What is an Ashby Plot?

Ashby plots, also known as Ashby charts, are widely used in engineering, mechanical design, materials science, chemistry, and other material-heavy fields. They are named after Professor Michael Ashby from Cambridge University, who developed them.

At the simplest level, Ashby plots are 2D scatter plots that show one material property on the x-axis and another material property on the y-axis. This allows trade-offs among different material properties and other development parameters, such as cost, to be determined when choosing a material for a particular application. They are essentially a way of comparing different factors and properties when choosing a material that needs to fulfill a certain purpose. Ashby plots can be used to compare any types of material. While 3D plots are difficult to visualize, color can be used in 2D Ashby plots to provide information on additional properties.

Ashby plots can be used in any industry where materials science and specific properties (mechanical, thermal, physical, electrical, environmental, etc.) are central to a product. Because Ashby plots are a broad tool that are not targeted to any specific industry, they are a very versatile tool for engineers. Some common examples where Ashby plots are widely used include the automotive, aerospace, consumer technology, power generation, and construction industries, as well as academia. 

All Ashby plots serve as visual material selection and screening tools that enable engineers to look at the different combinations of properties for different materials. In many cases, the most advanced or popular or widely-used material may not be chosen because other factors and costs may limit their potential for a specific application. In Ashby plots, a trade-off is made among the necessary properties and other factors, such as material geometry, material availability, sustainability, and cost. The most appropriate material that has the best trade-off across all factors is the one that is chosen during the selection process.

Ashby plots often use colors to denote material classes, such as composites, polymers, metals, alloys, high-entropy alloys, natural materials, non-technical ceramics, or technical ceramics.

Ashby plots can be used during the design process to improve the performance of an existing component by finding a more suitable material, or they can be used to find the right material for a new application.

While Ashby plots can compare any two material properties — often some form of strength, cost, environmental impact, or lightweighting — some common examples that engineers look at may include:

• Density vs. Young’s modulus
• Young’s modulus vs. cost
• Yield strength vs. fracture toughness
• Environmental impact vs. any material property of interest
• Density vs. maximum service temperature

Ashby plots are part of the Ashby selection methodology, which centers around material choice. This methodology starts by considering all available materials across all material classes and whittling them down to a narrower range by considering more specific material requirements and constraints.

To narrow the choices down, engineers need to break down the design requirements of the application, considering questions such as:

• What is being built?
• What is the function of the product?
• What loading requirements does it need?
• What are its tolerances?
• Does it need high temperature properties?
• Does it need to be resistant to any corrosive elements?
• What are the geometry constraints?
• Is the carbon footprint important?

All these types of design questions help to determine what material properties are important in the material, what the must haves of the material are, and what properties may be flexible to trade-offs.

Once the material objectives have been identified, materials are screened against constraints and “must-have” properties to narrow the choice of materials that would be suitable. Anything that falls outside of these constraints is eliminated, while remaining materials can be considered and ranked based on the best potential type (considering factors such as cost, etc.). The resulting Ashby plot only displays those materials that have not already been eliminated by the constraints. The properties for material on the plot are often displayed as a range (considering the typical variation in performance), rather than a single value. Thus, the material often appears as a “bubble” to represent the range of properties that a material might exhibit.

For simple objectives, one or two Ashby plots combined with other constraints are usually sufficient to reach a decision. However, for many advanced applications, multiple objectives are often required, e.g., trying to compare a specific geometry under certain loading conditions. These require multiple Ashby plots or more complicated Ashby plots that use performance indexes to find the right material for the application.

For more complex or specific applications, simpler Ashby plots will not usually suffice. This is when using a performance index is necessary. A performance index is not a single attribute value on an axis of the Ashby chart, it is a mathematical combination of multiple material property attributes that allow several performance factors to be analyzed using a single axis of the chart. This simplifies the visual element when dealing with multiple objectives, as it takes a number of factors into account in a single plot to help find the right material.

Some straightforward examples of performance indexes are panels in bending, columns in compression, or shafts in torsion. Taking the panel in bending example, there are free variables that could potentially change during the design, such as the thickness of the panel depending on the required performance. Fixed variables, i.e. those that can’t change in the design, also need to be identified. For example, this could be the length and width of the panel as it needs to fit within a certain space.

Once these are determined, the limiting constraints can be identified. These center around the behavior of the material, such as a stiffness-limited design that must not bend past a certain point, or a strength-limited design where it can’t fail under a certain load. The limiting constraints are concerned with whether the material will fail under certain conditions and finding materials that will not fail.

