corrects the use of honeycomb structures in radiator grille applications as being for flow conditioning, the second corrects the use of the Maxwell stability criterion, replacing the space frame example with an octet truss.
Within the design element, the first step in implementing cellular structures in Additive Manufacturing (AM) is selecting the appropriate unit cell(s). The unit cell is selected based on the performance desired of it as well as the manufacturability of the cells. In this post, I wish to delve deeper into the different types of cellular structures and why the classification is important. This will set the stage for defining criteria for why certain unit cell designs are preferable over others, which I will attempt in future posts. This post will also explain in greater detail what a “lattice” structure, a term that is often erroneously used to describe all cellular solids, truly is.
Honeycombs are prismatic, 2-dimensional cellular designs extruded in the 3rd dimension, like the well-known hexagonal honeycomb shown in Figure 1. All cross-sections through the 3rd dimension are thus identical, making honeycombs somewhat easy to model. Though the hexagonal honeycomb is most well known, the term applies to all designs that have this prismatic property, including square and triangular honeycombs. Honeycombs have a strong anisotropy in the 3rd dimension – in fact, the modulus of regular hexagonal and triangular honeycombs is transversely isotropic – equal in all directions in the plane but very different out-of-plane.
1.2 Design Implications The 2D nature of honeycomb structures means that their use is beneficial when the environmental conditions are predictable and the honeycomb design can be oriented in such a way to extract maximum benefit. One such example is the crash structure in Figure 2 as well as a range of sandwich panels. Several automotive radiator grilles are also of a honeycomb design to condition the flow of air. In both cases, the direction of the environmental stimulus is known – in the former, the impact load, in the latter, airflow.
2. Open-Cell Foam
Freeing up the prismatic requirement on the honeycomb brings us to a fully 3-dimensionalopen-cell foam design as shown in one representation of a unit cell in Figure 3. Typically, open-cell foams are bending-dominated, distinguishing them from stretch-dominated lattices, which are discussed in more detail in a following section on lattices.
2.2 Design Implications Unlike the honeycomb, open cell foam designs are more useful when the environmental stimulus (stress, flow, heat) is not as predictable and unidirectional. The bending dominated mechanism of deformation make open-cell foams ideal for energy absorption – stretch dominated structures tend to be stiffer. As a result of this, applications that require energy absorption such as mattresses and crumple zones in complex structures. The interconnectivity of open-cell foams also makes them a candidate for applications requiring fluid flow through the structure.
3. Closed-Cell Foam
3.1 Definition As the name suggests, closed cell foams are open-cell foams with enclosed cells, such as the representation shown in Figure 6. This typically involves a membrane like structure that may be of varying thickness from the strut-like structures, though this is not necessary. Closed-cell foams arise from a lot of natural processes and are commonly found in nature. In man-made entities, they are commonly found in the food industry (bread, chocolate) and in engineering applications where the enclosed cell is filled with some fluid (like air in bubble wrap, foam for bicycle helmets and fragile packaging).
3.2 Design Implications
The primary benefit of closed cell foams is the ability to encapsulate a fluid of different properties for compressive resilience. From a structural standpoint, while the membrane is a load-bearing part of the structure under certain loads, the additional material and manufacturing burden can be hard to justify. Within the AM context, this is a key area of interest for those exploring 3D printing food products in particular but may also have value for biomimetic applications.
Lattices are in appearance very similar to open cell foams but differ in that lattice member deformation is stretch-dominated, as opposed to bending*. This is important since for the same material allocation, structures tend to be stiffer in tension and/or compression compared to bending – by contrast, bending dominated structures typically absorb more energy and are more compliant.
So the question is – when does an open cell foam become stretch dominated and therefore, a lattice? Fortunately, there is an app equation for that.
