At Boeing, my group, termed BAM (Boeing Additive Manufacturing), views itself as an accelerator for product development. Our focus on additive manufacturing (AM) includes the fabrication of metal and polymer fly-away parts, and also in assisting our factory workers and research engineers in the rapid fabrication of tooling and shop aids, ergonomic factory aids and research mockups.
Our metal Additive Manufacturing timeline began in 2001, with our first Titanium-wire alloy part for the X-37A. We proceeded methodically through the years, maturing our Ti-wire technology, and simultaneously embarking on powder bed fusion technology. By 2017, we had Ti-wire parts on every 787 Dreamliner. In 2018, we produced the deployable ion engine mount for a satellite family that is part of an assembly of three other AM components. Today, we have over 70,000 AM parts flying in Boeing products in both polymer and metal.
Outside of Boeing, the industry has also made notable milestones. I think we all agree that GE Additive made a significant contribution in 2015 with its LEAP fuel nozzle. The nozzle represented a 25 percent weight reduction and consolidated 20 parts into one. Once at full-rate production there will be 36,000 of these produced annually.
More recently, GE Additive gained Federal Aviation Administration (FAA) approval for 228 metal AM turbine blade parts for their GE9X engine that will be flown on the 777X These weigh 30 percent less and contribute to a 10 percent efficiency gain in engine performance.
One might now ask, what’s next for additive manufacturing? I hear many people say that they ‘just need to find the next fuel nozzle’. The LEAP fuel nozzle is a remarkable advancement in AM and it demonstrated many of its advantages. But limiting AM to the search for the next fuel nozzle as the final destination of your AM journey is, to me, akin to the quote that’s attributed to Bill Gates (that he denies saying), “No one’s ever going to need more than 640K RAM.” Whether he said it or not, AM’s potential is much bigger than finding another fuel nozzle application.
That said, here are our opportunities and challenges in our road ahead as we continue our journey to develop, define, and realize the full benefits that AM can offer.
Engineering culture: By culture, I refer to the ‘additive-first’ mindset when engineers embark upon a new product design. The transition to this cultural mindset is necessary to achieve the full benefit of AM when inserting onto new products. As a community we cannot simply demand this cultural transformation; rather it must be earned through a deep understanding of the science of AM and through the creation of databases that demonstrate repeatable and reliable performance.
Industrializing machines for serial production: By industrialization I am not referring to the placement of robots in the factory that service the machines; rather I am referring to the fact that AM machines are largely built as one-offs, and seldom will two machines have exactly the same bill of materials. Wiring schemes and ducting schemes will be different in two of the same model machines, for example. The machine manufacturers need to industrialize how the machines are made if they are to provide uniform performance from machine to machine.
Industry 4.0: It’s very important and will allow us to drive positive outcomes in efficiency and quality by connecting our factory through sensors and weaving that data into our digital thread, providing the ability to perform data-driven analytics and provide feedback into our end-to-end value stream.
AM as a sustainability driver: AM is a sustainability driver because it uses much less material to make a part. This means in the early end of the value stream the carbon footprint is reduced because less material is mined from the earth, converted, and transported to the point of printing. Then during fabrication we recycle unused material. We’re also getting smarter about designing without support structures, and if we use them we are exploring how to recycle them. In the performance end of the value stream, AM allows for the parts to be lighter in weight and to occupy smaller volumes, enabling the vehicle to be more streamlined, requiring less fuel to operate.
Product differentiation: We begin to shift our focus from part optimization towards product differentiation. Instead of part-for-part replacements, we look at how we can use integrated systems of parts to reduce volume and assembly. We also employ AM to design in small, odd spaces in ways that conventional manufacturing cannot, and to add functionality and complexity into our designs.
Scale: With an engineering cultural change, necessary data and specifications in hand supported by industrialized machines, combined with a digitally integrated factory, we can begin to think of scale. If scale is not vertically integrated within the institution, then the supply-chain ecosystem needs to be developed, nurtured and supported, including every step from raw material, printing capabilities, post processing, testing and inspection.
What is the value added of AM? I like to look at it in three different levels.
The first is the part level. For example, our aperture cold plate is multifunctional—it’s a heat exchanger, a structural component and a waveguide. It’s a demonstration of value added with AM, consolidating many parts into one, and making something cheaper, faster, smarter and more durable. We have many examples where we have achieved different types of value with AM at Boeing. There are instances where we have reduced a program schedule by a factor of 10, and other instances when the heritage assembled part did not pass testing while the AM counterpart did. Part level value is very important, and it is not always measured in dollars.
The second type of value added by AM is product level value. At Boeing, we’re designing for AM and creating components that can’t be made traditionally. We seek to use AM to create differentiated vehicles, not just differentiated parts.