All these factors are incorporated into the performance index and enable engineers to rank many different materials and material classes for design optimization in specific scenarios. The performance factor thus takes geometry and loading into account to an extent. This means that rather than simply giving the "lowest cost material" it will give the "lowest cost option for a panel in bending in a stiffness-limited design," according to your specific constraints. For example: A metal may produce a thinner part, but a thicker plastic may still be lighter overall and therefore more favorable in certain scenarios. While performance indexes can be derived manually or calculated manually for each scenario, the quickest and easiest way to use performance index metrics today is to use software that incorporates pre-defined performance indexes in an easy-to-select format covering a wide range of engineering scenarios.

There are many different situations and materials that can be screened depending on the application. Below is a typical run-through of how one engineer from Ansys, part of Synopsys, determined what new materials might replace an existing material to improve performance. In this example, a new material for an automotive crossbeam was sought to replace the current sand cast 357 aluminum alloy. While the aluminum crossbeam was sufficient, the engineers considered how to find a new material that was lighter, thereby reducing the weight of the car part and, in turn, the overall environmental impact of the vehicle.

To start the selection process, the crossbeam was approximated to be a beam in bending. Fixed and free variables were determined as follows: the length and shape of the beam couldn’t be changed, but the area of the beam (the cross-section) could be changed if needed.

The limiting constraint of an automotive crossbeam is its strength, so the material needed to be strong enough to withstand loads without failing. The mass is one of the key objectives here as well. The first Ashby plot used two performance indices: on the Y axis it was mass per unit of strength for a beam in bending, on the X axis it was cost per unit of strength for a beam in bending. This led to many families of materials, from technical ceramics to metals, metal alloys, and non-technical ceramics being potentially suitable according to this initial analysis. Some materials here would be thicker but lighter, while others would be thinner and heavier, based on the density of the materials.

At this point, no materials had been eliminated, leading to completely unusable materials list for an automotive application. Though technically OK from a mass and/or cost per unit of strength perspective, materials such as wood and concrete are not suitable for an automotive application. Once sensible constraints were applied, unfeasible materials were removed to leave only suitable materials. For the automotive crossbeam, example constraints included sufficient mechanical properties, operating in a wide temperature range (-40 to 100 °C) and at least an acceptable resistance to fresh water and salt water.

After applying these constraints, the materials that remained on the bottom side of the Ashby plot were the lightest, but also tended to be more expensive, such as carbon fiber composite materials. Options on the far left side of the Ashby plot were the cheapest, but also tended to be heavier. For a low-mass, low-price compromise, it was found that glass-fiber-filled PA66 (Nylon 66) grade polymers could potentially be a good replacement that meet all the requirements. This candidate was then taken forward for further analysis, simulation, and physical testing.

The data source for the plot was the Ansys MaterialUniverse database, a unique Ansys-specific database of several thousand general engineering materials with complete and comparable information, making it particularly suitable for material selection and/or performance indices in Ashby plots.

Even though there are many benefits to using Ashby plots, it’s not a flawless method. Like any analytical method, there are always some limitations. Limitations of Ashby plots include:

• It’s not possible to simultaneously compare more than two or three factors with a single Ashby chart, and doing so requires creating multiple Ashby charts and comparing the data side by side
• It’s a visual method that doesn’t give a single answer or a single best material, instead, it gives families of materials or a range of potential candidates that need to be investigated in more detail. Engineering judgment plays into this because each organization must decide to what extent each trade-off factor is important, e.g. how much cost increase is acceptable for an increase in performance
• Ashby plots need to be used alongside other search and selection queries to fully understand if a material will be suitable for an application
• Ashby plots require complete and comparable data, as it is not possible to plot a material if data for a property is absent. This makes Ansys MaterialUniverse database particularly suitable for this application

Ashby plots can be generated using the Ansys Granta materials information, selection, and data management product collection, including Ansys Granta Selector materials selection software and Ansys Granta MI Enterprise materials data management software. In Ansys Granta, the data can be plotted and labeled, and any number of constraints and requirements can be included to narrow the material selection down to a few options that can be investigated in more detail, e.g. reducing the number of materials from tens of thousands to five or 10 potential materials once the constraints have been put in place.

Ansys Granta Selector software is a standalone program aimed at material selection tasks. It is a Windows desktop-based solution for designers, simulators, and materials science experts. Ansys Granta MI software is an enterprise-level application used by organizations to manage and store their own materials data, combined with the ability to carry out material search and selection. Both software tools can take materials data and create Ashby plots.

Once the materials have been chosen using either Granta tool, these materials and their use in different application scenarios can be simulated in other Ansys tools such as Ansys Mechanical structural finite element analysis software, Ansys Discovery 3D product simulation software, Ansys Maxwell advanced electromagnetic field solver, or Ansys HFSS high-frequency electromagnetic simulation software. The relevant data can be directly exported from Granta into the other tools to simulate any potential candidates for their desired service in more depth and find which material is the best option.

If you’d like to find out more about how you can utilize Ashby plots to choose the right material, or set of materials, for your application, then get in contact with our experts today.

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