Maxwell’s Stability Criterion
Maxwell’s stability criterion involves the computation of a metric M for a lattice-like structure with b struts and j joints as follows:
In 2D structures: M = b – 2j + 3
In 3D structures: M = b – 3j + 6
Per Maxwell’s criterion, for our purposes here where the joints are locked (and not pinned), if M < 0, we get a structure that is bending dominated. If M >= 0, the structure is stretch dominated. The former constitutes an open-cell foam, the latter a lattice.
There are several approaches to establishing the appropriateness of a lattice design for a structural applications (connectivity, static and kinematic determinism etc.) and how they are applied to periodic structures and space frames. It is easy for one (including for this author) to confuse these ideas and their applicability. For the purposes of AM, Maxwell’s Stability Criterion for 3D structures is a sufficient condition for static determinancy. Further, for a periodic structure to be truly space-filling (as we need for AM applications), there is no simple rigid polyhedron that fits the bill – we need a combination of polyhedra (such as an octahedron and tetrahedron in the octet truss shown in the video below) to generate true space filling, and rigid structures. The 2001 papers by Deshpande, Ashby and Fleck illustrate these ideas in greater detail and are referenced at the end of this post.
Video: The octet truss is a classic stretch-dominated structure, with b = 36 struts, j = 14 joints and M = 0 [Attr. Lawrence Livermore National Labs]
4.2 Design Implications Lattices are the most common cellular solid studied in AM – this is primarily on account of their strong structural performance in applications where high stiffness-to-weight ratio is desired (such as aerospace), or where stiffness modulation is important (such as in medical implants). However, it is important to realize that there are other cellular representations that have a range of other benefits that lattice designs cannot provide.
Conclusion: Why this matters
It is a fair question to ask why this matters – is this all just semantics? I would like to argue that the above classification is vital since it represents the first stage of selecting a unit cell for a particular function. Generally speaking, the following guidelines apply:
Honeycomb structures for predictable, unidirectional loading or flow
Open cell foams where energy absorption and compliance is important
Closed cell foams for fluid-filled and hydrostatic applications
Lattice structures where stiffness and resistance to bending is critical
Finally, another reason it is important to retain the bigger picture on all cellular solids is it ensures that the discussion of what we can do with AM and cellular solids includes all the possibilities and is not limited to only stiffness driven lattice designs.
Note: This blog post is part of a series on “Additive Manufacturing of Cellular Solids” that I am writing over the coming year, diving deep into the fundamentals of this exciting and fast evolving topic. To ensure you get each post (~2 a month) or to give me feedback for improvement, please connect with me on LinkedIn.
 Ashby, “Materials Selection in Mechanical Design,” Fourth Edition, 2011
 Gibson & Ashby, “Cellular Solids: Structure & Properties,” Second Edition, 1997
 Gibson, Ashby & Harley, “Cellular Materials in Nature & Medicine,” First Edition, 2010
 Ashby, Evans, Fleck, Gibson, Hutchinson, Wadley, “Metal Foams: A Design Guide,” First Edition, 2000
 Deshpande, Ashby, Fleck, “Foam Topology Bending versus Stretching Dominated Architectures,” Acta Materialia 49, 2001
 Deshpande, Fleck, Ashby, “Effective properties of the octet-truss lattice material,” Journal of the Mechanics and Physics of Solids, 49, 2001
* We defer to reference  in distinguishing lattice structures as separate from foams – this is NOT the approach used in  and  where lattices are treated implicitly as a subset of open-cell foams. The distinction is useful from a structural perspective and as such is retained here.
The Committee aims to meet once a month, our second meeting occurs Monday, July 11 2016 at the ASU Polytechnic Campus and is open to anyone in Arizona that works in Additive Manufacturing and has an interest in promoting its growth statewide through collaboration. For more info, connect with me on LinkedIn or send a note to email@example.com and cite this blog post.