Finally, there’s program value. What I mean by that is, we may win a program award due to additive content, or because use of additive allows us to deliver faster, or make it with reduced cost. We use additive to help accelerate a design to market, which could be through additive insertions or through the prototyping, mockups, and tooling support to our engineers. Within program value lies sustainability. We believe that positive sustainability trades due to AM are key program value drivers.
AM allows you to differentiate your products by improving function and performance. It permits a strategy to adapt to a moving environment of product development that’s faster, cleaner, cheaper and smarter.
AM is a sustainability driver: In a circular manufacturing cycle, AM helps in each step.
For example, AM intrinsically uses less material than conventional subtractive manufacturing, so that the front end of the value stream results in a reduced carbon footprint (mining of raw material, conversion, and transportation to point of use). Furthermore, AM enables the design of lightweight, topologically optimized parts that are difficult or impossible to machine traditionally. Hence AM provides positive sustainability trades in both how we make the part and how the part performs. Additionally, AM allows you to print at point of use, reducing the carbon footprint resulting from transportation.
Finally, we can make products more durable with AM. We’ve proven that at Boeing in parts that were previously bolted assemblies but with additive became consolidated, monolithic parts. These parts are more durable, surviving testing where the prior bolted assemblies failed. Hence, it is expected that these types of additive parts will have a longer life and will be replaced less frequently.
When people say “scale,” often times they suggest this means purchasing 50 printers, end of story. But there’s a lot of homework we have to do first before we can scale effectively.
As I intimated previously, there are several things that need to take place before we can scale. They include:
Increase the speed and accuracy of AM machines.
Create a framework for equivalency. When we create a database for design allowables we create it on a specific machine type. When we wish to onboard a new machine that is faster, larger, and provides better quality, do we need to start creating the same database from the beginning? What is necessary is the creation of a framework for equivalency so we can leverage the data we’ve already collected, enabling the onboarding of the latest technology with agility and reduced resources.
Ensure our source material is consistent, and that quality is monitored to insure it is free of contamination.
Automate post processing if we want repeatable and reliable results. Much of the current post processing is performed with brute-force manual operations, which is not scalable and prone to inconsistencies.
Repair the disjointed AM ecosystem. (Some will say it’s not even disjointed, it’s non-existent.) We need to nurture the ecosystem of the end-to-end value stream. Produce industry specifications so that suppliers are important contributors, and address workforce challenges through training.
Create a digital infrastructure so we can collect all of our data and connect it to the digital thread. This is extremely important for scale as well as quality. At Boeing our end-to-end value stream is over 40 percent digitally connected and I estimate that by the end of 2022 we will be over 50 percent connected. We have already seen huge improvements in quality through the learnings that our digitally connected value stream provides.
Avoid bottlenecks: We need to consider the entire end-to-end value stream when we scale—and scale each aspect proportionally. If I’m going very fast in one area of production, but have a bottleneck somewhere further along the value stream, gains in speed upstream have no consequence and my production rate is now determined by the speed through the bottleneck. Hence, every aspect of the value stream needs to be scaled in proportion to the time it takes to do that particular job.
Sometimes it feels like we’re Sisyphus, pushing a boulder up a mountain, where the boulder represents our goals of repeatable and reliable printing with agility, and the mountain represents the obstacles of everything we must overcome to achieve scale.
What are those obstacles that keep us from reaching the top? We need to make sure the machines made by the OEMs are industrialized. That doesn’t mean that we have a nice robotic platform that’s moving powder from here to there. What it means to me is each machine of the same model is produced exactly the same. They have the same bill of materials the same ducting, and the same wiring. If they don’t, they’re two different machines. We have to ensure the installations are the same (e.g., how they are placed, the plumbing details of their utilities hook-ups etc). Otherwise, they’re two different machines.
Another issue that needs addressing is that of machine data access. AM is a digital process, and there’s much data driving each step and generated by each step. In order to optimize our machine performance (or troubleshoot anomalous machine behavior), we need to have access to that data. We have found that the aerospace industry has extremely tight requirements for processed material characterization, necessitating optimization of the machines. Many of the OEMs don’t allow access to the data, which is problematic for the aerospace and defense industry.
Then what do you do with the data? AM creates terabytes of data. And how do you manage that? The protocols between OEMs are different, which causes our engineers to spend a good deal of time converting the data into a format that is standardized so that our system can digest it, enabling our engineers and scientists to learn from it. It would be beneficial if the OEMs had a standardized data format.
Also consider the business case. One of the first things we should do, before we even think about creating a part or system of parts, is run a trade study. Does use of additive manufacturing make sense? Sometimes it may be better to create the part with conventional manufacturing if AM is not providing additional value. Enhancing the business is the availability of design allowables. Because without design allowables for aerospace, we certify by point design, which entails a great deal of testing, eroding our business case.
