A review on benchmark artifacts for evaluating the geometrical performance of additive manufacturing processes
06 Jul 2017-The International Journal of Advanced Manufacturing Technology (Springer London)-Vol. 93, Iss: 5, pp 2571-2598
TL;DR: In this paper, the authors present a review of the available literature on benchmark artifacts for evaluating the geometrical performance of additive manufacturing processes and propose a summary of guidelines to design benchmark artifacts.
Abstract: In recent years, additive manufacturing (AM) has undergone a rapid growth, therefore several processes based on different working principles (e.g. photopolymerization, sintering, extrusion, material jetting, etc) are now available and allow to manufacture parts using a wide range of materials. Consequently, the so-called benchmark artifacts are necessary to assess the capabilities and limitations of each AM process or to compare the performance of different processes. This paper focuses on the benchmark artifacts for evaluating the geometrical performance of AM processes and proposes an extensive review of the available literature, analyzing the design of such test parts in detail. The investigated test parts are classified according to the process aspect that they are able to evaluate (dimensional/geometrical accuracy, repeatability, minimum feature size) and the combination AM process/materials for which they have been used. In addition, the paper draws a summary of guidelines to design benchmark artifacts for geometrical performance evaluation.
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TL;DR: The infrastructure under development for specification standards in AM is presented, and the research on geometrical dimensioning and tolerancing for AM is reviewed, and post-process metrology is covered, including the measurement of surface form, texture and internal features.
177 citations
TL;DR: This work supports AI related decision-making in additive manufacturability analysis and (re-)design for AM and guides machine learning to addressing problems related to AM design rules.
Abstract: Additive Manufacturing (AM) is becoming data-intensive while increasingly generating newly available data. The availability of AM data provides Design for AM (DfAM) with a newfound opportunity to construct AM design rules with improved understanding of AM’s influence on part qualities. To seize the opportunity, this paper proposes a novel approach for AM design rule construction based on machine learning and knowledge graph. First, this paper presents a framework that enables i) deploying machine learning for extracting knowledge on predictive additive manufacturability from data, ii) adopting ontology with knowledge graphs as a knowledge base for storing both a priori and newfound AM knowledge, and iii) reasoning with knowledge for deriving data-driven prescriptive AM design rules. Second, this paper presents a methodology that constructs knowledge on predictive additive manufacturability and prescriptive AM design rules. In the methodology, we formalize knowledge representations, extractions, and reasoning, which enhances automated and autonomous construction and improvements of AM design rules. The methodology then employs a machine learning algorithm of Classification and Regression Tree on measurement data from National Institute of Standards and Technology for construction of a Laser Powder Bed Fusion-specific design rule for overhang features. This work supports AI related decision-making in additive manufacturability analysis and (re-)design for AM and guides machine learning to addressing problems related to AM design rules. This work is also meaningful as it provides sharable AM design rule knowledge with the AM society.
60 citations
TL;DR: An in-depth analysis of the existing representations of additive manufacturing data is provided, detailed comparisons among these representations are made, and a discussion about the main issues in AM data representation is carried out on the basis of the comparisons.
Abstract: An effective representation of additive manufacturing (AM) data is important for ensuring the repeatability of AM processes and the reproducibility of AM parts. Recently, several standardised representations have been developed and used in the industry. While at the same time, a number of other representations have been presented within the academia. The coexistence of different representations generates a series of questions and discussions: What is a representation of AM data? Are the standardised representations comprehensive enough to ensure the repeatability and reproducibility? What challenges have been addressed so far in the presented representations? What are the strengths and weaknesses of each representation? What are the main issues in the field of AM data representation currently? What are the potential research directions of AM data representation in the future? To approach these questions, a review of the existing representations of AM data is presented in this paper. Firstly, an in-depth analysis of the existing representations is provided. Then, detailed comparisons among these representations are made, and a discussion about the main issues in AM data representation is carried out on the basis of the comparisons. Finally, some future research directions of AM data representation are suggested.
46 citations
TL;DR: 3D printing techniques are introduced with respect to the technical parameters and features that are uniquely related to each stage of pharmaceutical development, and specific micro-sized pharmaceutical applications of 3D printing are grouped according to the provided benefits.
Abstract: 3D printing, as one of the most rapidly-evolving fabrication technologies, has released a cascade of innovation in the last two decades. In the pharmaceutical field, the integration of 3D printing technology has offered unique advantages, especially at the micro-scale. When printed at a micro-scale, materials and devices can provide nuanced solutions to controlled release, minimally invasive delivery, high-precision targeting, biomimetic models for drug discovery and development, and future opportunities for personalized medicine. This review aims to cover the recent advances in this area. First, the 3D printing techniques are introduced with respect to the technical parameters and features that are uniquely related to each stage of pharmaceutical development. Then specific micro-sized pharmaceutical applications of 3D printing are summarized and grouped according to the provided benefits. Both advantages and challenges are discussed for each application. We believe that these technologies provide compelling future solutions for modern medicine, while challenges remain for scale-up and regulatory approval.
45 citations
Cites background from "A review on benchmark artifacts for..."
...Literature has attempted to address this [70,71], but more research in the area would be invaluable....
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TL;DR: In this paper, a high-speed sintering additive manufacturing benchmarking artefact has been designed and characterised using a design-for-metrology approach, where the specifications and operating principles of the instruments that would be used to measure the manufactured artefact were taken into account during its design process.
Abstract: We present the design and characterisation of a high-speed sintering additive manufacturing benchmarking artefact following a design-for-metrology approach. In an important improvement over conventional approaches, the specifications and operating principles of the instruments that would be used to measure the manufactured artefact were taken into account during its design process. With the design-for-metrology methodology, we aim to improve and facilitate measurements on parts produced using additive manufacturing. The benchmarking artefact has a number of geometrical features, including sphericity, cylindricity, coaxiality and minimum feature size, all of which are measured using contact, optical and X-ray computed tomography coordinate measuring systems. The results highlight the differences between the measuring methods, and the need to establish a specification standards and guidance for the dimensional assessment of additive manufacturing parts.
44 citations
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TL;DR: In this article, the authors investigated the possibility of producing medical or dental parts by selective laser melting (SLM) and developed a procedure to fabricate frameworks for complex dental prostheses.
Abstract: Purpose – This paper seeks to investigate the possibility of producing medical or dental parts by selective laser melting (SLM). Rapid Manufacturing could be very suitable for these applications due to their complex geometry, low volume and strong individualization.Design/methodology/approach – The SLM‐process has been optimized and fully characterized for two biocompatible metal alloys: Ti‐6Al‐4V and Co‐Cr‐Mo. Mechanical and chemical properties were tested and geometrical feasibility, including process accuracy and surface roughness, was discussed by benchmark studies. By developing a procedure to fabricate frameworks for complex dental prostheses, the potential of SLM as a medical manufacturing technique has been proved.Findings – Optimized SLM parameters lead to part densities up to 99.98 percent for titanium. Strength and stiffness, corrosion behavior, and process accuracy fulfil requirements for medical or dental parts. Surface roughness analyses show some limitations of the SLM process. Dental frame...
738 citations
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