Qualification of channels produced by laser powder bed fusion: Analysis of cleaning methods, flow rate and melt pool monitoring data

Kolb, Tobias; Mahr, Alexander; Huber, Florian; Tremel, Jan; Schmidt, Michael

doi:10.1016/j.addma.2018.11.026

Cited by 11 publications

(5 citation statements)

References 7 publications

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“…The laser power results of all measured positions were found inside a 5 per cent tolerance band. A M2 cusing dual-laser system with a melt-pool monitoring system QM-Meltpool 3D was used; see Kolb et al (2018b) for further details and Figure 1. For camera image analysis, an additional PC with a frame grabber for image transfer and a RAID 0 system for fast data storage was used.…”

Section: Methodsmentioning

confidence: 99%

Camera signal dependencies within coaxial melt pool monitoring in laser powder bed fusion

Kolb

Elahi

Seeger

et al. 2020

RPJ

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Purpose The purpose of this paper is to analyse the signal dependency of the camera-based coaxial monitoring system QMMeltpool 3D (Concept Laser GmbH, Lichtenfels, Germany) for laser powder bed fusion (LPBF) under the variation of process parameters, position, direction and layer thickness to determine the capability of the system. Because such and similar monitoring systems are designed and presented for quality assurance in series production, it is important to present the dominant signal influences and limitations. Design/methodology/approach Hardware of the commercially available coaxial monitoring QMMeltpool 3D is used to investigate the thermal emission of the interaction zone during LPBF. The raw images of the camera are analysed by means of image processing to bypass the software of QMMeltpool 3D and to gain a high level of signal understanding. Laser power, scan speed, laser spot diameter and powder layer thickness were varied for single-melt tracks to determine the influence of a parameter variation on the measured sensory signals. The effects of the scan direction and position were also analysed in detail. The influence of surface roughness on the detected sensory signals was simulated by a machined substrate plate. Findings Parameter variations are confirmed to be detectable. Because of strong directional and positional dependencies of the melt-pool monitoring signal a calibration algorithm is necessary. A decreasing signal is detected for increasing layer thickness. Surface roughness is identified as a dominating factor with major influence on the melt-pool monitoring signal exceeding other process flaws. Research limitations/implications This work was performed with the hardware of a commercially available QMMeltpool 3D system of an LPBF machine M2 of the company Concept Laser GmbH. The results are relevant for all melt-pool monitoring research activities connected to LPBF, as well as for end users and serial production. Originality/value Surface roughness has not yet been revealed as being one of the most important origins for signal deviations in coaxial melt-pool monitoring. To the best of the authors’ knowledge, the direct comparison of influences because of parameters and environment has not been published to this extent. The detection, evaluation and remelting of surface roughness constitute a plausible workflow for closed-loop control in LPBF.

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Section: Methodsmentioning

confidence: 99%

Camera signal dependencies within coaxial melt pool monitoring in laser powder bed fusion

Kolb

Elahi

Seeger

et al. 2020

RPJ

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“…AM process modelling tools and process in-situ inspection are suggested to be an important part of future process development and control [17]. Although promising, these tools are still in their infancy and require further development and demonstration [65,66]. Future qualification approaches could hence have increased dependence of process modelling and in-situ inspection, which is not contradicted by the Design for Qualification framework.…”

Section: Verification Phase (Tactic 3 4 and 5)mentioning

confidence: 99%

A Design for Qualification Framework for the Development of Additive Manufacturing Components—A Case Study from the Space Industry

Dordlofva

2020

Aerospace

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Additive Manufacturing (AM) provides several benefits for aerospace companies in terms of efficient and innovative product development. However, due to the general lack of AM process understanding, engineers face many uncertainties related to product qualification during the design of AM components. The aim of this paper is to further the understanding of how to cope with the need to develop process understanding, while at the same time designing products that can be qualified. A qualitative action research study has been performed, using the development of an AM rocket engine turbine demonstrator as a case study. The results show that the qualification approach should be developed for the specific application, dependent on the AM knowledge within the organization. AM knowledge is not only linked to the AM process but to the complete AM process chain. Therefore, it is necessary to consider the manufacturing chain during design and to develop necessary knowledge concurrently with the product in order to define suitable requirements. The paper proposes a Design for Qualification framework, supported by six design tactics. The framework encourages proactive consideration for qualification and the capabilities of the AM process chain, as well as the continuous development of AM knowledge during product development.

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“…This chapter aimed to increase the level of detail, reduce the amount of saturation, and highlight edge features in melt pool images. Melt pool monitoring and melt pool width dimensioning has proved to be an incredibly useful tool in advancing AM capabilities [10,17,[23][24][25][26][27][28][29][30][31][32][33][34][43][44][45][46][47][48][49][50][51][52][53][54][55][56][57][58], so it is of high importance that these techniques are accurate and provide high quality melt pool images.…”

Section: Discussionmentioning

confidence: 99%

“…An abundance of literature details the use of visual, NIR, IR and/or thermal cameras to monitor the melt pool phenomena [10,17,[23][24][25][26][27][28][29][30][31][32][33][34][43][44][45][46][47][48][49][50][51][52][53][54][55][56][57][58], with a certain literature focusing on specifically melt pool dimensions [10,[27][28][29][30][31][32][33][43][44][45][46][47].…”

Section: Melt Event Monitoringmentioning

confidence: 99%

“…Multiple research papers have eradicated the measurement of melt pool dimensions in their system and have instead introduced techniques that measure melting event signals, splatters, and/or signatures throughout AM builds [48][49][50][51][52][53][54][55][56][57][58]. The premise of this technique is that different melting event signals are shown depending on the condition of the melt event.…”

Section: Melt Event Monitoringmentioning

confidence: 99%

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Improved Melt Pool Monitoring Systems for Direct energy Deposition Processes

Sampson¹

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Qualification of channels produced by laser powder bed fusion: Analysis of cleaning methods, flow rate and melt pool monitoring data

Cited by 11 publications

References 7 publications

Camera signal dependencies within coaxial melt pool monitoring in laser powder bed fusion

Camera signal dependencies within coaxial melt pool monitoring in laser powder bed fusion

A Design for Qualification Framework for the Development of Additive Manufacturing Components—A Case Study from the Space Industry

Improved Melt Pool Monitoring Systems for Direct energy Deposition Processes

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