So, we have design allowables, which is a database comprised of thousands of test coupon data providing statistical significance of our processed material. Design allowables enables the certification by analysis with much less testing. Hence, design allowables provide better business cases, and give engineers the data they need to design for additive.
But what do we do when those machines from which we’ve made those design allowables become obsolete? Do we just keep using them because that’s where we have our data? I’m repeating because this is so important—we really need to create a reusable framework for equivalency so the next generation machine can be onboarded by leveraging that existing data by creating a subset of data that proves the new machine data is in family with our previously generated database. And that standardized framework doesn’t exist at the moment.
Risk reduction is very important because engineers are trained to design with reduced risk. It’s the right thing to do, however this being the case will cause them to choose to design for the manufacturing modality that has accumulated several decades worth of data. It’s our job to create the data for them with the new AM systems, not decades worth of data, but data that demonstrates repeatable and reliable material and mechanical performance under the intended operating conditions of the part.
It is the job of the AM community to do the homework to demonstrate to design engineers that we understand the underlying science of the process. We understand how to mitigate risk and have the data to prove it. That’s the only way engineers will opt to design for additive and encourage an additive-only solution with no ‘plan-b’ for traditionally fabricated designs. Having a ‘plan-b’ for traditional design means that ‘plan-a’ (the AM solution) was not optimized, and the full benefit of AM was not realized. Engineers aren’t going to risk designing for an AM-only solution until we’ve done our homework and have the data that demonstrates every single part will be the same metallurgically, mechanically and geometrically.
How do we certify? The subject of this discussion is AM for Aerospace and Defense, which has different requirements than automotive, industrial, consumer products, etc. For certification by the FAA, for example, we certify either by point design or by analysis with design allowables. With either type of certification, we have to show that we’ve picked a laser parameter that is centered in parameter space, such that if there are small variations in laser power, speed, or other machine attributes, your resulting change in parameter results in insignificant changes in material properties.
In the future we may opt to drive away from certifying with a fixed parameter because a fixed parameter for a geometrically complex part may not always drive the optimum material characteristics within the part. We may consider in the future to certify by melt pool characteristics, or other in-situ process variables that we keep constant during the build.
These are things to think about for the future that affect both the part quality as well as certification efficiency.
Every advancement that we make on our journey of additive manufacturing needs to be centered on the thought that repeatable and reliable material and mechanical characterization is the cornerstone of our progress. Many of the recent industry trends such as in-situ monitoring and IoT will help us achieve our goals.
Recent industry trends began with Internet of Things (IoT), which began with sensors embedded into everyday consumer products and then moved to industrial machines. In-situ monitoring in a powder bed machine is an example of IoT, where information about the interaction between the heat source and the powder bed flows via the internet into our database for discovery, analytics, and learning. Later came Industry 4.0, which is the interconnectedness of machines in the factory in order to help control quality and gain efficiencies.
And most recently came the digital thread—which is something we’re working on at Boeing. Connecting our end-to-end value stream data to the digital thread enables us to use that information for analytics, such as data-driven modeling, corroboration of our physics-based modeling, creation of hybrid models, employment of machine learning and artificial intelligence, and for driving the intelligence back into our value chain for optimization.
The digital-thread integration of the end-to-end value stream helps drive quality and efficiencies. It enables the use of data to generate data-driven models that provide learnings that accelerate our AM maturity. The learnings enable the deep understanding of AM that will enable the mitigation of risk. The mitigation of risk brings us back to engineering culture.
Once we demonstrate to our customers, regulators, and stakeholders that we possess the deep scientific understanding of AM that enables the mitigation of risk, AM can become a standard, viable manufacturing option that can be used to create differentiated products, not just differentiated parts. Engineers can design for AM with no ‘plan-b’, no self-limiting ‘off ramp’, so to speak, for traditional manufacturing. Such AM-only designs will enable thinner wings and lightweighted airplanes, it will enable larger payloads on satellites, it will enable longer range electrical vehicles because we’ve used additive-only solutions to create a differentiated product in a way that only additive manufacturing can do.
William Faulkner once said, “You cannot swim for new horizons until you have courage to lose sight of the shore.” Faulkner’s quote relates to AM in this way: To fully exploit the benefits of AM, you have to let go of ‘plan- b’, traditional manufacturing. The shore is conventional manufacturing, and additive-only solutions are the new horizons. We have our work to do before we are ready to lose sight of the shore but that new horizon is in sight for the near future.
Author’s note: This article is based on my keynote address at the RAPID + TCT conference in September 2021 in Chicago.
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