There is an increasing awareness that robust decisions need to be made early within the design process, in order to avoid mistakes that could be costly to rectify at a later stage. As a result, it is important that the relevant material and processing information can be assessed in the early stages of design. For example, the manufacture of a high quality cast aluminium component relies on selecting the correct alloy, process and heat treatment—any changes during the methoding would be both costly and time consuming. Traditionally, these choices are made using “expert” knowledge and in-house data. However, such approaches have two inherent problems: expert knowledge can be lost, and novel options may be over-looked. This paper examines ways in which selection procedures can be used to assess the available options for casting in aluminium. The aims are twofold: to demonstrate how databases and simple modelling techniques can be used to produce repeatable and reliable selections at different levels of detail and, in addition, how the application of “fuzzy logic” to a software-based selection tool can improve the robustness of the decisions that are taken.
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