An Introduction to Additive Manufacturing
By Mark Vitale, Mark Cotteleer, and Jonathan Holdowsky
Additive manufacturing (AM) — known also as “3D printing” — has exploded into public consciousness over the past several years. Stories and perspectives seem to appear in the popular press and technology blogs on a near daily basis. Enthusiasts tout the prospect for AM to revolutionize manufacturing industries and the markets they serve, while skeptics point to the relatively limited number of applications and materials in current use. While the reality of AM likely rests somewhere between these two views, there can be little doubt that the technology is enjoying an increasing deployment across sectors — both within manufacturing and beyond — and throughout all phases of the value chain.
This article provides an introduction to AM — its technologies, processes and end-market applications. In addition, we touch upon a number of strategic challenges that companies should consider as they integrate AM into their value propositions. We also offer a strategic framework that may help companies understand how this set of technologies and processes increases flexibility and reduces the capital required to achieve greater scope and economies of scale.
What Is AM?
AM refers to a set of technologies and processes developed over more than 30 years. ASTM International, a global body recognized for the development and delivery of consensus standards within the manufacturing industry, defines AM as: “A process of joining materials to make objects from 3D [three-dimensional] model data, usually layer upon layer, as opposed to subtractive manufacturing methodologies.” In common practice, the terms “AM” and “3D printing” are used interchangeably.
Layer by Layer Additive Process
The AM process traditionally begins with the creation of a 3D model through the use of computer-aided design (CAD) software. The CAD-based 3D model typically is saved as a standard tessellation language (.STL) file, which is a triangulated representation of the model. Software then slices the data file into individual layers, which are sent as instructions to the AM device. The AM device creates the object by adding layers of material, one on top of the other, until the physical object is created.
Once the object is created, a variety of finishing activities may be required. Depending on the material used and the complexity of the product, some parts may need secondary processing, which can include sanding, filing, polishing, curing, material fill or painting. Figure 1 depicts the overall AM process.
Sophisticated 3D scanning and imaging tools are emerging as alternatives for traditional CAD programs. In addition, stylus-based and other design technologies that allow consumers to modify digital models themselves — without the need for extensive CAD experience — are expected to contribute to growth in the personal AM systems space. New formats, such as AM file format (AMF), are also being developed to address .STL’s limitations and allow for more flexible file structures.
Trade-offs Versus Traditional Manufacturing
AM creates 3D structures by adding materials layer upon layer. In contrast, traditional manufacturing practices (such as drilling or machining) are often “subtractive,” as they remove material from areas where it is not desired. AM and traditional manufacturing face different trade-offs, with each process likely to play a role in the deployment of manufacturing capabilities. Table 1 lists some of the respective advantages of AM and traditional manufacturing.
Overall, AM offers companies an array of time efficiencies and cost reductions throughout the product life cycle and supply chain, as well as greater flexibility in design and product customization than traditional manufacturing. These benefits will likely drive increasing levels of AM adoption going forward.
Processes, Technologies and Applications
Functional prototypes and end-use parts built through AM technologies have wide applications in industries such as industrial and consumer products, automotive, medical and commercial aerospace and defense. AM technologies deploy multiple different processes to address issues such as design complexity, surface finish, unit cost, speed of operations, and others. To meet diverse requirements, industrial-grade AM systems are available in the market ranging in cost from less than $10,000 to $1 million — and more.
AM technologies typically are based on one of the seven primary manufacturing processes described below in Table 2. The major AM processes and technologies can be characterized by the materials they use and the advantages and disadvantages they offer (see Table 3).
Although AM material availability is less varied when compared to traditional manufacturing approaches, AM technologies still use a range of materials, including plastics, metals, ceramics and composites, as Table 3 shows. At the present time, plastics (polymers) and metals are most commonly used in AM systems. To a lesser extent, ceramics and composites also support AM processes. Increasing use of varied materials in AM is an area of focus for future research and development.
Inherent Benefits to Increasing Penetration in the Next Decade
Overall, since its beginnings some 30 years ago, AM systems have become markedly faster, more versatile in complexity of design and variety of materials used, and less expensive. At the same time, the global AM products and services industry has seen remarkable growth — from virtually nothing in 1985 to more than $20 billion projected in 2020 according to Wohlers Associates.
Application of AM technologies is expected to grow across industries as increasing numbers of companies use the processes not just for producing prototypes, but to manufacture parts and full-scale products. Such applications will act as a particularly strong catalyst for substantive research developments in the health care and manufacturing industries. Table 4 summarizes some current applications of and potential future developments in AM in select industries. The breadth of current and likely future applications suggests that there is strong growth potential for AM going forward.
Strategic Considerations Going Forward
Some experts have heralded AM as the next great disruptive technology, similar to personal computing, giving everyone on the planet the ability to imagine, design and create custom and personalized products. As powerful and transformational as AM will likely be across an array of industries and applications for years to come, organizations should address a number of strategic challenges as they integrate AM into their value chain. We identify four such strategic challenges as especially worthy of further consideration.
