Skip to ContentGo to accessibility pageKeyboard shortcuts menu
OpenStax Logo

Learning Objectives

By the end of this section, students will be able to:

  • Describe the relationship between overall productivity and the balance between the different processes.
  • Understand learning curves and how they relate to AM and CM.
  • Describe how MfAM, DfAM, complexity, and quantity are interrelated.

Appreciating the economics of additive manufacturing iw core to understanding AM at all. Economics is the study of production and consumption, which helps us to decide when to use and not use AM. While there are scenarios where cost is not the primary driver such as schedule and performance, most of the time, those events ultimately have a cost penalty, or a price premium associated with them. In this section, we will address productivity and examples of what can drive productivity in AM. We will also assess the impact of throughput or volume, what goes into a business case for an AM application and the application of learning curves.

Impact of Productivity

A 3D printer is a tool just like other forms of manufacturing. If the productivity of the tool is low, its usefulness or application will ultimately be limited to items that are not cost sensitive. The Organization for Economic Co-operation and Development (OECD) defines productivity as, “a ratio between the output volume and volume of inputs.” It is the measure of how efficient inputs, such as lasers, are being used to produce a level of output, i.e. parts. If adding a second laser increases the cost of the system without increasing its output, it would decrease productivity. It will be through this lens that we will examine the impacts to productivity in some 3D printers and associated processes like metal powder production.

We will examine the productivity of the supply chain, or the process steps required to make the feedstock material through to a finished part. In doing so, we can appreciate the contributions of each step in the productivity of the process. The alternative often is to only examine the productivity of the 3D printer itself. This is an important step to understand, but it is only a step in a multi-step process where to squeeze more productivity out we must look at each process step and how it contributes to or limits the productivity of the process.

Feedstock

For metal PBF, the feedstock is a powder. Traditionally, the metal powder is made via an atomization process whereby the metal is made liquid by heating and the molten droplets fall into a tall chamber. The droplet is broken up by a variety of methods which cause many smaller droplets to form before the they cool and solidify as they fall through the chamber. The output of the process tends to be a spherical powder with a Gaussian distribution of diameters. Not all metal powders are made this way, however, and there are many variations on the concept. Atomization is done via gas atomization, water atomization or plasma atomization which vary in the medium used to break the liquid metal droplet and the raw materials to create the liquid metal. Other forms of powder production exist and have been used in powder metallurgy such as Hydride De-Hydride (HDH) and mechanical methods. In polymeric PBF, the powder can be synthesized or mechanically ground which gives very different characteristics in terms of roundness and size distribution. For our purposes in this chapter, the size distribution will be a particular focus because it drives the yield and therefor productivity that process to make feedstock.

Powder Size Distribution (PSD) is a key factor in any powder production process. This is mostly because the printing process has prescribed a fairly narrow PSD to be used in the process, while atomization produces a fairly wide PSD, regardless of which method is employed. The selection of PSD contributes to surface finish, the ability gets a desirable Packing Factor in the bed, the ability to move the powder and ultimately cost. PSD can contribute to cost in the powder price, the printer performance and the downstream processing so it is a pervasive cost driver. It is also important to point out that size is a factor in the ability to move particles with smaller particles flowing more poorly than larger, which is why roundness or sphericity is often discussed. Spherical particles flow better than non-spherical particles, so when the requirements call for freely flowing, narrow PSD and small particles; having spherical particles helps. Naturally, having fewer smaller particles also helps as well as having particles that can be moved versus having “high flowability” are important specifications. If over specified, the powder costs more than the AM process truly needs to produce a desired output.

AM Process

Within the AM process, the speed of creating a layer and melting the material is critical to productivity. The layer creation step is influenced by the speed at which the powder can be moved into place, the utilization of the powder (i.e. how many times it can be re-used) and the thickness of the layer. In PBF, for example, the scanning step where the laser (or electron beam) is melting the material and thereby creating the part is influenced by the number of lasers and the part thickness. Another nuance is the addition of lasers to create a larger bed size where more parts or larger parts can be made. All of these factors affect the productivity of the printing process. They also then impact the upstream and downstream processing as well.

