Nothing beats seeing a product we were part of hit the shelves, except seeing that product become a success. The Globalstar Spot3 project was even better because we were able to apply the full range of PADT’s capabilities to contribute to this success: Product Development, Simulation, and 3D Printing.
In “Fast-Forwarding Next-Generation Product Development” PADT’s Mike Landis outlines how we applied leading edge technology and a proven process to quickly develop Globalstar’s next-generation design, not just for performance but also for manufactuing. The article is a great overview of the service PADT has to offer and how we partner with customers to make their innovation work.
If you have a new generation of an existing product line, or a brand new product under development and want a better product to market faster, PADT is here to help with our design, simulation, 3D Printing, test, and manufacturing expertise. Just give us a call at 1-800-293-PADT or email firstname.lastname@example.org.
As the worldwide demand for energy continues to grow every year, energy systems simulation is becoming an indispensable tool for improving the way energy is produced and consumed. At the same time, concerns about climate change are leading to stricter emissions regulations and calls for sustainable design in all future energy systems. Clearly, breakthroughs in energy innovation are needed to meet these formidable challenges.
Join PADT in exploring the impact of breakthrough energy innovation as well as how ANSYS simulation solutions can be used to help combat the challenges that this area presents.
This campaign covers five main topics:
Machine & Fuel Efficiency
Information on each topic will be released over the course of the next few months as the webinars take place.
The campaign will consist of a series of webinars explaining the applications of ANSYS simulations software with regards to each topic, along with additional downloadable content.
Sign Up Now to receive updates regarding the campaign, including additional information on each subject, registration forms to each webinar and more.
More information regarding the campaign in general can be found Here.
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.
In the Age of IoT, electronics continue to get smaller, faster, more power efficient, and are integrated into everything around us. Increasingly, companies are incorporating simulation early in the product development process, when the cost of design changes are at their lowest, to meet the challenges presented by Signal Integrity. For this to be effective, simulation tools need to be easy-to-use, compatible with existing work flows, and accurate, all while delivering meaningful results quickly.
If you or your company are designing or using electronics that are:
Critical to revenue, performance, or safety
Getting smaller, faster, or more efficient
Communicating with Gbps data rates
Using several or new connectors
Using long cables or backplanes
Then you could be a victim of Signal Integrity failure!
Join us September 7th, 2016 at 1 pm Pacific Time for this free webinar to discover how ANSYS is delivering intuitive Signal Integrity analysis solutions that can easily import ECAD geometry to compute SYZ parameters, inter-trace coupling, or impedance variations. Learn how ANSYS can help identify Signal Integrity problems and optimize potential solutions faster and cheaper than prototyping multiple iterations.
This webinar will introduce:
What products ANSYS provides for Signal Integrity problems
How these products can integrate into existing design workflows
And how easy these products are to use, even for novice operators
Followed by a Q&A session!
Click Here to register for this event and be sure to add it to your calendar to receive reminders.
Can’t make it? We suggest you register regardless, as our webinars are recorded and sent out along with a PDF of the presentation to our contacts within 24 hours of the presentation finishing.
I am writing this post after visiting the 27th SFF Symposium, a 3-day Additive Manufacturing (AM) conference held annually at the University of Texas at Austin. The SFF Symposium stands apart from other 3D printing conferences held in the US (such as AMUG, RAPID and Inside3D) in the fact that about 90% of the attendees and presenters are from academia. This year had 339 talks in 8 concurrent tracks and 54 posters, with an estimated 470 attendees from 20 countries – an overall 50% increase over the past year.
As one would expect from a predominantly academic conference, the talks were deeper in their content and tracks were more specialized. The track I presented in (Lattice Structures) had a total of 15 talks – 300 minutes of lattice talk, which pretty much made the conference for me!
In this post, I wish to summarize the research landscape in AM cellular solids at a high level: this classification dawned on me as I was listening to the talks over two days and taking in all the different work going on across several universities. My attempt in this post is to wrap my arms around the big picture and show how all these elements are needed to make cellular solids a routine design feature in production AM parts.
