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AM design and its impact on the AM business case

One of the most overlooked factors of additive manufacturing is the business case. In this post, we will look at:

  • The important relationship between AM design and its impact on the AM business case

  • Get under the hood of the iron triangle of cost/quality/time and understand the trade-offs

  • The underlying equations and parameters that affect our design decisions

  • Often when we see design tips and guidelines, there is a lack of information about WHY. We will try to answer that here.

  • Some design tips to help improve the profitability of your AM designs.

The iron triangle

The balance between cost, performance and time has been studied by project management consultants since the 1950s. The term iron triangle was coined by Dr Martin Barnes in 1969 and was further developed by Roger Atkinson who stated that work is constrained by cost, deadline or scope (number or quality of features) and the project stakeholders can trade between constraints.

The Iron Triangle

As with project management, engineering design is also constrained by the iron triangle. All of the decisions that we make during the design process will have an impact on the cost, quality and time taken to build our products. In additive manufacturing, the time and cost can be well defined. Quality is harder to define and can have different specifications depending on the part being designed.

Build time, cost and quality in additive manufacturing

To understand how we can design around the iron triangle, we must first understand the properties that affect the quality, cost and build time of AM parts. In this section, we will focus mainly on laser powder bed fusion methods and the following equations will consider single laser systems. However, the theory should carry across all processes.

Build time

Firstly, let’s consider print time. In additive manufacturing, the build time is defined by the following equation:

Build time equation

The build rate is defined by the processing parameters, for example in laser powder bed fusion the build rate is a function of many factors including the laser spot size, the layer thickness and the scan spacing.

For clarity, let’s tabulate the parameters in the equation to see which factors need to be minimised and maximised in order to minimise print time.

Tabulation of the parameters of the equation

Here we can see that there are many factors here that are influenced by the overall geometry of a part and therefore can be optimised by applying DfAM knowledge.

Build cost

The cost of the additive manufactured part is defined as the sum of the costs of the pre-processing, the print itself and the post-processing:

Cost equation

Where the cost of printing is defined as:

Print cost

And the material cost is defined as:

Material cost

The build cost consists of the geometric factors that govern the build time but also other factors including the material cost and many indirect factors including the energy consumption of the machine.

As an AM designer, you will have less control over these factors and therefore we will not focus on these elements in this post.

Part quality

Many factors can affect the quality of a printed part. Some of the more prominent factors include scan speed, layer thickness, hatching strategy, downskin, and any areas of the part that are in contact with support structures. Let’s now consider some of these in more detail.

Firstly, let’s consider layer thickness. In layered manufacturing processes such as additive manufacturing, the layer thickness can affect the surface roughness and uniformity of the part. You can see in the image below, that if the surfaces become very curved the deviation between the desired shape and the printed part can be quite large if the layer thickness is too high.

Layer thickness

As you can see the relationship between the geometry of a part and the process parameters that go into building it are tightly integrated. Therefore it is important that if you are not in control over the design and the build that you ensure that you have regular back and forth dialogue between the design engineers and AM process engineers about the quality specification of the part you are making.

Designing within the iron triangle

Now that we know what parameters affect the cost, build time and quality, we can now relate this back to the iron triangle. As we know, it is impossible to have all three characteristics so it is up to us as designers to examine where we can include the allowable tradeoffs.

One of Gen3D’s key principles of design for additive manufacturing is design for minimal material usage and as part volume is a key driver for both build time and part cost it is essential that we can remove as much material as possible.

In our design for additive manufacturing course, we teach many techniques that can be used for material reduction including, topology optimisation, cellular structures and support structure reduction.

“I can sacrifice speed but it should look great”

If time is the constraint that we wish to trade-off, but we need excellent surface finish on the part then we can analyse the factors in the build time equation that affect the surface quality of a part. In this case, we may wish to reduce the layer thickness of the part, slow down the scan speed or spend extra time ensuring that support structures don’t interface with the part in critical aesthetic zones.

However, this is not as simple as it seems, if we change the orientation of a part, the design constraints of most additive manufacturing processes means that we may introduce some printing issues. For example, if we re-orient a self-supporting channel, we may introduce internal supports structures that we cannot remove. It is therefore important to consider the design and support strategy simultaneously.

At Gen3D, we aim to streamline this process by including the build plate inside the design environment as default.

Gen3D manifold design - additive manufacturing

“I don’t mind paying a little more but it should have market-leading performance”

If performance is the main driver and we are willing to spend more money to achieve that in the fastest time then we can look at the cost equation and find optimal materials for a given process. This process of finding the most cost-efficient material for a task can be challenging and we recommend reading Jon Meyer’s excellent article on coupling topology optimisation with material selection for more information on this topic.

We do, however, see that build packing efficiency can have a direct impact on the parts that can be designed. For example, we may fit significantly more parts on a build plate in one orientation than another but this may come with the sacrifice of extra support material or reduced performance.

cantilever base plates

“The part doesn’t have to look perfect but I need it fast”

If build time is the main driver and the aesthetics of the part are not so important then we need to analyse the build time equation and analyse the driving properties. Here we may want to maximise the build parameters for build speed or orient the part for the fastest speed. We can also think about shelling parts and filling them with lattice structures to reduce material consumption if structural strength is not compromised.


Presently, the high cost of additive manufacturing (AM), particularly, metal AM, means it’s important to select potential AM part candidates that will achieve the quality required at the correct price point. AM has the potential to significantly reduce lead time to market for many products. This is because of the ability to create mass customised products and remove the requirement for hard tooling that would be required for casting and forging.

AM design and its impact on the AM business case is huge. When we are designing parts for additive manufacturing, we should be trying to create the most cost-effective, high-quality parts possible. However, this is often not possible. The iron triangle dictates that there are always tradeoffs that we have to make as designers.

By understanding the fundamental parameters that govern the build time and cost of additively manufactured parts we can have discussions about the trade-offs we are willing to make in our designs and understand the changes we need to make in our designs to make this happen.

Learn to design better parts for additive manufacturing by subscribing to our “Introduction to Design for Additive Manufacturing” course. You will receive unlimited access to over 3 hours of video content, 50+ pages of course notes, in-depth analysis of industrial case studies and interactive design walkthroughs in Gen3D’s proprietary design software. Sign up at