Joining Two of PADT’s Favorite Things: Simulation and 3D Printing
Recent advances in Additive Manufacturing (3D Printing) have removed barriers to manufacturing certain geometry because of constraints in traditional manufacturing methods. Although you can make almost any shape, how do you figure out what shape to make. Using ANSYS products you can apply topological optimization to come up with a free-form shape that best meets your needs, and that can be made with Additive Manufacturing.
A few months ago we presented some background information on how to drive the design of this type of part using ANSYS tools to a few of our customers. It was a well received so we cleaned it up a bit (no guarantee there all the typos are gone) and recorded the presentation. Here it is on YouTube
Let us know what you think and if you have any questions or comments, please contact us.
One of the more difficult things about being at the Additive Manufacturing Users Group (AMUG) is dealing with the fact that there is more to do than you can hope to accomplish in four and a half days. So I decided to focus on two themes: laser-based metal additive manufacturing (AM); and design & simulation for AM. In this post, I focus on the former and try to distill the trends I noticed across the laser-based metal AM system manufacturers that were present at the conference: Concept Laser, SLM, Renishaw, EOS and 3D Systems (listed here in the decreasing order of the time I spent at each supplier’s booth). While it is interesting to study how 5 different suppliers interpret the same technology and develop machines around it, it is not my objective to compare them here, but to extract common trends that most suppliers seem to be working on to push their machines to the next level. For the purposes of this post, I have picked the top-of-the-line machine that each supplier offers as an indication of the technology’s capabilities: they span a range of price points, so once again this is not meant to be a comparison.
As a point of observation, the 5 key trends I noticed turned out to be all really aspects of taking the technology from short run builds towards continuous production. This was not my intent, so I believe it is an accurate indication of what suppliers are prioritizing at this stage of the technology’s growth and see as providing key levers for differentiation.
1. Quality Monitoring
Most customers of AM machines that wish to use it for functional part production bemoan the lack of controls during manufacturing that allow them to assess the quality of a part and screen for excursionary behavior without requiring expensive post-processing inspection. Third party companies like Sigma Labs and Stratonics have developed platform-independent solutions that can be integrated with most metal AM systems. Metal AM suppliers themselves have developed a range of in-situ monitors that were discussed in a few presentations during AMUG, and they generally fall into the following categories:
Laser: Sensors monitor laser powder as well as temperature across the different critical components in the system
Oxygen Level: Sensors in the build chamber as well as in sieving stations track O2 levels to ensure the flushing of air with inert Argon or Nitrogen has been effective and that there are no leaks in the system
Live video: simple but useful, this allows users to get a live video stream of the top layer as it is being built and can help detection of recoater blade damage and part interaction
Meltpool: Concept Laser showed how its Meltpool monitoring system can be used to develop 2D and 3D plots that can be superimposed with the 3D CAD file to identify problematic areas – the video is also on YouTube and embedded below. SLM and EOS offer similar meltpool monitoring solutions.
Coater consistency: Concept Laser also described a monitor that captures before and after pictures to assess the consistency of the coater thickness across the build area – and this information is fed forward to adjust subsequent coater thicknesses in an intelligent manner.
Quality monitoring systems are still in their infancy with regard to what is done with the information generated, either in terms of feed forward (active) process control or even having high confidence in using the data to validate part quality. A combination of supplier development and academic and industry R&D is ongoing to get us to the next level.
2. Powder Handling
In a previous post, I touched upon the fire and explosion risks posed by metal powder handling. To lower the bar for an operator to gain access to a metal AM machine, one of the considerations is operator safety and the associated training they would need. Suppliers are constantly trying to improve the methods by which they can minimize powder handling. For a mechanical engineer, it is intriguing to see how reactive metal powders can be moved around in inert atmospheres using different strategies. The SLM 500HL uses a screw system to move the powder around in narrow tubes that stick out of the machine and direct the material to a sieving station after which they are returned to the feed area. The Renishaw RenAM 500M on the other hand uses a pneumatically driven recirculation system powered by Argon gas that is well integrated into the machine frame. Concept Laser also offers automated powder handling on the XLine 2000R, while EOS and 3DSystems do not offer this at the moment. Figure 2 below does not do justice to the level of complexity and thought that needs to go into this.
