Additive manufacturing (AM) has, for decades now, represented the promise of a future to come. A future where users can drag and drop a part, any part, into a software no matter how complex the geometry, how large or small, or of what material, and in no time a printer would serve up the user’s end vision on a platter, exactly to specifications and with desired part performance. In short, once matured, AM promised to bridge the gap between human creativity and what is physically possible to manufacture.
With the world becoming more and more digital in operation and function, and globalization intertwining resources and people across the world, AM
also has become perhaps one of the only pathways to another goal for the future — distributed manufacturing. The current standard in manufacturing is to produce components in centralized, infrastructure heavy plants and factories, and then distribute outward across the globe. This requires significant expenditure both to bring necessary resources into the facilitate for production, as well as to ship out products to customers. AM would enable part production where and when it was needed, or in some cases where the resources needed create parts are located. Such as shift in logistic approach could reduce cost, improve turnaround time to the customer, and actually facilitate improved overall sustainability for manufacturing operations by optimizing resource usage.
Seeking to make this future a reality, great minds all over the world have spent decades maturing AM hardware technology to the point it is today. Several approaches, ranging from material or binder jetting to powder bed fusion or direct energy deposition1, have been developed for robust types of operation, and huge strides have been made making methods faster, cheaper, and higher quality. So, what then is holding AM back? The answer comes down to throughput. Turnaround is still too slow for parts of sufficient quality and performance, at relevant scales, for the end user.
While hardware will undoubtedly continue to confront this challenge with further research and development, an extremely important aspect remains relatively unaddressed: software. That’s right, in many cases it is the software used to execute printing methods that may ultimately limit operational efficiency and production at relevant scales. The industry is now beginning to see million-dollar state-of-the-art machines, that cannot live up to their true potential under the pressure of true at-scale production because the underlying software is generations behind and still requires extensive human oversight and input.
This is critical issue to address, especially considering AM’s innate software - based operation is one of its most attractive attributes. Being fundamentally based on the ability of a machine to print from software uploaded specifications is what enables AM compatibility with data-driven process optimization, workflow improvement, and ultimately automation. Whereas CNC, milling, or other more traditional manufacturing operations require (often significant) human oversight, AM can be completely guided and executed by software. Of course, a natural consequence is an inherent link between the quality and efficiency of AM methods and the corresponding quality and efficiency of the software guiding operations.
Much of current AM software is based on legacy products from the traditional manufacturing space — CAD, G-code, etc. These emphasize starting with an original block of material and performing a series of surface-based operations, like extrude, cut, remove, or rotate to make the end part. Intentionally, these mimic the true to life subtractive manufacturing, and in essence ensure the design process is (loosely) tied to what is physically possible by traditional methods. In contrast, AM is fundamentally a volume driven process where creation is not limited to a subtractive operation but is tied to the substance of the part itself and the structures which compose the part2. Using the traditional template for the AM approach unintentionally limits the design and creation of AM components as it ties design to the traditional manufacturing mindset. At best this just limits, or makes difficult, the creation of intricate geometries made possible by AM, but at worst this requires significant user tweaking and input on a printer to outline what structure is needed with in the part volume and how to create it. This clash of mindset is the heart of significant inefficiency, and it is addressing this inefficiency and reinventing the software management of AM that could be the key to unlocking AM’s true potential for the market sooner rather than later.
Much as legacy software was designed from the ground-up to facilitate synergistic operation with traditional manufacturing methods, software that
supports and designs for AM could likewise be created from the ground up to mimic the AM process. Fortunately, throughout the past decade, some
startups and companies have begun to address some isolated aspects of the AM design chain. Companies such as Dyndrite, Link3D, Oqton, nTopology, and Materialise have created software which serves to create build workflows, create optimized geometries for specific applications, and other similar AM-niche functions.
While the creation of applications such as these are important steps in the right direction, the next step for AM software, and the AM industry as a
whole, is to push for the seamless integration of software as a fundamental extension of hardware to optimize for a machines true capability. Working with OEMs exploring the AM space for their current and future manufacturing needs, software developers could develop comprehensive platforms from the ground up for entire AM operations. Instead of emphasizing high flexibility, low efficiency operations for low throughput, highly customizable components, software could be tailored to collaborate with the hardware available for a given operation to optimize throughput as a function of cost, quality, and scale constraints.
The potential benefits of implementing software which can successfully collaborate with hardware is difficult to overstate. Starting at original design,
components could be built based on the structural volumes (and specifications) possible with certain machines or vice versa the hardware required could be requested based on design constraints and performance requirements. Part production could then be readily planned as a function of
available machines, load balancing work based on availability, and simultaneously print quality could be ensured by tailoring workflow with the
machines needed to provide that level of performance. The end result would be intelligent design. Not just of a specific component, but of the process to create that component for a given AM operation.
Developing this sort of software would also serve as critical milestone on the pathway to the drag and drop ability to provide distributed manufacturing, by incorporating the aspects of separate hardware systems located in separate locations across the globe and tailor operation to enable the printing of that component, in the most optimal way, at that given location given available system options and resources.
Overall, the visionary future promised by AM comes closer with each passing year thanks to relentless research and innovation by scientists, engineers, and entrepreneurs the world over. While technical hardware challenges still remain, and required tradeoffs in scale, resolution, time, and quality continued to be confronted, incredible gains are possible by considering the software that guides AM design and execution. By developing software which collaborates with hardware from the ground up to optimize based on a balance of operational capabilities and design requirements, already developed tools could operate at new levels of efficiency and throughput – saving time, money, and resources. This could unlock the market for AM and enable production scale relevant application and change the game for the industry altogether.
Founded in 2021, Phasio is a global high-tech startup specializing in the development of intelligent software to accelerate high throughput, rapid
turnaround additive manufacturing at scale. Our single-software platform enables simplified workflow management, continuous process improvement, and the ability to optimize production. By linking separate printers together into one central system, users can tailor production to enable efficient, higher volume operation and provide low-cost AM solutions for their customers. Learn more about what Phasio can do for you and get your free demo by contacting us today!
1. 7 Types of Additive Manufacturing. (2021, January 22). Applied Engineering.
2. Wong, K. Has software failed AM? (2022, May 2). Digital Engineering.