Classification of Cellular Solids
First, I feel the need to clarify a technicality that bothered me a wee bit at the conference: I prefer the term “cellular solids” to “lattices” since it is more inclusive of honeycomb and all foam-like structures, following Gibson and Ashby’s 1997 seminal text of the same name. Lattices are generally associated with “open-cell foam” type structures only – but there is a lot of room for honeycomb structures and close-cell foams, each having different advantages and behaviors, which get excluded when we use the term “lattice”.
The AM Cellular Solids Research Landscape
The 15 papers at the symposium, and indeed all my prior literature reviews and conference visits, suggested to me that all of the work in this space falls into one or more of four categories shown in Figure 2. For each of the four categories (design, analysis, manufacturing & implementation), I have listed below the current list of capabilities (not comprehensive), many of which were discussed in the talks at SFF. Further down I list the current challenges from my point of view, based on what I have learned studying this area over the past year.
Over the coming weeks I plan to publish a post with more detail on each of the four areas above, summarizing the commercial and academic research that is ongoing (to the best of my knowledge) in each area. For now, I provide below a brief elaboration of each area and highlight some important research questions.
1. Representation (Design)
This deals with how we incorporate cellular structures into our designs for all downstream activities. This involves two aspects: the selection of the specific cellular design (honeycomb or octet truss, for example) and its implementation in the CAD framework. For the former, a key question is: what is the optimum unit cell to select relative to performance requirements, manufacturability and other constraints? The second set of challenges arises from the CAD implementation: how does one allow for rapid iteration with minimal computational expense, how do cellular structures cover the space and merge with the external skin geometry seamlessly?
2. Optimization (Analysis)
Having tools to incorporate cellular designs is not enough – the next question is how to arrange these structures for optimum performance relative to specified requirements? The two most significant challenges in this area are performing the analysis at reasonable computational expense and the development of material models that accurately represent behavior at the cellular structure level, which may be significantly different from the bulk.
3. Realization (Manufacturing)
Manufacturing cellular structures is non-trivial, primarily due to the small size of the connecting members (struts, walls). The dimensions required are often in the order of a few hundred microns and lower, which tends to push the capabilities of the AM equipment under consideration. Additionally, in most cases, the cellular structure needs to be self-supporting and specifically for powder bed fusion, must allow for removal of trapped powder after completion of the build. One way to address this is to develop a map that identifies acceptable sizes of both the connecting members and the pores they enclose. For this, we need robust ways of monitoring quality of AM cellular solids by using in-situ and Non-Destructive techniques to guard against voids and other defects.
4. Application (Implementation)
Cellular solids have a range of potential applications. The well established ones include increasing stiffness-to-weight ratios, energy absorption and thermal performance. More recent applications include improving bone integration for implants and modulating stiffness to match biological distributions of material (biomimicry), as well as a host of ideas involving meta-materials. The key questions here include how do we ensure long term reliability of cellular structures in their use condition? How do we accurately identify and validate these conditions? How do we monitor quality in the field? And how do we ensure the entire life cycle of the product is cost-effective?
I wrote this post for two reasons: I love to classify information and couldn’t help myself after 5 hours of hearing and thinking about this area. But secondly, I hope it helps give all of us working in this space context to engage and communicate more seamlessly and see how our own work fits in the bigger picture.
A lot of us have a singular passion for the overlapping zone of AM and cellular solids and I can imagine in a few years we may well have a conference, an online journal or a forum of some sort just dedicated to this field – in fact, I’d love to assess interest in such an effort or an equivalent collaborative exercise. If this idea resonates with you, please connect with me on LinkedIn and drop me a note, or send us an email (email@example.com) and cite this blog post so it finds its way to me.
Some product designs require a single physics solution, while others require multiple physics simulations. Electronics cooling, wind loading on a solar array and the thermal performance of a heat exchanger are just a few examples of applications that require multiphysics simulation. Setting up and running multiphysics simulations used to be a challenging task involving the transfer of data between multiple physics solvers. With AIM, multiphysics simulations are easy to perform. AIM provides a consistent workflow and intuitive simulation environment for fluids, structures and electromagnetics that lowers the barrier to entry for multiphysics simulations.
Join us for this webinar to discover how AIM makes it easier than ever to solve your multiphysics design challenges in a single, easy-to-use environment. Don’t settle for single physics approximation when multiphysics simulations yield more accurate results with AIM.