One of the limitations of automating powder handling is the ability to change materials, which is very hard to impossible to do with high enough confidence with these systems. As a result, their use is limited to cases where one machine can be dedicated to one material and efficiency gains of powder handling can be fully realized. The jury is still out on the long term performance of these systems, and I suspect this is one area that will continue to see improvements and refinements in subsequent model releases.
3. Multi-Laser Processing
In the quest for productivity improvement, one of the biggest gains comes from increasing the number and power of available lasers for manufacturing. In my previous experience with laser based systems (albeit not for this application), an additional laser can increase overall machine throughput by 50-80% (it does not double due to steps like the recoater blade movement that does not scale with the number of lasers).
The suppliers I visited at AMUG have very different approaches to this: SLM provides the widest range of customizable options for laser selection with their 500HL, which can accept either 2 or 4 lasers with power selection choices of 400W or 1000W (the 4 laser option was on display, YouTube video from the same machine in action is below) – the lasers of different powers can also be combined to have two 400W and two 1000W lasers. Concept Laser’s XLine 2000R allows for either 1 or 2 1000W lasers and their smaller, M2 machine that was showcased at AMUG has options for 1 or 2 lasers, with power selection of 200W or 400W. EOS, Renishaw and 3D Systems presently offer only single laser solutions: the EOS M 400 has one 1000W laser, Renishaw’s RenAM 500M has one 500W laser and the ProX DMP 320 from 3D Systems has one 500W laser.
There are a few considerations to be aware of when assessing a multi-laser machine: Each laser drives an increase in machine capital cost. But there is another point of note to remember when using multi-laser systems for manufacturing that centers around matching process outputs from different lasers: laser-to-laser variation can be a dominant source of overall process variation and can drive a need to calibrate, maintain and control both lasers as if they were independent machine systems. Additionally, development of a process on one particular laser power (100W, 400W, 500W, 1000W) may not scale easily to another and is something to remember when developing a long term strategy for metal AM that involves different kinds of machines, even if from the same supplier.
4. Software Integration
Renishaw spent a significant amount of time talking about their easy-to-use QuantAM software which is designed to integrate Renishaw process parameters and part processing information more tightly and allow for seamless process parameter development without needing third part software like Magics. Additive Industries announced in their presentation at AMUG that they had just signed an agreement with 3DSIM to integrate their support design software solution into their MetalFab1 machine. Software integration is likely to be an increasing trend especially around the following areas:
Improving support design methods and reducing its empirical nature and reducing the material, build time and support removal costs associated with them as well as eliminating the need for iterative builds
Increasing process options available to the user (for example for the outer skin vs the inner core, or for thick vs thin walls)
Simplifying the development of optimized process parameters for the user working on new materials
Integrating design and process optimization to increase effective part performance
In a future blog post, I will look specifically at the many design and simulation tools available around AM and how they are connected today even if not well-synergized.
5. Modular System Architectures
In a list of mostly evolutionary changes, this is the one area that struck me as being a step-change in how this technology will make an impact, even if it will be felt only by larger scale manufacturers. Concept Laser and Additive Industries are two companies that delivered presentations discussing how they were approaching the challenge of revolutionizing the technology for true production and minimizing the need for human touch. Common to both is the notion of modularity, allowing for stacking of printing, powder removal, heat treating and other stations. While Additive Industries are developing a flow resembling a series production line, Concept Laser have taken the more radical approach of having autonomous vehicles delivering the powder bed to the different stations, with travel channels for the vehicles, for the operator and for maintenance access (Figure 3). Both companies expect to have solutions out by the end of this year.
