Additive manufacturing (AM) refers to the production of a component, part, tool or even an assembly using a layer-upon-layer method of fabrication. Additive processes join together formed layers of liquid, powder or sheet materials to create three dimensional objects. It has been reported that AM may cut product development costs by up to 70% and time to market by up to 90%, however, the adoption of AM is still slow and underutilised due to the lack of knowledge of potential users and coupled with the advancement in technology developments and the introduction of new materials. Typically, more than one material is suitable for specific engineering applications and the final selection will bring some advantages as well as disadvantages. A material selection tool can be used to aid users in recommending suitable materials and technologies to manufacture any given product. The aim of this study is to conduct an analysis of material selection tools available for AM which seeks to address the following questions: (1) What kinds of AM material selection tools exist already?; (2) What are the methods/systems/tools/approaches currently applied?; (3) Is there any inadequacy in these existing tools?
This study is constructed using literature from previous research, articles, patents, databases and theses. All the relevant information is organised in a table detailing the tool name, author, description of the tool, methods, systems and approaches used for the tool and any limitations observed from the tool. This table is used to compare and highlight any major input of these existing tools, which responds to the three questions that have been highlighted above. The outcome of this research intends to provide a tangible proposition for a robust AM material selector. The availability of this information will also be very helpful for designers, researchers, and other users performing material selection for AM. Such information presented within this paper leads into further detailed research by the authors investigating the wider utilisation of AM technologies and techniques by a wide industrial base, where the functionality of AM is critically modelled using a case-based approach.