This webinar will be held on September 1st from 1:00 – 2:00 pm PT
Innovative companies are using simulation early in the product development process to improve and optimize product designs. Companies deploying up-front simulation to their product design teams require simulation software that is easy-to-use, provides accurate simulation results and allows customization to enforce best practices. Such design engineering simulation software allows teams to develop and refine design ideas early in the design cycle when the cost of making design changes is still low.
Join us for this webinar to discover how AIM’s intuitive simulation workflow delivers high levels of automation and allows customization to automate engineering simulation best practice. Learn how AIM’s custom applications enable every engineer in your organization to benefit from simulation insights.
This webinar will be held on August 24th from 1:00 pm – 2:00 pm PT
Product design engineers are increasingly under pressure to complete product designs faster so innovative products can reach the market sooner. Performing up-front simulation as part of the product development process can accelerate designing optimized products and reduce costly physical prototypes. To successfully implement simulation early in the product development process, simulation software must be easy-to-use and cover all the necessary physics that impact product designs.
Join us for this webinar to discover how AIM delivers unparalleled ease-of-use for simulation driven product development, and learn how design engineers can benefit from using simulation early in the product development process.
This webinar will be held on August 10th from 1:00 pm – 2:00 pm PT
Have you ever looked at the mechanical properties in an FDM material datasheet (one example shown below for Stratasys ULTEM-9085) and wondered why properties were prescribed in the non-traditional manner of XZ and ZX orientation? You may also have wondered, as I did, whatever happened to the XY orientation and why its values were not reported? The short (and unfortunate) answer is you may as well ignore the numbers in the datasheet. The longer answer follows in this blog post.
Mesostructure has a First Order Effect on FDM Properties
In the context of FDM, mesostructure is the term used to describe structural detail at the level of individual filaments. And as we show below, it is the most dominant effect in properties.
Consider this simple experiment we did a few months ago: we re-created the geometry used in the tensile test specimens reported in the datasheets and printed them on our Fortus 400mc 3D printer with ULTEM-9085. While we kept layer thickness identical throughout the experiment (0.010″), we modified the number of contours: from the default 1-contour to 10-contours, in 4 steps shown in the curves below. We used a 0.020″ value for both contour and raster widths. Each of these samples was tested mechanically on an INSTRON 8801 under tension at a displacement rate of 5mm/min.
As the figure below shows, the identical geometry had significantly different load-displacement response – as the number of contours grew, the sample grew stiffer. The calculated modulii were in the range of 180-240 kpsi. These values are lower than those reported in datasheets, but closer to published values in work done by Bagsik et al (211-303 kpsi); datasheets do not specify the meso-structure used to construct the part (number of contours, contour and raster widths etc.). Further, it is possible to modify process parameters to optimize for a certain outcome: for example, as suggested by the graph below, an all-contour design is likely to have the highest stiffness when loaded in tension.
Can we Borrow Ideas from Micromechanics Theory?
The above result is not surprising – the more interesting question is, could we have predicted it? While this is not a composite material, I wondered if I could, in my model, separate the contours that run along the boundary from the raster, and identify each as it’s own “material” with unique properties (Er and Ec). Doing this allows us to apply the Rule of Mixtures and derive an effective property. For the figure below, the effective modulus Eeff becomes:
Eeff = f.Ec + (1-f).Er
where f represents the cross-sectional area fraction of the contours.
With four data points in the curve above, I was able to use two of those data points to solve the above equation simultaneously and derive Er and Ec as follows:
Er = 182596 psi Ec = 305776 psi
Now the question became: how predictive are these values of experimentally observed stiffness for other combinations of raster and contours? In a preliminary evaluation for two other cases, the results look promising.
So What About the Orientation in Datasheets?
Below is a typical image showing the different orientations data are typically attributed to. From our micromechanics argument above, the orientation is not the correct way to look at this data. The more pertinent question is: what is the mesostructure of the load-bearing cross-section? And the answer to the question I posed at the start, as to why the XY values are not typically reported, is apparent if you look at the image below closely and imagine the XZ and XY samples being tested under tension. You will see that from the perspective of the load-bearing cross-section, XY and XZ effectively have the similar (not the same) mesostructure at the load-bearing cross-sectional area, but with a different distribution of contours and rasters – these are NOT different orientations in the conventional X-Y-Z sense that we as users of 3D printers are familiar with.