It is an interesting time to be a manufacturer of laser-based metal 3D printers, and an even more interesting time to be a consumer of this technology. The laser-material interaction fundamentals of the process are now fairly well-established. Competitors abound both in existing and emerging markets with machines that share many of the same capabilities. Alternative technologies (E-Beam melting, deposition and jetting) are making strides and may start to play in some applications currently dominated by laser-based technologies. A post early-adopter chasm may be around the corner. This will continuously drive the intense need to innovate and differentiate, and possibly also lead to a merger or two. And while most of the news coming out of conferences is justifiably centered around new process technologies (as was the case with Carbon’s CLIP and XJET’s metal nanoparticle jetting at AMUG this year), I think there is an interesting story developing in laser-based powder bed fusion and can’t wait to see what AMUG 2017 looks like!
One of the first concepts you come across in metal 3D printing is the notion of reactivity of the powder metal alloys – in this post, I investigate why some of these powder alloys are classified as reactive and others as non-reactive, and briefly touch upon the implications of this to the user of metal 3D printing tools, scoping the discussion to laser-based powder bed fusion. Ultimately, this boils down to a safety issue and I believe it is important that we, the users of these technologies, truly understand the fundamentals behind the measures we are trained to follow. If you are looking to get something chemical etched visit https://interplex.com/technology/process-capability/chemical-etching/.
Figure 1 below is indicative of the range of materials available currently for the laser-based powder bed fusion process (this selection is from Concept Laser). I have separated these into non-reactive and reactive metal alloys. The former includes steels, Inconels, bronze and CoCrW alloys. The reactive metal alloys on the other hand are Aluminum or Titanium based. The question is: what classifies them as such in the context of this process?
Reactivity in this process really pertains to the likelihood of the alloy in question serving as a fuel for a fire and/or an explosion, which are two related but distinct phenomena. To truly understand the risk associated with powder metals, we must first understand a few basic concepts.
1. Fire and Explosion Criteria
Figure 2 is a commonly used representation of the criteria that need to be met to initiate a fire (fuel, oxygen and an ignition source) and an explosion (the same three criteria for a fire, plus a dust cloud and confined space). When handling reactive metal alloy powders, it is important to remember that two of the three requirements for a fire are almost always met and the key lies in avoiding the other criterion. When not processing the powder in the machine, it is often subject to ambient oxygen content and thus all precautions are taken to prevent an ignition source (an ESD spark, for example). When the metal is being processed with a high power laser, it is done in an inert atmosphere at very low Oxygen levels. This thought process of appreciating you are one criterion away from a fire is useful, if sobering, to bear in mind when working with these powders. Well in case of fire explosion which can harm that should be resist or plan to resist. System like automatic fire alarm should be build with partnership of PH EL.
2. Terms Used to Describe Fire and Explosion Risk
There are several terms used to describe fire and explosion risk. I have picked 5 here that tie into the overall “index” I will discuss in the following section. All these parameters are in turn functions of the material in question, both with regard to its composition and its size distribution and are co-dependent. These definitions are adapted from Benson (2012) and Prodan et al. (2012).
Fire Related:These two terms describe the sensitivity of a metal dust cloud to ignition.
Ignition Temperature: This is the lowest surface temperature capable of igniting a powder or dust dispersed in the form of a dust cloud
Minimum Ignition Energy: This measures the ease of ignition of a dust cloud by electrical and electrostatic discharges.
Explosion Related: These terms describe the severity of an explosion arising from a fire once ignited.
Minimum Explosion Concentration (MEC): This is the smallest amount of dust which when suspended in air, under a set of test conditions, will initiate an explosion and propagate even after the action of the ignition source has ceased.
Maximum Explosion Pressure: This is a measure of the highest pressure that occurs during of an explosion of a flammable mixture in a closed vessel.
Maximum Rate of Pressure Rise: This is the maximum slope of the pressure/time curve during a flammable mixture explosion in a closed vessel.
