A Framework for Additive Manufacturing Process Monitoring &amp; Control

Cummings, Ian; Bax, Megan E.; Fuller, Ivan J.; Wachtor, Adam J.; Bernardin, John D.

doi:10.1007/978-3-319-54810-4_14

Cited by 11 publications

(7 citation statements)

References 6 publications

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“…Some research groups used ultrasonic sensors to analyze the part structures. Reflections of high-frequency pulses exerted onto the part were analyzed based on the duration until detection [229][230][231][232][233]. Another relevant approach is the use of encoders to determine the axis positions and to implement closed-loop control of the axis movement.…”

Section: Other Sensor Technologiesmentioning

confidence: 99%

Process monitoring for material extrusion additive manufacturing: a state-of-the-art review

et al. 2021

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Qualitative uncertainties are a key challenge for the further industrialization of additive manufacturing. To solve this challenge, methods for measuring the process states and properties of parts during additive manufacturing are essential. The subject of this review is in-situ process monitoring for material extrusion additive manufacturing. The objectives are, first, to quantify the research activity on this topic, second, to analyze the utilized technologies, and finally, to identify research gaps. Various databases were systematically searched for relevant publications and a total of 221 publications were analyzed in detail. The study demonstrated that the research activity in this field has been gaining importance. Numerous sensor technologies and analysis algorithms have been identified. Nonetheless, research gaps exist in topics such as optimized monitoring systems for industrial material extrusion facilities, inspection capabilities for additional quality characteristics, and standardization aspects. This literature review is the first to address process monitoring for material extrusion using a systematic and comprehensive approach.

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Section: Other Sensor Technologiesmentioning

confidence: 99%

Process monitoring for material extrusion additive manufacturing: a state-of-the-art review

et al. 2021

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“…Wu and coauthors [40][41][42][43][44] employed the acoustic emission technique to identify normal and abnormal states of machine conditions. Other techniques used in monitoring the FFF process include augmented reality technique [45], ultrasonic inspection technique [46], fiber Bragg grating sensor [47], and laser triangulation system [48].…”

Section: Additive Manufacturing Process Monitoringmentioning

confidence: 99%

Physics-Based Compressive Sensing to Enable Digital Twins of Additive Manufacturing Processes

Shevtshenko

Wang

2021

Journal of Computing and Information Science in Engineering

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Sensors play an important role in monitoring manufacturing processes and update their digital twins. However, the data transmission bandwidth and sensor placement limitations in the physical systems may not allow us to collect the amount or the type of data that we wish. Recently, a physics based compressive sensing (PBCS) approach was proposed to monitor manufacturing processes and obtain high-fidelity information with the reduced number of sensors by incorporating physical models of processes in compressed sensing. It can recover and reconstruct complete three-dimensional temperature distributions based on some limited measurements. In this paper, a constrained orthogonal matching pursuit algorithm is developed for PBCS, where coherence exists between the measurement matrix and basis matrix. The efficiency of recovery is improved by introducing a boundary-domain reduction approach, which reduces the size of PBCS model matrices during the inverse operations. The improved PBCS method is demonstrated with the measurement of temperature distributions in the cooling and real-time printing processes of fused filament fabrication.

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“…The obtained signals were analyzed by several approaches, but the results were not ideal. Cummings et al 25 attempted to realize a control feedback framework for the FDM process. Disabling the cooling fan resulted in a repeatable and visually detectable fault that the extruded layers before could not cool down and solidify enough to support the new extruded layers.…”

Section: Introductionmentioning

confidence: 99%

Real-time distortion monitoring during fused deposition modeling via acoustic emission

Feng

Yang

et al. 2019

Structural Health Monitoring

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Fused deposition modeling is a popular technique for three-dimensional prototyping since it is cost-effective, convenient to operate, and environment-friendly. However, the low quality of its printed products jeopardizes its future development. Distortion, also known as warping deformation, which is caused by many factors such as inappropriate process parameters and process drifts, is one of the most common defects in the fused deposition modeling process. Rapid detection of such part distortion during the printing process is beneficial for improving the production efficiency and saving materials. In this article, a real-time part distortion monitoring method based on acoustic emission is presented. Our work is to identify distortion defects and understand the condition of the distortion area through sensing and digital signal processing techniques. In our experiments, both the acoustic emission hits and original signals were acquired during the fused deposition modeling process. Then, the acoustic emission hits were analyzed. Ensemble empirical mode decomposition was utilized to eliminate noise and extract features from the original acoustic emission signal to further analyze the acoustic emission signal in the case of part distortion. Furthermore, the root mean square of the reconstructed signals was calculated, and the prediction results are strongly correlated with the ground truth printing states. This work provides a promising method for the quality diagnosis of printing parts.

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A Framework for Additive Manufacturing Process Monitoring & Control

Cited by 11 publications

References 6 publications

Process monitoring for material extrusion additive manufacturing: a state-of-the-art review

Process monitoring for material extrusion additive manufacturing: a state-of-the-art review

Physics-Based Compressive Sensing to Enable Digital Twins of Additive Manufacturing Processes

Real-time distortion monitoring during fused deposition modeling via acoustic emission

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