The point of this preliminary work is not to propose a new way to model FDM structures using the Rule of Mixtures, but to emphasize the significance of the role of the mesostructure on mechanical properties. FDM mesostructure determines properties, and is not just an annoying second order effect. While property numbers from datasheets may serve as useful insights for qualitative, comparative purposes, the numbers are not extendable beyond the specific process conditions and geometry used in the testing. As such, any attempts to model FDM structure that do not account for the mesostructure are not valid, and unlikely to be accurate. To be fair to the creators of FDM datasheets, it is worth noting that the disclaimers at the bottom of these datasheets typically do inform the user that these numbers “should not be used for design specifications or quality control purposes.”
If you would like to learn more and discuss this, and other ideas in the modeling of FDM, tune in to my webinar on June 28, 2016 at 11am Eastern using the link here, or read more of my posts on this subject below. If you are reading this post after that date, drop us a line at firstname.lastname@example.org and cite this post, or connect with me directly on LinkedIn.
“Why are there so many different software solutions in Additive Manufacturing and which ones do I really need?“
This was a question I was asked at lunch during the recently concluded RAPID 3D printing conference by a manager at an aerospace company. I gave her my thoughts as I was stuffing down my very average panini, but the question lingered on long after the conference was over – several weeks later, I decided to expand on my response in this blog post.
There are over 25 software solutions available (scheduling software for service technicians, etc.) and being used for different aspects of Additive Manufacturing (AM). To answer the question above, I found it best to classify these solutions into four main categories based on their purpose, and allow sub-categories to emerge as appropriate. This classification is shown in Figure 1 below – and each of the 7 sub-categories are discussed in more detail in this post.
1. Design Modeler
You need this if you intend to create or modify designs
Most designs are created in CAD software such as SOLIDWorks, CATIA and SpaceClaim (now ANSYS SpaceClaim). These have been in use long before the more recent rise in interest in AM and most companies have access to some CAD software internally already. Wikipedia has a comparison of different CAD software that is a good starting point to get a sense of the wide range of CAD solutions out there.
2. Build Preparation
You need this if you plan on using any AM technology yourself (as opposed to sending your designs outside for manufacturing)
Once you have a CAD file, you need to ensure you get the best print possible with the printer you have available. Most equipment suppliers will provide associated software with their machines that enable this. Stand-alone software packages do exist, such as the one developed by Materialise called Magics, which is a preferred solution for Stereolithography (SLA) and metal powder bed fusion in particular – some of the features of Magics are shown in the video below.
Scanning & File Transfer
3. Geometry Repair
You need this if you deal with low-quality geometries – either from scans or since you work with customers with poor CAD generation capabilities
Geomagic Design X is arguably the industry’s most comprehensive reverse engineering software which combines history-based CAD with 3D scan data processing so you can create feature-based, editable solid models compatible with your existing CAD software. If you are using ANSYS, their SpaceClaim has a powerful repair solution as well, as demonstrated in the video below.
Improving Performance Through Analysis
4. Topology Optimization
You need this if you stand to benefit from designing towards a specific objective like reducing mass, increasing stiffness etc. such as the control-arm shown in Figure 2
Of all the ways design freedom can be meaningfully exploited, topology optimization is arguably the most promising. The ability to now bring analysis up-front in the design cycle and design towards a certain objective (such as maximizing stiffness-to-weight) is compelling, particularly for high performance, material usage sensitive applications like aerospace. The most visible commercial solutions in the AM space come from Altair: with their Optistruct solution (for advanced users) and SolidThinking Inspire (which is a more user-friendly solution that uses Altair’s solver). ANSYS and Autodesk 360 Inventor also offer optimization solutions. A complete list, including freeware, can be availed of at this link.
5. Lattice Generation
You need this if you wish to take advantage of cellular/lattice structure properties for applications like such as lightweight structural panels, energy absorption devices, thermal insulation as well as medical applications like porous implants with optimum bone integration and stiffness and scaffolds for tissue engineering.
