Filament Breakage Monitoring in Fused Deposition Modeling Using Acoustic Emission Technique

Yang, Zhensheng; Li, Jin; Yan, Youruiling; Yiming, Mei

doi:10.3390/s18030749

Cited by 47 publications

(15 citation statements)

References 25 publications

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“…The main limitation of this technology is the limited range of filaments commercially available. Moreover, the quality of printing can be disturbed by issues such as filament break, filament thickness, and length . However, novel technologies, capable of printing raw materials from pellets and also of heating the receiving support or substrate, are now on the market.…”

Section: Introductionmentioning

confidence: 99%

“…3D printing or polymer additive manufacturing (PAM) could be a solution to overcome this limitation. 1 Several 3D techniques have emerged these last years, such as (a) fused deposition modeling (FDM) ( Figure 1A) [1][2][3][4] ; selective laser sintering ( Figure 1B), which uses a laser as the power source to sinter and bind powdered material to create a solid structure, [5][6][7] and (b) stereolitography apparatus (SLA; with liquid or powder), 8 which is based on photopolymerization and therefore using light to link chains of molecules, forming polymers and thus making up a three dimensional solid ( Figure 1C). Among these technologies, FDM presents the best quality to cost ratio.…”

mentioning

confidence: 99%

“…Moreover, the quality of printing can be disturbed by issues such as filament break, filament thickness, and length. 2,4 However, novel technologies, capable of printing raw materials from pellets and also of heating the receiving support or substrate, 9 are now on the market. It has therefore many advantages compared to the technology using filaments, and this technique was used in this work.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Additive manufacturing of fire‐retardant ethylene‐vinyl acetate

Geoffroy

Samyn

Jimenez

et al. 2019

Polymers for Advanced Techs

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Thermocompression (with also extrusion and injection molding) is a classical polymer shaping manufacturing, but it does not easily allow designing sophisticated shapes without using a complex mold, on the contrary to 3D printing (or polymer additive manufacturing), which is a very flexible technique. Among all 3D printing techniques, fused deposition modeling is of high potential for product manufacturing, with the capability to compete with conventional polymer processing techniques. This is a quite low cost 3D printing technique, but the range of filaments commercially available is limited. However, in some specific 3D printing processes, no filaments are necessary. Polymers pellets feed directly the printing nozzle allowing to investigate many polymeric matrices with no commercial limitation. This is of high interest for the design of flame‐retarded materials, but literature is scarce in that field. In this paper, a comparison between thermocompression and 3D printing processes was performed on both neat ethylene‐vinyl acetate (EVA) copolymer and EVA flame retarded with aluminum triHydroxyde (ATH) containing different loadings (30 or 65 wt%) and with expandable graphite (EG), ie, EVA/ATH (30 wt%), EVA/ATH (65 wt%), and EVA/EG (10 wt%), respectively. Morphological comparisons, using microscopic and electronic microprobe analyses, revealed that 3D printed plates have lower apparent density and higher porosity than thermocompressed plate. The fire‐retardant properties of thermocompressed and 3D printed plates were then evaluated using mass loss calorimeter test at 50 kW/m2. Results highlight that 3D printing can be used to produce flame‐retardant systems. This work is a pioneer study exploring the feasibility of using polymer additive manufacturing technology for designing efficient flame‐retarded materials.

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Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Additive manufacturing of fire‐retardant ethylene‐vinyl acetate

Geoffroy

Samyn

Jimenez

et al. 2019

Polymers for Advanced Techs

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“…Accelerometers, thermocouples, infrared temperature sensor, video borescope were used to monitor the quality of 3D printed parts, and most optimal parameters of feed/flow ratio, extruder temperature, and layer height were recommended for better dimensional accuracy and surface roughness [28,29]. Acoustic emission monitoring technique was used to detect such 3D printing process errors as semiblocked extruder, completely blocked extruder, and run out of the material [30], and filament breakage [31]. Orientation, motion, hygrometry, temperature, and vibration sensors were utilised to track printing and not printing conditions in FDM [32].…”

Section: Introductionmentioning

confidence: 99%

A dynamic model for current-based nozzle condition monitoring in fused deposition modelling

Tlegenov

Hong

2019

Prog Addit Manuf

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3D printing and particularly fused deposition modelling (FDM) is widely used for prototyping and fabricating low-cost customised parts. However, present fused deposition modelling 3D printers have limited nozzle condition monitoring techniques to minimize nozzle clogging errors. Nozzle clogging is one of the significant process errors in fused deposition modelling 3D printers, and it affects the quality of prototyped parts in terms of mechanical properties and geometrical accuracy. This paper proposes a dynamic model for current-based nozzle condition monitoring in fused deposition modelling, which is briefly described as follows. First, all the process forces in filament extrusion of the fused deposition modelling were identified and derived theoretically, and theoretical equations of the feed rolling forces and flow-through-nozzle forces were derived. In addition, the effect of the nozzle clogging on the current of extruding motor were identified. Second, based on the proposed dynamic model, current-based nozzle condition monitoring method was proposed. Next, sets of experiments on FDM machine using polylactic acid (PLA) material were carried out to verify the proposed theoretical model, and the results were analysed and evaluated. Findings of the present study indicate that nozzle clogging in FDM 3D printing can be monitored by sensing the current of the filament extruding motor. The proposed model can be used efficiently for monitoring nozzle clogging conditions in fused deposition modelling 3D printers as it is based on the fundamental process modelling.

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“…Several methods are currently under development for reliable in-situ monitoring based on the sensors for defect detection and location [8,9,10,11,12,13,14,15,16]. The sensors applied for in-situ monitoring during the FFF process contain acoustic emission (AE) [8], accelerometer sensors [10], infrared temperature sensors [11], fiber Bragg grating (FBG) sensors [15], visual camera [16], and more.…”

Section: Introductionmentioning

confidence: 99%

In-Situ Monitoring and Diagnosing for Fused Filament Fabrication Process Based on Vibration Sensors

Zhao

et al. 2019

Sensors

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Fused filament fabrication (FFF) is one of the most widely used additive manufacturing (AM) technologies and it has great potential in fabricating prototypes with complex geometry. For high quality manufacturing, monitoring the products in real time is as important as maintaining the FFF machine in the normal state. This paper introduces an approach that is based on the vibration sensors and data-driven methods for in-situ monitoring and diagnosing the FFF process. The least squares support vector machine (LS-SVM) algorithm has been applied for identifying the normal and filament jam states of the FFF machine, besides fault diagnosis in real time. The identification accuracy for the case studies explored here using LS-SVM is greater than 90%. Furthermore, to ensure the product quality during the FFF process, the back-propagation neural network (BPNN) algorithm has been used to monitor and diagnose the quality defects, as well as the warpage and material stack caused by abnormal leakage for the products in-situ. The diagnosis accuracy for the case studies explored here using BPNN is greater than 95%. Results from the experiments show that the proposed approach can accurately recognize the machine failures and quality defects during the FFF process, thus effectively assuring the product quality.

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Filament Breakage Monitoring in Fused Deposition Modeling Using Acoustic Emission Technique

Cited by 47 publications

References 25 publications

Additive manufacturing of fire‐retardant ethylene‐vinyl acetate

Additive manufacturing of fire‐retardant ethylene‐vinyl acetate

A dynamic model for current-based nozzle condition monitoring in fused deposition modelling

In-Situ Monitoring and Diagnosing for Fused Filament Fabrication Process Based on Vibration Sensors

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