Demystifying “absolute truths” of additive manufacturing

Authors received funding from the European Institute of Innovation and Technology (EIT) \u2013 Project Smart WAAM: Microstructural Engineering and Integrated Non-Destructive Testing. This body of the European Union receives support from the European Union's Horizon 2020 research and innovation programme. Publisher Copyright: © 2024 The AuthorsThe hype around additive manufacturing technologies suggests that any complex shaped structure can be fabricated regardless of the type of material used. Moreover, it is often suggested that additive manufacturing processes will certainly disrupt the supply chain logistics and that everyone will be able to print on the demand at the comfort of their home. In this viewpoint, we describe and demystify some of the common assumptions associated with these set of technologies. We also show that conventional manufacturing processes cannot be fully replaced by additive manufacturing technologies, but rather there is a need for a complementarity between well-consolidated manufacturing technologies and additive manufacturing. While some of the contents presented here are basic for specialists working in the manufacturing field, we expect that this viewpoint can aid researchers working on topics related to additive manufacturing, but with less focus on the manufacturing aspects, helping them understand the actual limitations and advantages associated to these technologies. The four key issues that are addressed in this viewpoint, and their consequences, also intend to shape and mold future entrepreneurial efforts on additive manufacturing, as well as define future impacts (environmental, logistics, commercial and disruptive) associated to additive manufacturing technologies.publishersversionpublishe

In situ monitoring of additive manufacturing using digital image correlation: A review

UIDB/00667/2020 POCI-01-0145-FEDER-016414This paper is a critical review of in situ full-field measurements provided by digital image correlation (DIC) for inspecting and enhancing additive manufacturing (AM) processes. The principle of DIC is firstly recalled and its applicability during different AM processes systematically addressed. Relevant customisations of DIC in AM processes are highlighted regarding optical system, lighting and speckled pattern procedures. A perspective is given in view of the impact of in situ monitoring regarding AM processes based on target subjects concerning defect characterisation, evaluation of residual stresses, geometric distortions, strain measurements, numerical modelling validation and material characterisation. Finally, a case study on in situ measurements with DIC for wire and arc additive manufacturing (WAAM) is presented emphasizing opportunities, challenges and solutions.publishersversionpublishe

Micro wire and arc additive manufacturing (µ-WAAM)

Publisher Copyright: © 2022 The Author(s) This activity has received funding from the European Institute of Innovation and Technology (EIT) – Project Smart WAAM: Microstructural Engineering and Integrated NonDestructive Testing. This body of the European Union receives support from the European Union’s Horizon 2020 research and innovation program.In this work we explore the wire and arc additive manufacturing (WAAM) process scale limits by using a wire diameter of 250 µm and about 2 mm stickout. This WAAM variant, named µ-WAAM, aims at competing with laser powder bed fusion technology, by enabling the fabrication of smaller parts with significantly higher deposition rates. The main issues of descaling the WAAM process are discussed and an acceptable parameter window to fabricate thin walls is presented. Several depositions were successfully performed with ASTMA 228 steel using a wire feed speed ranging from 75 to 90 mm/s, travel speed from 7 to 10 mm/s, a current intensity of 16 A RMS and power of ≈ 35 W RMS.publishersversionpublishe

Garnet-biotite diffusion mechanisms in complex high-grade orogenic belts : understanding and constraining petrological cooling rates in granulites from Ribeira Fold Belt (SE Brazil)

Cooling rates based on the retrograde diffusion of Fe2+ and Mg between garnet and biotite inclusions commonly show two contrasting scenarios: a) narrow closure temperature range with apparent absence of retrograde diffusion; or b) high result dispersion due to compositional variations in garnet and biotite. Cooling rates from migmatites, felsic and mafic granulites from Ribeira Fold Belt (SE Brazil) also show these two scenarios. Although the former can be explained by very fast cooling, the latter is often the result of open-system behaviour caused by deformation. Retrogressive cooling during the exhumation of granulite-facies rocks is often processed by thrusting and shearing which may cause plastic deformation, fractures and cracks in the garnet megablasts, allowing chemical diffusion outside the garnet megablast – biotite inclusion system. However, a careful use of garnets and biotites with large Fe/Mg variation and software that reduces result dispersion provides a good correlation between closure temperatures and the size of biotite inclusions which are mostly due to diffusion and compositional readjustment to thermal evolution during retrogression. Results show that felsic and mafic granulites have low cooling rates (1–2 °C/Ma) at higher temperatures and high cooling rates (~100 °C/Ma) at lower temperatures, suggesting a two-step cooling/exhumation process, whereas migmatites show a small decrease in cooling rates during cooling (from 2.0 to 0.5 °C/Ma). These results agree with previously obtained thermochronological data, which indicates that this method is a valid tool to obtain meaningful petrological cooling rates in complex high-grade orogenic belts, such as the Ribeira Fold Belt