Broadly speaking, there are 3 different approaches that have been taken to lattice design software:
I will cover the differences between these approaches in detail in a future blog post. A general guideline is that the generative design approach taken by Autodesk’s Within is well suited to medical applications, while Lattice generation through topology optimization seems to be a sensible next step for those that are already performing topology optimization, as is the case with most aerospace companies pursuing AM technology. The infill/conformal approach is limiting in that it does not enable optimization of lattice structures in response to an objective function and typically involves a-priori definition of a lattice density and type which cannot then be modified locally. This is a fast evolving field – between new software and updates to existing ones, there is a new release on an almost quarterly, if not monthly basis – some recent examples are nTopology and the open source IntraLattice.
Below is a short video demo of Autodesk’s Within:
You need this if you do either topology optimization or lattice design, or need it for part performance simulation
Basic mechanical FE analysis solvers are integrated into most topology optimization and lattice generation software. For topology optimization, the digitally represented part at the end of the optimization typically has jarring surfaces that are smoothed and then need to be reanalyzed to ensure that the design changes have not shifted the part’s performance outside the required window. Beyond topology optimization & lattice design, analysis has a major role to play in simulating performance – this is also true for those seeking to compare performance between traditionally manufactured and 3D printed parts. The key challenge is the availability of valid constitutive and failure material models for AM, which needs to be sourced through independent testing, from the Senvol database or from publications.
7. Process Simulation
You need this if you would like to simulate the actual process to allow for improved part and process parameter selection, or to assess how changes in parameters influence part behavior
The real benefit for process simulation has been seen for metal AM. In this space, there are broadly speaking two approaches: simulating at the level of the part, or at the level of the powder.
Part Level Simulation: This involves either the use of stand-alone AM-specific solutions like 3DSIM and Pan Computing (acquired by Autodesk in March 2016), or the use of commercially available FE software such as ANSYS & ABAQUS. The focus of these efforts is on intelligent support design, accounting for residual stresses and part distortion, and simulating thermal gradients in the part during the process. ANSYS recently announced a new effort with the University of Pittsburgh in this regard.
Powder Level Simulation: R&D efforts in this space are led by Lawrence Livermore National Labs (LLNL) and the focus here is on fundamental understanding to explain observed defects and also to enable process optimization to accelerate new materials and process research
Part level simulation is of great interest for companies seeking to go down a production route with metal AM. In particular there is a need to predict part distortion and correct for it in the design – this distortion can be unacceptable in many geometries – one such example is shown in the Pan Computing (now Autodesk) video below.
A Note on Convergence
Some companies have ownership of more than one aspect of the 7 categories represented above, and are seeking to converge them either through enabling smooth handshakes or truly integrate them into one platform. In fact, Stratasys announced their GrabCAD solution at the RAPID conference, which aims to do some of this (minus the analysis aspects, and only limited to their printers at the moment – all of which are for polymers only). Companies like Autodesk, Dassault Systemes and ANSYS have many elements of the 7 software solutions listed above and while it is not clear what level of convergence they have in mind, all have recognized the potential for a solution that can address the AM design community’s needs. Autodesk for example, has in the past 2 years acquired Within (for lattice generation), netfabb (for build preparation) and Pan Computing (for simulation), to go with their existing design suite.
Conclusion: So what do I need again?
What you need depends primarily on what you are using AM technologies for. I recommend the following approach:
Identify which of the 4 main categories apply to you
Enumerate existing capabilities: This is a simple task of listing the software you have access to already that have capabilities described in the sub-categories
Assess gaps in software relative to meeting requirements
Develop an efficient road-map to get there: be aware that some software only make sense (or are available) for certain processes
In the end, one of the things AM enables is design freedom, and to quote the novelist Toni Morrison: “Freedom is not having no responsibilities; it is choosing the ones you want.” AT PADT, we work with design and analysis software as well as AM machines on a daily basis and would love to discuss choosing the appropriate software solutions for your needs in greater detail. Send us a note at email@example.com and cite this blog post, or contact me directly on LinkedIn. .
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.
PADT’s Ward Rand and Eric Miller were interviewed recently by Chris Gilfallan of “The Record Reporter” about what PADT does and how it impacts the local product development and intellectual property community. It ended up being a great overview and is aimed at helping the Arizona legal profession understand a bit more about what we do. If you have a subscription you can read the article here.
