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For more than ten years, the value of additive manufacturing (AM) for after-sales service logistics has been propagated. Today, however, only few applications are observed in practice. The purpose of this paper is to discuss possible reasons for this discrepancy and to develop a method to simplify the identification of economically valuable and technologically feasible business cases.

The approach is based on the analytic hierarchy process and relies on spare part information, that is easily retrievable from the company databases. This has two advantages: first, the approach can be customized toward specific company characteristics, and second, a very large number of spare parts may be assessed simultaneously. A field study is discussed in order to demonstrate and validate the approach in practice. Furthermore, sensitivity analyses are performed to evaluate the robustness of the method.

Results provide evidence that the method allows a valid prioritization of a large spare part assortment. Also, sensitivity analyses clarify the robustness of the approach and illustrate the flexibility of applying the method in practice. More than 1,000 positive business cases of AM for after-sales service logistics have been identified based on the method.

The developed method enables companies to rank spare parts according to their potential value when produced with AM. As a result, companies can evaluate the most promising spare parts first. This increases the effectiveness and efficiency of identifying business cases and thus may support the adoption of AM in after-sales service supply chains.

There are many investigations in design methodologies, but there are also divergences and convergences as there are so many points of view. This study aims to evaluate to corroborate and deepen other researchers’ findings, dissipate divergences and provide directing to future work on the subject from a methodological and convergent perspective.

This study analyzes the previous reviews (about 15 reviews) and based on the consensus and the classifications provided by these authors, a significant sample of research is analyzed in the design for additive manufacturing (DFAM) theme (approximately 80 articles until June of 2017 and approximately 280–300 articles until February of 2019) through descriptive statistics, to corroborate and deepen the findings of other researchers.

Throughout this work, this paper found statistics indicating that the main areas studied are: multiple objective optimizations, execution of the design, general DFAM and DFAM for functional performance. Among the main conclusions: there is a lack of innovation in the products developed with the methodologies, there is a lack of exhaustivity in the methodologies, there are few efforts to include environmental aspects in the methodologies, many of the methods include economic and cost evaluation, but are not very explicit and broad (sustainability evaluation), it is necessary to consider a greater variety of functions, among other conclusions

The novelty in this study is the methodology. It is very objective, comprehensive and quantitative. The starting point is not the case studies nor the qualitative criteria, but the figures and quantities of methodologies. The main contribution of this review article is to guide future work on the subject from a methodological and convergent perspective and this article provides a broad database with articles containing information on many issues to make decisions: design methodology; optimization; processes, selection of parts and materials; cost and product management; mechanical, electrical and thermal properties; health and environmental impact, etc.