In almost all design exercises, materials selection is an important element. There are hardly any instances where only one material is suitable for the job – space shuttle windows being one of the few – and so one needs a means to compare the candidate materials.
As energy prices have increased and technology has improved, we have seen a number of material adjustments.
- Automobiles have substituted increasing amounts of lightweight magnesium and aluminium alloys for steel
- Aircraft are substituting carbon fibre-reinforced plastic and titanium alloys for aluminium
- Satellites have long been constructed from exotic composite materials
The selection of a material may be partly based on a numerical comparison of properties and partly qualitative. The process may involve some “red lines” – eliminating materials which are clearly unsuitable or even illegal. At the other end, there may be formulae which enable materials to be rigorously compared mathematically.
Of course, cost per kg is not the only important factor in material selection. An important concept is ‘cost per unit of function’. The optimum material might change with time, as the relative cost of various materials varies. Paradoxically, the optimum material might even be different in different locations, because the relative costs of materials may vary owing to factors such as trade tariffs and transportation costs.
That’s difficult enough, but of course in most cases, materials have to provide not just one property, but a combination of properties. So to take this logic forward further, the design engineer has to try to decide which properties are most important and assign some sort of weighting order to the properties required.
Add to this the fact that the available data isn’t always fully available, and it is perhaps no surprise that design engineers tend to stay with the materials with which they are most familiar. This often leads to very conservative design principles.
In areas where highly specialised design comparisons need to be made, highly specialised testing regimes may be instituted, as would be the case for example with aircraft wings, where a comparison between aluminium and advanced composites would involve many hours of accelerated testing. Such a comparison is made even more difficult by the fact that aluminium and composites fail in different ways, so it is impossible to define material properties which can be compared in a meaningful way.
Against these difficulties, some laudable attempts have been made to provide ways of assisting the materials selection process. In the (broadly) pre-computer days of the 1970s, a comprehensive paper-based materials selection system called the Fulmer Materials Optimizer was published by a UK-based organisation called Fulmer Research Institute. It was the mastermind of Norman Waterman and following his departure, it was later taken on by myself, amongst others.
The publication contained extensive data about all the materials classes and their relative performance in terms of mechanical, electrical, thermal, corrosion, wear and other specialist properties. Most of the data was presented in simple tabular, chart and graphical form. The publication was later re-launched by the Dutch publishing company as the Elsevier Materials Selector.
Many of the ideas contained in the Optimizer were in fact originally based on the concepts of Cambridge University professor Mike Ashby. He took them forward via a separate organisation called Granta Design, where they devised a computerised materials selection – the CES Selector. This is still in existence today.
The traditional Ashby plot is a scatter plot which displays two or more properties of many materials or classes of materials. For example, if a key design objective is the stiffness of a plate of the material, then the designer needs a material with the optimal combination of density, Young’s modulus, and price.
Materials families (polymers, foams, metals, etc.) can be identified by colours. These plots are useful to compare the ratio between different properties.
In the example discussed above, the stiff/light part would have Young’s modulus on one axis and density on the other axis, with one data point on the graph for each candidate material. On such a plot, it is easy to find not only the material with the highest stiffness, or that with the lowest density, but also that with the best ratio. Using a log scale on both axes facilitates selection of the material with the best plate stiffness.
Optimising complex combinations of technical and price properties is a hard process to achieve manually, so rational material selection software is an important tool.
The CES Selector can be used for a metal to polymer material substitution. In one example, Honeywell Aerospace wanted to substitute a polymer for the aluminum alloy used in the manufacture of a pressure regulator housing.
The initial approach was to convert the original aluminum alloy hog-out to a moldable Valox polyester, while the geometry and size were maintained. However, it is not unusual for problems to arise with fixed-geometry metal-polymer substitutions. In this case, the thick central section led to issues with very low yield rates and delayed cracking after molding. To overcome this, CES Selector was used to investigate alternative injection molding materials that were more forgiving to this challenging situation.
Honeywell began the rational selection process by defining the design requirements of the housing, material, and production method. These included:
- Environmental performance constraints: maximum service temperature and solvent resistance.
- Production methods: a material capable of injection molding was required.
- End user requirement: compatibility with self-cutting thread screws for installation purposes.
CES Selector provides property data for virtually every class of purchasable engineering material — around 3000 potential candidates. As property values are either populated with known, referenced data or with estimated values estimated, Honeywell Aerospace was able to consider the universe of potential candidate materials: no suitable materials would be excluded simply because their properties were not known.
The range of possible materials was quickly reduced (using a ‘Tree stage’ selection) by restricting the choices to those materials that met the processability criteria. The pool was further reduced by adding two ‘Limit stages’, taking account of maximum temperature and durability. Based on the design specifications, two materials (PEEK and PEI) were identified as possible alternatives to the polyester (PBT).
The Ashby diagram below shows that there is relatively little difference in fatigue strength between the candidate materials. However, from considering the thermal expansion coefficient and maximum service temperature (right), PEEK was chosen as the preferred material for component testing to ensure that it performed as well as, or better than, the baseline material.
Discover plastics options in Prospector
While the CES Selector incorporates data from all materials classes, the most comprehensive source of data on materials is the UL Prospector Materials Database, which incorporates its own materials selection capability. Incorporating information from around 1000 materials manufacturing companies, it contains over 85,000 plastics datasheets and nearly 10,000 metals datasheets, along with nearly 50,000 UL yellow cards.
A particularly powerful feature in Prospector is the sections on plastic additives and equipment. There are over 400,000 users of the powerful parametric search engine, which allows quick and easy access to property and processing information critical to product development.
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