Automatic defect detection in fiber-reinforced polymer matrix composites using thermographic vision data

Authors acknowledge Fundação para a Ciência e a Tecnologia (FCT - MCTES) for its financial support via the project UIDB/EMS/00667/2020 (UNIDEMI).The detection of internal defects, not visible to the naked eye from the outside of materials, using non-destructive testing (NDT) are increasingly requested by industrial processes. This study proposes a novel methodology for acquisition and processing of images from a thermographic camera using computer vision methods to test composite materials made of a polymer matrix reinforced with glass, carbon, and kevlar fibers. The image is acquired while cooling the sample, following a suggested procedure. The processing methodology is divided into three steps, image pre-processing, image processing, and data post-processing. In image preprocessing, filters are applied to improve image quality, and methods are proposed to segment and identify the region of interest. In image processing, a blob analysis method is suggested for defect identification, isolation and characterization. A data analysis method is proposed for the post-processing step to characterize the defects identified in the previous step. Samples with known defects in terms of size, geometry, and location were used to test the developed system. The system showed high performance, achieving 98% accuracy, and suitability for defect detection larger than 0.5 mm in thickness and 600 mm2 in area. The experimental results showed that the algorithm did not detect any false positives, and that the type of reinforcement used in the analyzed samples had no influence on the results. On the other hand, the depth of the delaminations had an influence on the pixel intensity contrast of the defect region, and its instant of maximum contrast. The lesser the depth of the defects detected, the higher the value of their intensity and the shorter the instant of maximum contrast.publishersversionpublishe

Deep Learning Framework for Controlling Work Sequence in Collaborative Human–Robot Assembly Processes

project UIDB/EMS/00667/2020 (UNIDEMI)The human–robot collaboration (HRC) solutions presented so far have the disadvantage that the interaction between humans and robots is based on the human’s state or on specific gestures purposely performed by the human, thus increasing the time required to perform a task and slowing down the pace of human labor, making such solutions uninteresting. In this study, a different concept of the HRC system is introduced, consisting of an HRC framework for managing assembly processes that are executed simultaneously or individually by humans and robots. This HRC framework based on deep learning models uses only one type of data, RGB camera data, to make predictions about the collaborative workspace and human action, and consequently manage the assembly process. To validate the HRC framework, an industrial HRC demonstrator was built to assemble a mechanical component. Four different HRC frameworks were created based on the convolutional neural network (CNN) model structures: Faster R-CNN ResNet-50 and ResNet-101, YOLOv2 and YOLOv3. The HRC framework with YOLOv3 structure showed the best performance, showing a mean average performance of 72.26% and allowed the HRC industrial demonstrator to successfully complete all assembly tasks within a desired time window. The HRC framework has proven effective for industrial assembly applicationspublishersversionpublishe

Comparison of three control theories for single-phase active power filters

Active Power Filters have been developed in last years, mostly for three-phase systems applications. The use of Shunt Active Power Filters on single-phase facilities brings many benefits for the electrical grid, since these installations have non linear loads and power factor problems, and in their total, they are responsible by a significant portion of the total electric energy consumption. Harmonics and reactive power consumed by single-phase installations cause additional power losses on the electrical grid. So, mitigate harmonics at the origin helps reducing these extra losses and other problems caused by the harmonics. The drawback of this solution is the necessity of a large number of Active Power Filters distributed by the generality of the single-phase facilities. So, it becomes necessary a simple and low cost Shunt Active Power Filter to install on single-phase installations. This paper presents three simple control theories to use on single-phase Shunt Active Power Filters. Simulation and experimental results comparing the three different control theories are presented and analyzed.Fundação para a Ciência e a Tecnologia (FCT

Assumptions and problems with Fe-Mg garnet - biotite diffusion based petrological cooling rates : a case study in granulites and migmatites from central Ribeira Fold Belt, SE Brazil

O sector São Fidelis - Santo António de Pádua, pertencente à zona central da Faixa Ribeira, é fundamentalmente composto por migmatites, granulitos e blasmilonitos. A aplicação de diferentes metodologias com o objectivo de obetr taxas de arrefecimento baseadas na difusão Fe-Mg entre granada e respectivas inclusões de biotite revelou-se infrutífera. Tal deve-se fundamentalmente a: a) elevada dispersão dos resultados causada pela existência de um sistema aberto; b) estreita variação das temperaturas de fecho do sistema causada por re-homogeneização da granada e altas temperaturas seguida de arrefecimento muito rápido. Os resultados obtidos são fundamentalmente qualitativos, mas estão de acordo com resultados termocronológicos previamente obtidos baseados na integração de múltiplos sistemas isotópicos

C-O-H isotopic evidences for fluid sources of granulites in Ribeira Belt, SE Brazil

Publicado em: Geochemica et Cosmochimica Acta, Vol. 72, issue 12, Suppl. 1, A7