Thick layer vs Machining

Printing a thicker layer could drive a larger PSD, but also require more machining due to lower resolution. If the part were going to be machined anyway, the bulk of the cost would accumulate in the setup, so machining more can be more productive when printing parts faster.

Using more of the atomization output increases the productivity of atomization and therefore should decrease cost. The thicker layer improves productivity by reducing the input costs and optimizing the downstream costs.

Print Speed

Print speed is often mentioned when discussing productivity or comparing various AM processes. It is important to take this into context as increasing the print speed alone may not increase the speed at which a part can be made and, in some cases, a faster print speed can be more expensive at the part than a slightly slower speed. It is logical to assume with expensive capital expenditure (CAPEX) items, like 3D printers, that faster would be better, but this often obfuscates several important factors. There is a difference between the print speed, the effective print speed, and then the actual cost to produce the component. We will discuss:

  • Actual print speed: Speed at which the printer makes a shape
  • Effective print speed: The resolved speed of the printing when considering the print time and required steps to make the print useful

Finally, the final part cost is the ultimate metric if the productivity of the entire process has been improved or not.

AM is a series of processes, and those processes must be matched or optimized to get the maximum benefit. Inherent in these examples has been the ability to make thicker layers. We will now look specifically at the economic considerations of thicker layers in a series of processes.

Printing thicker layers can be more difficult than it sounds. We’ve already mentioned that thicker layers can have implications on the powder input. Thicker layers will also impact the processing downstream because of the lower resolution. If the part is extremely detailed, thicker layers may not work but for larger parts or parts without a high degree of detailing, using thicker layers is a means to making more parts faster.

By increasing the layer thickness, we effectively reduce the print time. Going from 30-micron layers to 60-micron layers isn’t exactly a 50% improvement, but it is close. Thicker layers only impact the time during printing when the part is being scanned or made. Recoating time is unchanged as is the set up and cool down time.

The figure below shows the resulting calculation to examine the impact of thicker layers on part cost due to reduction in print time. Increasing the layer thickness by 50% leads to a reduction in print time and consequently part cost of approximately 20%.

A chart has fractional part cost on the y axis, and begins at 40% moving up to 100% in increments of 10. The x axis is layer thickness, and proceeds from 0 to 100 in increments of 20.  The value on the graph, indicated by a sloping line, begins at the very top at a 100% fractional part cost, when the thickness is 30.  The line curves downward as the thicknes increases, indicating that the part cost goes down with higher thickness. The line progresses through points at about 80 percent part cost when the thickness is near 60.
Figure 8.8 The calculated impact of layer thickness on part cost.

The next focus then becomes the cost of the powder because we have shifted our part cost contribution. The figure below shows the new cost implication as escalating the impact of powder as the downstream processing is more or less unchanged.

Two stacked bar graphs indicate the impact of thicker layers on cost drivers. A graph representing the baseline indicates that the feedstock makes up 14%, the printing makes up 43% and the post-process makes up 41%.  A second graph indicates thicker layer.  On this graph, the feedstock makes up 32%, the printing makes up 27%, and the post process is the same amount as the baseline graph at 41%.
Figure 8.9 Cost driver impact from a 30-micron layer baseline to a 60-micron layer, and same powder PSD and cost/kg.

The Four Lenses of AM and The Business Case

This chapter primarily deals with the financial aspects of AM. After the mechanical approach of adding the material cost plus the equipment time etc. there is the time to appreciate how the situation is improved and optimized. After all, economics is the study of what is the best use of financial resources. In order to provide a holistic view, we will divide this consideration into four domains: Machines, Materials, Digital and People. In these sections we will explore the additional possibilities and potential sources for new performance or savings.

Making a business case considers employing the right AM technology or process, with the right material which meets the design intent which requires people to have experience. AM is sufficiently diverse and within technology types there are many suppliers, brands, makes and models. The material of interest and the design are critical influences on the AM process choice. The process must meet your requirements and those requirements are both technical and financial. Meeting the technical intent but failing to provide some kind of value proposition will not lead to success.