3. Index of Explosibility
Having defined these terms, the question is how they can be tied together to give some sense of the hazard associated with each metal powder. I came across a 1964 US Bureau of Mines study that defined an Index of Explosibility as a measure of the hazard risk posed by powder metal alloys. The index represents both the sensitivity of the powder to ignition, and once ignited, the severity of the resulting explosion. Since this is a subjective metric, it is normalized by comparison against a “standard”, which was selected as Pittsburgh coal dust in the 1964 study. Importantly though, this normalization enables us to do qualitative comparisons between metal powders and have some sense of the hazard risk posed by them. Figure 3 is the equation reproduced from the original 1964 report and shows how this term is estimated.
The study also showed how the index was a direct function of particle size. Most powders for 3D metal printing are in the 20-100um range, and as shown in Fig. 4 for atomized Aluminum, the risk of an explosion increases with reducing particle diameter.
The authors tested a range of metals and computed the different variables, which I have compiled anew in the table in Figure 5 for the ones we are interested in for metal 3D printing. The particle sizes in the 1964 study were ones that made it through a No. 200 sieve (less than 75 microns), but did not include sub-micron particles – this makes it an appropriate comparison for metal 3D printing. It is clear from the Index of Explosibility values, as well as the Cloud Ignition Temperatures in the table below why Aluminum and Titanium are classified as reactive metals requiring special attention and care.
4. Implications for Metal 3D Printing
So what does this mean for metal 3D printing? There are three things to be aware of that are influenced by whether you are working with non-reactive or reactive alloys – I only provide a general discussion here, specific instructions will be provided to you in supplier training and manuals and must be followed.
Personal Protective Equipment (PPE): There are typically two levels of PPE: standard and extended. The standard PPE can be used for non-reactive alloy handling, but the reactive alloys require the more stringent, extended PPE. The main difference is that the extended PPE requires the use of a full bunny suit, ESD grounding straps and thermal gloves.
Need for Inert Gas Handling: Many tasks on a metal 3D printer require handling of powder (pouring the powder into the chamber, excavating a part, cleaning the chamber of powder etc.). Most of these tasks can be performed in the ambient for non-reactive metal alloys with standard PPE, but for reactive alloys these tasks must be performed in an inert atmosphere.
Local authority approvals: It is important that your local authorities including the fire marshall, are aware of the materials you are processing and review and authorize their use in your facility before you turn on the machine. Local regulations may require special procedures be implemented for preparing the room for use of reactive metal alloys, that do not apply to non-reactive metals. It is vital that the authorities are brought into the discussion early on and necessary certifications obtained, keeping in mind that reactive metal alloy use may drive additional investment in safety measures.
Safe operation of metal 3D printers requires installation of all the necessary safety equipment, extensive hands-on training and the use of checklists as memory aides. In addition to that, it helps to connect these to the fundamental reasons why these steps are important so as to gain a clearer appreciation of the source of the hazard and the nature of the risk it poses. In this article I have tried to demonstrate why reactivity in metal 3D printing matters and what the basis is for the classification of these metal alloys into reactive and non-reactive by leveraging an old 1964 study. I wish to close with a reminder that this information is meant to supplement formal training from your equipment supplier – if there is any conflict in the information presented here, please revert to your supplier’s recommendations.
Metal Additive Manufacturing, or Metal 3D Printing, is a topic that generates a lot of interest, and even more questions. So we held a webinar on February 9th, 2016 to try and answer the most common questions we encounter. It was a huge success with over 150 people logging in to watch live. But many of you could not make it so we have put the slides and a recording of the webinar out there. Just go to this link to access the information. You can have more updates to check at aboriginalbluemountains.
The presentation answered the fllowing common questions:
Who are PADT and Concept Laser?
How does laser-based metal 3D printing work?
Are there other ways to 3D print in metal and how do they compare?
What are the different process steps involved?
How “good” are 3D printed metal parts?
What materials and machines do you offer?
Who uses this technology today?
What is the value proposition of metal 3D printing for me?
What can I do after this webinar?