AM Workforce Development
This projected growth for AM, while positive, also brings with it a significant challenge: heightened competition for a finite talent pool with the skills to use this technology. This challenge is expected to affect organizations of all sizes, from start-up to enterprise-level. The constricted supply of skilled AM labor is the result of several factors, which can be broadly categorized into the three key talent areas: recruitment and hiring, training and retention. Recruitment and hiring challenges primarily include accelerated retirement of skilled workers, a generally negative view of manufacturing among members of the Millennial Generation born from the early 1980s until the early 2000s, and an overall lack of science, technology, engineering and mathematics skills in the manufacturing market. For its part, training challenges include the relatively limited number of AM-specific educational programs offered in post-secondary and vocational institutions — no matter how much programs focused on AM are growing in number. Finally, retention of skilled AM professionals presents a challenge precisely because demand is so high for their talents given the limited number of training programs for aspiring AM workers. While many challenges face AM workforce development, organizations can use strategic workforce planning approaches to shape a robust AM workforce and build an AM talent pipeline.
AM Digital Thread
The AM process draws upon a digital design file to deposit material, layer upon layer, to construct 3D-printed parts composed of often complex geometries. Despite their promise and potential, digital designs dictating the production of end-use, 3D-printed objects have not yet moved fully into the mainstream. While AM has become a crucial part of the design process through rapid prototyping and other low-volume applications, it has not reached critical mass for applications in end-use parts and products at the enterprise level. For AM processes to scale at the industrial level, a series of complex, connected and data-driven events is needed. This series of data-driven events is commonly referred to as the digital thread: a single, seamless strand of data that stretches from the initial design concept to the finished part, constituting the information that enables the design, modeling, production, use and monitoring of an individual manufactured part.
This thread enables the flow of data throughout the manufacturing process, including design concept, modeling, build plan monitoring, quality assurance, the build process itself, and post-production monitoring and inspection. The ability to dissect, understand and apply the potentially massive amounts of data and intense computing demands within the digital thread allows users to enhance and scale their AM capabilities and manage the complexities of AM production. Yet, for all its importance, the digital thread is only as useful as it is integrated. Gaps in connectivity or stages within the design and manufacturing process where information remains siloed or isolated in separate parts of the organization prevent the manufacturer from gaining full visibility across the process. Thus, the right digital infrastructure — one that can store, access and analyze vast amounts of data and interoperate across multiple different machines and processes — is crucial to building and operating a successful digital thread.
AM Quality Assurance
While companies have widely explored AM’s potential to shrink the scale and scope necessary for manufacturing, produce items based on previously impossible designs, and alter the makeup of organizational supply chains, several significant hurdles prevent its wider adoption. One of the most important barriers is the qualification of AM-produced parts. So crucial is this issue, in fact, that many characterize quality assurance (QA) as the single biggest hurdle to widespread adoption of AM technology, particularly for metals. Put simply, many manufacturers and end users have difficulty stating with certainty that parts or products produced via 3D printing — whether all on the same printer or across geographies — will be of consistent quality, strength and reliability. Without this guarantee, many manufacturers will remain leery of AM technology, judging the risks of uncertain quality as too costly a trade-off for any gains they might realize.
QA presents a multifaceted challenge, encompassing both the scale and scope of production. Indeed, quality doesn’t just exist on one dimension; it exists on several from ensuring repeatable quality to guaranteeing quality under any environmental conditions and operational constraints to recognizing circumstances in which quality cannot be guaranteed. Each dimension should be addressed in order for parts qualification — and AM’s potential — to be more fully realized.
AM Business Model Considerations At its core, the AM process is a technical process based on data; without data, nothing gets printed. Yet the very central role that data play in the process of AM value creation inspires consideration of an array of issues that go to the core of the AM business transaction — issues that range from data ownership to data quality to protection of intellectual property rights.
In May 2016, America Makes sponsored a strategic simulation of a procurement action with 80 participants from the Department of Defense and industry. This event highlighted the many varied business model challenges that must be addressed for data to be exchanged enabling AM. For example, these challenges include: product liability, information security and suitable cost and profitability. A chartered working group is addressing these issues, with additional events planned to further explore solutions.
Closing Thoughts
There can be little doubt that the last 30 years have witnessed an unceasing advancement in AM system functionality, ease of use, cost and adoption across multiple industrial sectors. Indeed, there is an unmistakable shift in the AM landscape — from relatively common prototyping and modeling applications toward emerging applications aimed at manufacturing direct parts and end products. If the past is prologue, the role of AM technology in the manufacturing value chain will only grow in scope, scale and complexity. While there is still some time before AM realizes its full potential, companies should assess how AM can help advance their performance, growth and innovation goals.
Vitale is a specialist leader with Deloitte Consulting LLP, affiliated with the Deloitte Federal Practice. He is an adviser to public sector clients on a variety of supply chain management issues. Cotteleer is the deputy director of U.S. eminence and director of research at Deloitte Services LP, in Milwaukee, Wisconsin — affiliated with the Deloitte Center for Integrated Research. His research primarily focuses on the application of advanced technology in pursuit of operational and supply chain improvement. Holdowsky is a senior manager with Deloitte Services, affiliated with the Deloitte Center for Integrated Research, where he has managed a wide array of thought leadership initiatives on issues of strategic importance to clients within consumer and manufacturing sectors.
The authors can be contacted through mvitale@deloitte.com.
This article was originally published in the November-December edition of the “Defense AT&L” magazine on November 4, 2016.