Machines

As the printers or machines are the single biggest factor in the cost of making parts, we will consider them first. With some AM technologies, the printer comes with the peripheral equipment required to finish the part. Polymer PBF, for example, does require some post printing treatments, but due to the maturity of the technology, there are multiple suppliers and automations available. Metal AM, which is less mature by comparison, has a very immature supply chain and is somewhat scattered. We will examine two aspects of machines in a business case: batch vs. series production and operational cost.

In production, the processes must be aligned in a fashion to optimize the part flow. Through this optimization, the producer can get the most from the operational uptime of the equipment. AM can be thought of as a series of batch operations. Batch operations are where a service is performed on a group of parts at the same time, like heat treatment. Several parts are placed in a furnace, and it runs for hours. The cost of running the furnace is the same whether it is full of parts or has one part.

Clearly, we would be wise to optimize the maximum number of parts we need with the chamber size of the printer and the capacity of a furnace. When these are matched well, we can see a benefit close to series production called batch series. Batch series simply describes where two batch processes are matched so that they in effect act like series production. Series production is more closely related to the original Ford model of assembly line efficiency. The biggest difference here is that we have a printer which is good at making many different designs so keeping it running may mean making one part in the first week and a different part (same material) the next. This is most commonly referred to as “agile” manufacturing where capital equipment is capable of making many different things as they demand arises.

Calculating Costs to Increase Productivity

Let’s consider the case of a fictional company that just bought and installed the fastest binder jet printer available, at a price of $500,000. The CEO is unhappy because their costs are higher than expected, causing the profit margins to be very low. After conducting an audit to map the production process, they discovered that the printer output was fast but did not align to the next two process steps: curing and de-powdering. Consequently, the printer was making 12 parts in 12 hours (1 part per hour) but the remaining steps could only manage to process 12 parts in 16 hours (1.3 parts per hour).

The manufacturing group wanted authorization to buy an additional sintering furnace to handle the part flow. The cost of the sintering furnace was $1,000,000. However, doubling the sintering capacity would result in excess capacity in that step, which would in turn cause the furnace to operate with excess capacity. Again, the printer was purchased for $500,000. So, it was better financially to reduce (throttle) the printer output to 1.3 parts per hour to align to the other processes which were more expensive.

We can see that the role of manufacturing then has to respond to the demands of the market. While on the one hand, AM is agile and a printer can make many parts, on the other, it does not mean that the downstream processes are equivalently agile.

This brings us to the second point, operational cost. Regardless of what we are making, keeping the machines making parts is the most desirable situation. The cost of the capital equipment is high and will be amortized (spread) over a set period. Most AM equipment see the use of seven years for amortization but could be shorter for technologies that are advancing quickly. Spreading costs over seven years is desirable because it reduces the hourly burden of the equipment. Effectively, you divide the capital cost by the amortization period to get your annual cost. By dividing the annual cost by the planned operational hours gives us the $/hr. to use that machine.

The economics or operational effectiveness of AM equipment and the legacy manufacturing equipment are essentially the same. The Accounting of the depreciation of the capital equipment sets in place the hourly cost of using the equipment. The cost of using the equipment then drives how we can design the parts to balance cost and performance.

Beyond the hourly cost of the machines, the next factor is being able to deploy them such that our processes are aligned as much as possible to seek efficiency. Aligning our production so that part flow from the printer to the furnace is an example of lean manufacturing. Lean manufacturing is a methodology that focuses on minimizing waste within manufacturing systems while simultaneously maximizing productivity. In some ways, lean and agile manufacturing have opposing requirements, but both promote minimizing waste and focusing on productivity. The difference is perhaps that lean would prefer to make the same widget every day whereas agile responds to the market demand. Agile is then more difficult to predict and therefor harder to manage in manufacturing.