While much has been (justifiably) written about HP and XJet releasing new, potentially game-changing products at RAPID 2016, I wanted to write this post about some of the smaller, unexpected joys that I discovered. If I sound overly enthusiastic about the people and companies behind them, it is likely due to the fact that I wrote this on the flight back, staring out at the clouds and reflecting on what had been a wonderful trip: I own no locks, stocks or barrels in any of these companies.
1. Essentium Materials – Carbon Nanotubes and Microwaves to improve FDM mechanical properties
Over the past year, I have studied, written and made presentations about the challenges of developing models for describing Fused Deposition Modeling (FDM) given their complex and part-specific meso-structure. And while I worked on developing analytical and numerical techniques for extracting the best performance from parts in the presence of significant anisotropy, the team at Essentium has developed a process to coat FDM filaments with Carbon nanotubes and extrude them in the presence of microwave radiation. In the limited data they showed for test specimens constructed of unidirectional tool-paths, they demonstrated significant reduction in anisotropy and increase in strength for PLA. What I liked most about their work is how they are developing this solution on a foundation of understanding the contributions of both the meso-structure and inter-filament strength to overall part performance. Essentium was awarded the “RAPID Innovations award”, first among the 27 exhibitors that competed and are, in my opinion, addressing an important problem that is holding back greater expansion of FDM as a process in the production space.
2. Hyrel 3D – Maker meets Researcher meets The-Kid-in-All-of-Us
I only heard of Hyrel 3D a few days prior to RAPID, but neglected to verify if they were exhibiting at RAPID and was pleasantly surprised to see them there. Consider the options this 3D printer has that you would be hard pressed to find in several 3D printers combined: variable extrusion head temperatures (room temp to 450 C), sterile head options for biological materials, a 6W laser (yes, a laser), spindle tools, quad head dispensing with individual flow control and UV crosslinking options. Read that again slowly. This is true multiple degree-of-freedom material manipulation. What makes their products even more compelling is the direct involvement of the team and the community they are building up over time, particularly in academia, across the world, and the passion with which they engage their technology and its users.
3. Technic-Print: New Chemistry for Improved FDM Support Removal
If you manufacture FDM parts with soluble supports, keep reading. A chemist at Technic Inc. has developed a new solution that is claimed to be 400% faster than the current Sodium-Hydroxide solution we use to dissolve parts. Additionally, the solution is cited as being cleaner on the tank, leaving no residue, has a color indicator that changes the solution’s color from blue to clear. And finally, through an additional agent, the dissolved support material can be reclaimed as a clump and removed from the solution, leaving behind a solution that has a pH less than 9. Since PADT manufactures one of the most popular machines that are used to dissolve these supports that unbeknown to us, were used in the testing and development of the new solution, we had an enriching conversation with the lead chemist behind the solution. I was left wondering about the fundamental chemistry behind color changing, dissolution rates for supports and the reclaiming of support – and how these different features were optimized together to develop a usable end-solution.
4. Project Pan: Computationally Efficient Metal Powder Bed Fusion Simulation I presented a literature review at AMUG (another Additive Manufacturing conference) last month, on the simulation of the laser-based powder bed fusion. At the time, I thought I had captured all the key players between the work being done at Lawrence Livermore National Labs by Wayne King’s group, the work of Brent Stucker at 3DSIM and the many academics using mostly commercially available software (mostly ANSYS) to simulate this problem. I learned at RAPID that I had neglected to include a company called “Project Pan” in my review. This team emerged from Prof. Pan Michaleris’s academic work. In 2012, he started a company that was acquired by Autodesk two months ago. In a series of 3 presentations at RAPID, Pan’s team demonstrated their simulation techniques (at a very high level) along with experimental validation work they had done with GE, Honeywell and others through America Makes and other efforts. What was most impressive about their work was both the speed of their computations and the fact that this team actually had complex part experimental validations to back up their simulation work. What most users of the powder bed fusion need is information on temperatures, stresses and distortion – and within time frames of a few hours ideally. It seems to me that Pan and his team took an approach that delivers exactly that information and little else using different numerical methods listed on their site (novel Hex8 elements, an element activation method and intelligent mesh refinement) that were likely developed by Pan over the years in his academic career and found the perfect application, first in welding simulation and then in the powder bed fusion process. With the recent Autodesk acquisition, it will be interesting to see how this rolls out commercially. Details of some of the numerical techniques used in the code can be found at their website, along with a list of related publications.