As always, our technical team is available to answer any additional questions you may have. Just shoot an email to firstname.lastname@example.org or give us a call at 480.813.4884.
Metal 3D printing involves a combination of complex interacting phenomena at a range of length and time scales. In this blog post, I discuss three of these that lie at the core of the laser fusion of metals: phase changes, residual stresses and solidification structure (see Figure 1). I describe each phenomenon briefly and then why understanding it matters. In future posts I will dive deeper into each one of these areas and review what work is being done to advance our understanding of them.
Phase changes describe the transition from one phase to another, as shown in Figure 2. All phases are present in the process of laser fusion of metals. Metal in powder form (solid) is heated by means of a laser beam with spot sizes on the order of tens of microns. The powder then melts to form a melt pool (liquid) and then solidifies to form a portion of a layer of the final part (solid). During this process, there is visible gas and smoke, some of which ionizes to plasma.
The transition from powder to melt pool to solid part, as shown in Figure 3, is the essence of this process and understanding this is of vital importance. For example, if the laser fluence is too high, defects such as balling or discontinuous welds are possible and for low laser fluence, a full melt may not be obtained and thus lead to voids. Selecting the right laser, material and build parameters is thus essential to optimize the size and depth of the liquid melt pool, which in turn governs the density and structure of the final part. Finally, and this is more true of high power lasers, excessive gas and plasma generation can interfere with the incident laser fluence to reduce its effectiveness.
Residual stresses are stresses that exist in a structure after it reaches equilibrium with its environment. In the laser metal fusion process, residual stresses arise due to two related mechanisms [Mercelis & Kruth, 2006]:
Thermal Gradient: A steep temperature gradient develops during laser heating, with higher temperatures on the surface driving expansion against the cooler underlying layers and thereby introducing thermal stresses that could lead to plastic deformation.
Volume Shrinkage: Shrinkage in volume in the laser metal fusion process occurs due to several reasons: shrinkage from a powder to a liquid, shrinkage as the liquid itself cools, shrinkage during phase transition from liquid to solid and final shrinkage as the solid itself cools. These shrinkage events occur to a greater extent at the top layer, and reduce as one goes to lower layers.
After cooling, these two mechanisms together have the effect of creating compressive stresses on the top layers of the part, and tensile stresses on the bottom layers as shown in Figure 4. Since parts are held down by supports, these stresses could have the effect of peeling off supports from the build plate, or breaking off the supports from the part itself as shown in Figure 4. Thus, managing residual stresses is essential to ensuring a built part stays secured on the base plate and also for minimizing the amount of supports needed. A range of strategies are employed to mitigate residual stresses including laser rastering strategies, heated build plates and post-process thermal stress-relieving.
Solidification structure refers to the material structure of the resulting part that arises due to the solidification of the metal from a molten state, as is accomplished in the laser fusion of metals. It is well known that the structure of a metal alloy strongly influences its properties and further, that solidification process history has a strong influence on this structure, as does any post processing such as a thermal exposure. The wide range of materials and processing equipment in the laser metal fusion process makes it challenging to develop a cohesive theory on the nature of structure for these metals, but one approach is to study this on four length scales as shown in Figure 5. As an example, I have summarized the current understanding of each of these structures specifically for Ti-6Al-4V, which is one of the more popular alloys used in metal additive manufacturing. Of greatest interest are the macro-, meso- and microstructure, all of which influence mechanical properties of the final part. Understanding the nature of this structure, and correlating it to measured properties is a key step in certifying these materials and structures for end-use application.
Phase changes, residual stresses and solidification structure are three areas where an understanding of the fundamentals is crucial to solve problems and explore new opportunities that can accelerate the adoption of metal additive manufacturing. Over the past decade, most of this work has been, and continues to be, experimental in nature. However, in the last few years, progress has been made in deriving this understanding through simulation, but significant challenges remain, making this an exciting area of research in additive manufacturing to watch in the coming years.