While we have focused on the AM machines, we have also discussed the need to align production capacity with downstream processes. This is more prevalent in metal AM than polymer AM as metals are more exposed to supply chains. The premise of our discussion and examples however are the same. It will be necessary to match the production output of the printer to the stress relief furnace to the HIP vessel to other finishing processes. The ability to do this effectively will drive a decision on what can be done in house more efficiently than outsourcing where you seek market efficiency.

Process-by-Process Discussion: Emphasis on Metals

PBF and DED with powder have the majority of cost in printing and post-processing. Materials, while perhaps more expensive than typical mill products are used so efficiently, most of what you print with you use and remove very little. The AM equipment is expensive, so the depreciation drives the overall cost. Using the printer very productively is key. A key value proposition is making very detailed, very near net shape products either from the platform up or adding on to an existing product form or repair.

Sheet lamination has minimal printing costs partly because the print speed is higher but also because the feedstock (thin gauge sheet) is expensive, and the process provides details at the expense of material wastage. The printing and machining are coupled leaving post-processing to traditional metal working and final finishes.

Binder jetting has more post-processing intensive than other processes because it needs to sinter the part in order to achieve full density. The material cost is somewhat artificially inflated because we have normalized the whole cost to 100%. Materials in BJP are typically less than laser powder bed fusion, for example.

DED with wire is very efficient at printing. It will always require a heat treat for stress relief, perhaps multiple times, and machining due to its inability to make details. Wire can be an expensive product form due to the diameter that is typically required is around 3 mm. Wire is made from bar stock and drawn or swaged down which is a lengthy process.

Direct Extrusion is quite fast and not very expensive, so for putting a lot of material down, it is very efficient. The feedstock is more like bar stock or could be waste material, so readily available and not expensive. It does require similar post-processing to DED + wire due to its inability to make near-net shapes.

Cold spray is very fast and very affordable. It does not make near net shapes so additional machining will most likely be required but the deposition rate can be tailored to produce acceptable surfaces. In some cases, a heat treatment could be necessary as well. The powder cost for cold spray can vary wildly depending on the chemistry or alloy from very inexpensive to more expensive than laser powder bed fusion, specifically in titanium.

Materials

In some instances, the material will help decide the AM process needed. In other cases, where equivalent or superior performance is all that is required, a superior material could be used with better performance and no effect on cost. In some cases, like PBF, the material cost as a percentage is low. In this instance, evaluating alternative materials means getting higher performance at negligible cost impact. Consequently, in Sheet Lamination where the material input is high, further investigation would be required.

About 13 canisters with substantial sealed lids and detailed labels are stacked in two layers against a wall.
Figure 8.10 Each of these canisters contain 10 kilograms, about 22 pounds, of powdered steel, used in the construction process with the EOS M 400 3-D metal printer. Each container is valued at $7,000. The 3-D printer also used soft aluminum or titanium powder to construct hard to find parts or design and build tools specifically for a project at PPB, MDMC. (credit: Marine Corps photo by Keith Hayes on DVIDS, Public Domain)

The choice of material can inflate the importance in processes like BJP and SL because the PSD and thin gage requirements are more expensive in titanium than they would be for example in steel which is more easily rolled to thin gage. However, this choice also drives the point in PBF and DED powder which is that titanium whilst having a high relative $/kg than other materials is <20% of the overall cost.

In consideration of the business case, it would be necessary to consider how the AM feedstock price compares to the legacy form price. This assumes material substitution is not a possibility. If the cost of AM feedstock, being a powder, wire or sheet is multiples higher than the legacy method, it begins to describe how productive the AM process is going to have to be as a first order estimation.

Aluminum Versus Titanium

The price for plate of 7000 series is ~$10/kg and aluminum machines quite easily, an order of magnitude faster than nickel or titanium. Aluminum powder can sell for $70/kg. In this initial look, the productivity of AM is going to have be quite good to provide economic value. If the raw material to final part mass ratio were 11:1 with the legacy approach, we would have 11x$10/kg or $110 of raw material which would need to be machined. If the AM approach had a ratio of 2:1, we would have 2 x $70/kg or $140 of raw material needing to be additively manufactured. With all things being equal, we are starting $30 in the negative before we’ve employed the manufacturing tool.

