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A Comprehensive Overview of Additive Manufacturing Processes Through a Time-Based Classification Model.

Maria Koltsaki¹, Maria Mavri¹

¹Department of Business Administration, University of the Aegean, Chios, Greece.

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|February 23, 2024

Summary

The COVID-19 pandemic highlighted the need for innovation, with three-dimensional printing (3DP), a type of additive manufacturing (AM), emerging as a key solution. This study classifies AM technologies to guide systematic and less risky industrial investment.

Keywords:

3D printing method 3D printing technology AM classification AM process

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Area of Science:

Materials Science
Manufacturing Engineering
Industrial Innovation

Background:

The COVID-19 pandemic caused global supply chain disruptions, increasing the demand for innovative manufacturing solutions.
Three-dimensional printing (3DP), a form of additive manufacturing (AM), offers an effective method for fabricating complex geometries from digital designs.
The need for structured approaches to AM adoption has become apparent due to its growing importance.

Purpose of the Study:

To conduct a chronological literature review of additive manufacturing (AM) technologies.
To propose a multilevel classification model for AM processes based on technology and material factors.
To analyze the relationship between the proposed AM taxonomy and the historical development of these technologies.

Main Methods:

A comprehensive literature review of AM technologies, sorted chronologically.
Development of two double-level classification models for AM processes.
Analysis using a triangular methodology, referencing the ISO/ASTM 52900:2021 standard.
Investigation of the temporal relationship between AM process invention and the proposed classification.

Main Results:

Two distinct double-level classification models for AM processes were established, categorizing them by technology and material.
Each AM process was successfully placed within the proposed classification framework.
A correlation was found between the historical invention timelines of AM processes and their placement within the developed taxonomy.

Conclusions:

The study identifies crucial factors for the growth of the additive manufacturing (AM) ecosystem.
The proposed classification system offers a novel approach to selecting optimal AM solutions for industrial applications.
This systematic classification reduces investment risk by considering AM processes, materials, and technological evolution.