What is it about?

Various industries are embracing Additive Manufacturing (AM) due to its numerous advantages over traditional manufacturing techniques. However, its introduction must be evaluated on a case-by-case basis. To support this transition and optimize production and logistics processes, it is crucial to understand the key features, thresholds, and operational characteristics of AM technologies. In this paper, we present a comprehensive analysis of these aspects by building a classification and decision-support framework for efficient adoption of AM technologies. Features associated with machine characteristics, process features, physical properties of the printed parts, and costs were considered to develop the framework, which aims to aid decision-making in selecting the most appropriate technology for different industrial cases. Additionally, we provide a comparison of AM with injection molding to gain a deeper understanding of the potential opportunities for AM, as well as an overview of the usage of AM in different sectors. The proposed framework can be a valuable resource to aid organizations in adopting AM, as it allows managers and practitioners to make thoughtful decisions that are critical to reshape current production systems.

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Why is it important?

The study offers a novel classification and decision-support framework for selecting AM technologies, incorporating machine characteristics, process features, physical properties of printed parts, and costs as key features to evaluate the potential of AM. Additionally, it provides a deeper understanding of these features as well as the potential opportunities for AM and its impact on various industries.

Perspectives

The proposed framework offers valuable support for decision-makers to select the most suitable AM technologies, as demonstrated through practical examples of its utilization. In addition, it can help researchers identify the limitations of AM by pinpointing applications where existing technologies fail to meet the requirements.

Paulo Jorge Nascimento
Universidade de Coimbra

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This page is a summary of: A decision-support framework for selecting additive manufacturing technologies, Journal of Manufacturing Technology Management, July 2023, Emerald,
DOI: 10.1108/jmtm-02-2023-0047.
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