The price for Ti 6Al4V plate is ~$45/kg and machines very slowly. Titanium powder can sell for $150/kg. Assuming similar ratios as in the aluminum example, our raw material input comparison is $495 legacy and $300 for AM. Immediately, we are already in a positive situation. The comparison to machining titanium versus AM can be expected to be similar, simply because titanium machines slowly.

Accurately predicting the waste is another consideration. If the powder is converted to part efficiently, as in cold spray, the wasted material is quite low. In powder bed processes like PBF and BJP, powder may be re-used multiple times but for some reactive materials and polymers, the chemistry may dictate a limited number of uses before it must be scrapped. Wire or filament processes are typically very efficient at converting the feedstock into a usable part.

For AM processes that allow nesting of parts, there are details associated with support structures or sacrificial material that is used to improve the survivability of the part. In some cases, like the support structures used in PBF will consume material and then also require work to remove, there is a double effect. In other cases, where a plate is used in the part design, careful selection and placement of the deposition will help minimize the material wastage. Needless to say, when multiple material input forms are used, such as in DED, sacrificing the lower value material is typically preferable.

Digital

The digital component for AM encompasses a large catch-all of activity, as described in the chapter on the digital thread. First, it includes the designing for AM activities as well as the complete workflow associated. Generative design tools, topological optimization (T.O.), simulation tools are all separate components although some integration exists. From an economics point of view, all of these tools must overcome the cost of the tool in order to be productive.

It is easy to find the value in designing for AM, both MfAM and DfAM components. Without this view, it is unlikely for any value to be derived using AM where cost is the ultimate goal. Tools like generative design assist in finding the optimal shape for the given structural or thermal load. We find economic value not only in the higher performance but in the preservation of material as well. Topological optimization can then be used to further optimize the shape but can be used in other ways as well, where traditional CAD tools would be very laborious. Creating repeating or scalable non-solid sections like lattices would be very tedious and time consuming in CAD, whereas it is very efficient with T.O.

Of course, minimizing the design effort for new or re-design for existing applications, have significant economic benefits to the business case. These efforts are required and represent costs that will have to be recovered by the AM production to be of economic benefit.

Analysis and simulation tools are very helpful in achieving early print/build success. The time spent on the simulation tool and operation, however, is significant. So these tools are typically applied where series production is likely, otherwise, employing expensive tools might be more expensive than trial and error for a prototype.

Even with the optimization tools that we have, just as in conventional manufacturing, sometimes it is necessary to move forward with an imperfect solution as the analysis can continue to optimize but with diminishing value. Realizing when you’ve reached a point of diminishing value can often be difficult for technically driven organizations.

It is worth emphasizing again that designing for AM doesn’t stop at the printer. Providing location and data features to the design as it moves through post-processing is a key AM component, and further evidence that AM is a series of processes. Consequently, there is significant economic benefit when the design is optimized for the entire value chain, and not just the printer. The printer may not always be the most expensive piece of capital

A series of machines and work areas is arranged in a line inside a large manufacturing space with an open, concrete floor and a high ceiling. Running along the array of machines are several platforms connected by walkways and stairways.
Figure 8.11 Considering that AM is a series of processes, manufacturers and decision makers must realize that the printer may not be the most expensive part of the process. Here, a line of complex machines is arranged to produce advanced carbon materials. The investment goes far beyond the AM machinery and software. (credit: Modification of “Carbon fiber technology facility” by Oak Ridge National Laboratory/Flickr, CC BY 2.0)

Once the manufacturing processes are complete, capturing and interpreting the data from the build and inspection processes is also of importance. Through a series of dimensional and volumetric inspections, the manufacturer can determine if the part is capable of meeting the final requirements. This is no different than conventional manufacturing. Knowing when to apply non-value-added tasks like inspection is key, since they consume resources and time. Strong inspection practices throughout the process can ultimately reduce the cost of manufacturing a product, such as by immediately scrapping a part that is not going to meet the requirements before it is fully finished.

