Detecting first layer bond quality during FDM 3D printing using a discrete wavelet energy approach

Bhavsar, Pavan; Sharma, Bhisham; Moscoso-Kingsley, Wilfredo; Madhavan, Viswanathan

doi:10.1016/j.promfg.2020.05.104

Cited by 21 publications

(3 citation statements)

References 16 publications

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“…Problems caused by the failure of the first layer are commonly referred to as "First layer problems" or "First layer issues". This is arguably the biggest problem bothering all FDM 3D printer users [ 16 ]. Filaments are prone to deformation due to prolonged exposure to heat from the build plate during 3D printing, with ABS filaments being particularly prone to this.…”

Section: Discussionmentioning

confidence: 99%

Fused Deposition Modeling 3D Printing in Oral and Maxillofacial Surgery: Problems and Solutions

Kamio¹,

Onda²

2022

Cureus

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Three-dimensional (3D) printing technology in medicine is one of the new and innovative technology for fabricating 3D models of complex anatomical structures that can be observed both visually and haptically. Patient-specific 3D models fabricated through this process are currently being used for various purposes, including surgical simulation, training, and medical education. Most of the personal use/low-end desktop 3D printers that are becoming widespread are fused deposition modeling (FDM) 3D printers. Compared to professional/high-end 3D printers, the price of the personal use/low-end desktop FDM 3D printer itself, filament, and running costs are lower; it can lower the economic bottleneck for introducing 3D printing technology into clinical practice, such as surgical simulation. With a desktop FDM 3D printer and a general-purpose PC, anyone can now rapidly fabricate 3D models on their own without having to rely on 3D printing labs and specialized technicians. However, it is also true that FDM 3D printers, due to their mechanical characteristics, encounter many difficulties and problems that emerge during the 3D printing process. Knowledge, know-how, and tips about FDM 3D printers have been introduced in various media, and it has become easy to know about them worldwide via the Internet. However, there has been no comprehensive technical review to date to produce osseous 3D models for use in oral and maxillofacial surgery. In this report, to create 3D models according to the characteristics of maxillofacial and oral surgery, we enable surgeons themselves to create 3D models smoothly by presenting ideas for CT scanning, points to note when exporting Digital Imaging and Communications in Medicine (DICOM) image data, how to create optimal stereolithography (STL) models, and problems and solutions for 3D printing.

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Section: Discussionmentioning

confidence: 99%

Fused Deposition Modeling 3D Printing in Oral and Maxillofacial Surgery: Problems and Solutions

Kamio¹,

Onda²

2022

Cureus

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“…In detection, non-destructive testing is a widely employed method in FDM 3D printing, where error detection mechanisms using cameras provide feasibility for remote supervision and early fault detection [9]. Bhavsar et al [10] utilized discrete wavelet transform to analyze the differences in vibration acoustic signals of sensors during FDM 3D printing, aiming to detect the rst layer lament deposition process, thereby achieving detection of rst layer bonding quality. Machine learning nds extensive application in defect detection, as demonstrated by Lopes et al [11], who employed piezoelectric microphones, support vector machines (SVMs), and neural networks for machine state monitoring in FDM 3D printing.…”

Section: Introductionmentioning

confidence: 99%

Real-time defect detection for FDM 3D printing using lightweight model deployment

Hu,

Chang,

et al. 2024

Preprint

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FDM 3D printing is one of the most widely used additive manufacturing methods, bringing great convenience to production manufacturing. However, various printing defects may occur during the printing process due to human factors or printer-related issues. Timely detection of defects and halting printing becomes a scenario of significant practical importance. This paper first analyzes the causes of the five most common defects in FDM 3D printing, and a defect dataset is created by deliberately designing defects. Subsequently, a real-time defect detection system for FDM 3D printing, based on an improved YOLOv8 detection head, is developed. By employing an optimization method using Group Convolution to share parameters, the detection head is lightweight, resulting in better model performance. Experimental results demonstrate that the mAP50 of the improved YOLOv8 model reaches 97.5%, with an 18.1% increase in FPS and a 32.9% reduction in GFLOPs. This enhancement maintains comparable detection accuracy to the original model while achieving faster detection speed and lower computational requirements. The improved model is integrated into the detection system as the detection model, and through testing, the real-time detection system promptly and accurately identifies and alerts any occurring defects. The practical significance of this system lies in its ability to enhance production efficiency, reduce resource wastage due to defective printing, and improve product quality and manufacturing safety, thereby providing strong support for the application of visual inspection technology in FDM 3D printing.

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“… Add material just where it is needed -Although this element is discussed in various areas of the design guide, it is essential to highlight the importance of changing the mindset. Parts with large areas of solid volume are more prone to distortion, and the layer time increases, and therefore the strength is reduced (Bhavsar et al, 2020).…”

Section: Optimisationmentioning

confidence: 99%

Analysis to Support Design for Additive Manufacturing with Desktop 3D Printing

Vicente¹

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Detecting first layer bond quality during FDM 3D printing using a discrete wavelet energy approach

Cited by 21 publications

References 16 publications

Fused Deposition Modeling 3D Printing in Oral and Maxillofacial Surgery: Problems and Solutions

Fused Deposition Modeling 3D Printing in Oral and Maxillofacial Surgery: Problems and Solutions

Real-time defect detection for FDM 3D printing using lightweight model deployment

Analysis to Support Design for Additive Manufacturing with Desktop 3D Printing

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