5. FDA Participation: Regulating through education and partnership
On a different note from the above, I was pleasantly surprised by the presence of the FDA, represented by Matthew Di Prima, PhD. He taught part of a workshop I attended on the first day, took the time to talk to everyone who had an interest and also gave a talk of his own in the conference sessions, describing the details of the recently released draft guidance from the FDA on 3D printing in medical applications. It was good to connect the regulatory agency to a person who clearly has the passion, knowledge, intelligence and commitment to make a difference in the Additive Manufacturing medical community. Yes, the barriers to entry in this space are high (ISO certifications, QSR systems, 510(k) & Pre-Market Approvals) but it seems clear that the FDA, at least as represented by Dr. Di Prima, are doing their best to be a transparent and willing partner.
What really makes a trip to a conference like RAPID worth it are the new ideas, connections and possibilities you come away with that you may not stumble upon during your day job – and on that account, RAPID 2016 did not disappoint. As a line in one of my favorite song’s goes:
“We’ll never know, unless we grow.
There’s too much world outside the door.”
– Fran Healy (Travis, “Turn”).
PADT talks a lot about synergy as a key strength and a key element of the value we provide to our customers. Our three departments, Manufacturing, Services, and Sales, are in constant communication, always leveraging one another’s expertise to solve problems. Strong internal relationships — a consequence of being under the same roof — precipitate easy and abundant information and resource sharing. Communication, paradigm, alignment, synergy: clear as day.
But what does any of that mean?
When a PADT product development customer meets us for the first time, he or she may be shown a slide that looks like this:
Strong bilateral communication among the Product Development, 3D Printing, and Analysis groups means that the project is enriched by contributions from experts across several fields, multiplying the value we add in the development process. For instance, the product will likely someday run into a sticky problem without a clear solution. PADT can attack it from multiple angles, such as design adjustment, finite element analysis (FEA) optimization, and the iterative testing of 3D printed prototypes.
Ok, but still: what does any of that mean?
A longtime customer of PADT’s product development group recently ran into an urgent problem without a clear path to a solution. Their manufacturing partner called them and said that a particular subassembly in their design will cost three times more than expected, which would raise the price of the product above the maximum the market would bear. PADT was presented with the problem: how do we reduce the subassembly cost by 66% while maintaining overall performance, and how do we confidently select a solution in under a week?
PADT’s three engineering groups jumped in to help.
The Product Development group held a brainstorming session and came out with two adjustments to bring overall cost down. First, the subassembly of three bonded unique steel parts would be replaced by a single injection molded plastic part. This change reduces component cost to within the target, but also significantly reduces the final assembly’s structural integrity.
Secondly, a plastic stiffener truss was added between components to mitigate the reduction in overall stiffness. This change adds a little assembly cost, but also significantly increases the final assembly’s structural integrity, which had been weakened by the first change.
The Analysis group conducted a series of FEA simulations, first to determine the increased bending under load and second to select a material to balance the conflicting requirements for stiffness, strength, and cost. After multiple simulation iterations, it was determined that Product Development had selected a permissible path forward and that a glass-filled polypropylene provides the best combination of the three parameters.
The 3D Printing group then printed the new design for qualitative “look and feel” testing and quantitative force/deflection study. The group was able to closely match the properties of the selected material from their collection of printable filaments and top-shelf industrial printers, reproducing even the fine details — subtle fillets, radii — that boost strength but are missed with lower quality printers. Through prototype tests, it was determined that Analysis selected an appropriate material and Product Development selected an appropriate design.
In the end, PADT was able to confidently select a solution to the customer’s unique cost problem in under a week. Thanks to the synergy of three groups — Product Development, Analysis, and 3D Printing — the customer was able to stay on schedule and enter the market at a relevant price.
So how can PADT help my product?
PADT’s system for delivering services is a textbook example of synergy in action, and it represents a uniquely effective solution to your company’s product problems. Whether you’re in concept design or high-volume production, PADT will tailor-make a solution that fits your budget, schedule, and technical requirements.
Give us a call at 1–800–293-PADT or email firstname.lastname@example.org.