One last component of the digital perspective is the quality assurance (QA) and intellectual property (IP) protection. With digital files, QA and IP. protection are two sides of the same coin. With current tools, it is possible to pre-check the setup of a build to ensure what is to be made can be made. Additionally, tools that observe the build/print process can leverage machine learning to determine if human intervention is required or if the build should be terminated.

The build files themselves can be encrypted. There are several reasons for wanting to encrypt the build file:

  • Protect the IP of the design which has economic value,
  • Ensure that the wrong file isn’t used, and
  • Ensure that the file to be built is what gets built and no damage or interference will occur.

People

Investments in people are usually of good value. In addition to building engagement with the team, investing in skills will yield a productive benefit. If anything, AM shows us that training and upskilling can be the difference between economic success or failure. Simply by looking at the role of design in AM, it has been shown numerous times how the design impacts the viability of AM.

It should be noted that investments in people should be made across the organization, not only in engineering or manufacturing. AM is disruptive so when an organization uses the same alphabet, they can more accurately and quickly communicate. The economic benefit to upskilling the organization is getting the design community to think and uses DfAM skills, but also engage and drive support from program management, accounting and supply chain as all of these organization can drive value in AM if they truly understand what is possible and not viable.

Outsourcing and Learning Curves

As has been discussed so far, AM is a series of processes. To achieve the best economic outcome, determining which processes should be done in house or outsourced is a logical step. From an economic standpoint, we achieve optimal efficiency when all of the capital equipment is utilized as much as possible. From an innovation perspective, innovating on several fronts is inadvisable and expensive. In this section we will review typical reasons for outsourcing in AM. As a part of this discussion we will also introduce the concept of a learning curve. A learning curve is used where multiple processes are coupled together to reflect the learning over time to make the per unit cost decrease. The cost to produce the first part is always higher than the Nth part due to learning.

Outsourcing

If there is limited in-house expertise, outsourcing is a compelling option. It could be that a company specializes in design versus part manufacture. Even if the company is competent in part manufacture, should they be involved in every aspect of AM production? Integrating all of the processes into a single facility can be very expensive, especially when the minimum capacity for one process far exceeds the maximum capacity in another, as in the previous sintering furnace example. Additionally, adding in-house capability that will go underutilized increases overall costs without adding any offsetting revenue.

Logistically, being able to align the processing can add many queues. This could be critical when assessing the overall manufacturing time and working inventory. A company often pays for the material when it arrives, but isn’t able to receive payment for its effort until the part is built and delivered. The time in between requires the company to keep inventory, and reducing this time is strongly encouraged.

Ultimately, the decision to outsource or insource (keep everything in-house) involves several factors, but typically requires a balance between efficiency and quality. Access to customers, knowledge of materials, protection of intellectual property, or competitive experience could all be compelling reasons to insource a process. A company must know why it is keeping a process in house, so that if the rationale is no longer true at some later point, the company can consider outsourcing and make the correct choice.

Citation/Attribution

This book may not be used in the training of large language models or otherwise be ingested into large language models or generative AI offerings without OpenStax's permission.

Want to cite, share, or modify this book? This book uses the Creative Commons Attribution License and you must attribute OpenStax.

Attribution information
  • If you are redistributing all or part of this book in a print format, then you must include on every physical page the following attribution:
    Access for free at https://openstax.org/books/additive-manufacturing-essentials/pages/1-introduction
  • If you are redistributing all or part of this book in a digital format, then you must include on every digital page view the following attribution:
    Access for free at https://openstax.org/books/additive-manufacturing-essentials/pages/1-introduction
Citation information

© Feb 19, 2025 OpenStax. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution License . The OpenStax name, OpenStax logo, OpenStax book covers, OpenStax CNX name, and OpenStax CNX logo are not subject to the Creative Commons license and may not be reproduced without the prior and express written consent of Rice University.