Mapping value clusters of additive manufacturing on design strategies to support part identification and selection Christoph Klahn Inspire AG, Zurich, Switzerland Filippo Fontana Product Development Group Zurich pdjz, ETH Zurich D-MAVT, Zurich, Switzerland Bastian Leutenecker-Twelsiek Product Development Group Zurich pdjz, ETH Zurich D-MAVT, Zurich, Switzerland, and Mirko Meboldt Product Development Group Zurich pdjz, ETH Zurich D-MAVT, Zurich, Switzerland and Inspire AG, Zurich, Switzerland Abstract Purpose – Additive manufacturing (AM) allows companies to create additional value in the processes of new product development and order fulfillment. One of the challenges for engineers is to identify suitable parts and applications for additive manufacturing. The purpose of this paper is to investigate the relation between value creation and the design process. The implications of this relation provide an orientation on the methods for identifying parts and applications for additive manufacturing. Design/methodology/approach – Mapping the value clusters of AM on design strategies allows determining the expected degree of change in design. A classification into major and minor design changes is introduced to describe the predictability of the impact of AM on past performance and business model. The ability to predict the future properties of an AM part determines the suitability of identification and selection methods from literature. The mapping is validated by an identification process that creates a shortlist of potential AM parts based on the strategic decision for a value cluster. Shortlisted parts are then evaluated based on the criteria technology readiness, required post-processing, customer benefit and manufacturer benefit. Findings – The mapping of value clusters on expected design changes determines the type of selection process. For minor design changes, automated part identification serves as a powerful tool while major design changes require the judgment of skilled engineers. Research limitations/implications – The mapping of value clusters to design strategies and degree of change in design is based on empirical observations and conclusions. The mapping has been validated in an industrial context in different identification and selection processes. Nevertheless the versatility of AM and industrial environments impede a universal validity of high-level concepts. Practical implications – This value-driven process of identification and selection was applied in technology transfer projects and proved to be useful for AM novices and experts. The mapping supports the identification and selection process, as well as the general product development process by providing an indication of the design effort for implementing AM. Originality/value – The novel mapping links the economic domain of value creation to the engineering domain of design strategies to provide guidance in the selection of economically and technically suitable parts for additive manufacturing. Keywords Additive manufacturing, Product development, Value, Performance, Part selection Paper type Research paper 1. Introduction Additive manufacturing (AM) is a class of production technologies that allow companies to offer innovative products, services and business models (Wohlers et al., 2018). Selecting suitable parts and applications within the scope of a company can be a challenge. Literature reports a growing number of methods for this task with various scopes, objectives and approaches. This leads to the need to support engineers in choosing tools and methods that fit the requirements of a company. The common goal in all scenarios is that companies strive to create additional value by implementing additive manufacturing. Therefore, the starting point and key element of the approach presented here are the value propositions of AM and their implications on the design process. Mapping the value clusters of AM on the design strategies gives an indication of the expected degree of The current issue and full text archive of this journal is available on Emerald Insight at: https://www.emerald.com/insight/1355-2546.htm Rapid Prototyping Journal © Emerald Publishing Limited [ISSN 1355-2546] [DOI 10.1108/RPJ-10-2019-0272] Received 22 October 2019 Revised 18 March 2020 Accepted 2 September 2020