Referencing of powder bed for in situ detection of lateral layer displacements in additive manufacturing

Abstract. An increasing number of additive manufacturing (AM) applications leads to rising challenges for the process-accompanying quality assurance. Beside post-processing measurement systems, in situ monitoring systems in particular are currently requested to ensure feedback controlling during AM processes. For data acquisition and subsequent evaluation, a high data quality is of importance. It depends on a high resolution and accuracy of measurement systems, adapted measurement conditions and a reference to the powder bed or component for geometric measurements. Within this scientific study, a new reference system has been implemented into the powder bed to reduce measurement deviations by an abbreviated metrological loop. After data acquisition and image processing layer by layer, the position stability of the reference system has been analysed in relation to the optical measuring system. Based on a contour detection of the reference markers, the evaluation of geometrical process deviations is presented as an essential basis for a closed-loop controlling system. Thermally induced and mechanical drifts within the manufacturing process can be verified by the reference system in the powder bed. As an outlook, two methods are suggested for a process-accompanying referenced detection of the melting pool and resulting contour displacements during additive manufacturing.

Download Full-text

Methods and procedure of referenced in situ control of lateral contour displacements in additive manufacturing

Journal of Sensors and Sensor Systems ◽

10.5194/jsss-10-219-2021 ◽

2021 ◽

Vol 10 (2) ◽

pp. 219-232

Author(s):

Martin Lerchen ◽

Jakob Hornung ◽

Yu Zou ◽

Tino Hausotte

Keyword(s):

Additive Manufacturing ◽

Measurement Data ◽

Detection Algorithm ◽

Contour Detection ◽

Layer By Layer ◽

Powder Bed ◽

In Situ Control ◽

Melting Pool ◽

Lateral Displacements

Abstract. Additive manufacturing technologies are further developing from prototype to serial production. This trend requires rising challenges to the process-accompanying quality assurance. Optical in situ quality control approaches show great potential to generate accurate measurement data, which are essential for feedback control. If a reliable referencing concept for the layer-by-layer measured data is guaranteed, contour information can be used during the manufacturing to correct occurring geometrical deviations. Within this scientific study, two methods of optical, referenced in situ control of lateral displacements of additive manufactured contours are presented. In the first approach the 2-D contour of the melting pool is analysed in relation to a position-stable reference system implemented in the powder bed. The second approach uses the translucent contour of deeper layers covered with powder as a reference. Within the image evaluation several pre-processing steps like calibration, undistortion, rectification, illumination correction and low-pass filtering are essential for reliable and correct geometric measurements. The following adapted contour detection and position determination of the referenced melting pool contours are based on an extended edge detection algorithm according to Canny (1986). With the evaluation of further manufacturing layers of already lowered powder bed levels, it is possible to specify the influence of powder application on geometrical displacements separately. This is done by a comparison of the position of the detected powder-covered melting pool contours with the previously applied melted region. Consequently a better understanding of lateral contour displacements within the additive manufacturing process is the goal, which is important for a process-accompanying correction of geometrical deviations.

Download Full-text

Correlation between surface texture and internal defects in laser powder-bed fusion additive manufacturing

Scientific Reports ◽

10.1038/s41598-021-02240-z ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Makiko Yonehara ◽

Chika Kato ◽

Toshi-Taka Ikeshoji ◽

Koki Takeshita ◽

Hideki Kyogoku

Keyword(s):

Additive Manufacturing ◽

Surface Texture ◽

In Situ Monitoring ◽

Mean Square ◽

Powder Bed Fusion ◽

Internal Defects ◽

Powder Bed ◽

Texture Parameters ◽

Areal Surface

AbstractThe availability of an in-situ monitoring and feedback control system during the implementation of metal additive manufacturing technology ensures that high-quality finished parts are manufactured. This study aims to investigate the correlation between the surface texture and internal defects or density of laser-beam powder-bed fusion (LB-PBF) parts. In this study, 120 cubic specimens were fabricated via application of the LB-PBF process to the IN 718 Ni alloy powder. The density and 35 areal surface-texture parameters of manufactured specimens were determined based on the ISO 25,178–2 standard. Using a statistical method, a strong correlation was observed between the areal surface-texture parameters and density or internal defects within specimens. In particular, the areal surface-texture parameters of reduced dale height, core height, root-mean-square height, and root-mean-square gradient demonstrate a strong correlation with specimen density. Therefore, in-situ monitoring of these areal surface-texture parameters can facilitate their use as control variables in the feedback system.

Download Full-text

In-Situ monitoring and modeling of metal additive manufacturing powder bed fusion

10.1063/1.5031504 ◽

2018 ◽

Cited By ~ 2

Author(s):

Jacob Alldredge ◽

John Slotwinski ◽

Steven Storck ◽

Sam Kim ◽

Arnold Goldberg ◽

...

Keyword(s):

Additive Manufacturing ◽

In Situ Monitoring ◽

Powder Bed Fusion ◽

Powder Bed ◽

Metal Additive Manufacturing ◽

Metal Additive

Download Full-text

In-Situ Process Monitoring in Additive Manufacturing Using Statistics and Pre-Process Data

Tehnički glasnik ◽

10.31803/tg-20200526143210 ◽

2020 ◽

Vol 14 (2) ◽

pp. 180-185

Author(s):

Eva Maria Scheideler ◽

Andrea Huxol

Keyword(s):

Additive Manufacturing ◽

Performance Indicator ◽

In Situ Monitoring ◽

Research Approach ◽

Process Data ◽

Fast Analysis ◽

Powder Bed ◽

Control Value ◽

And Control

Long computation times are a major obstacle for the application of in-situ monitoring in additive manufacturing. This paper presents rapid in-situ monitoring, which returns a control value within typical build times. Observing powder bed fusion processes reveals that unsuitable parameter settings influence the appearance of the molten surface and the surrounding powder bed. The presented research approach evaluates the changing appearance of the exposed layers, in combination with the information from the preprocess about the position and geometry of the components in each layer. Grayscale images are captured with the build envelope camera and examined regarding the grayscale distribution in the critical areas surrounding the component boundaries. The grayscale distribution is then used to predict product quality by using standard statistical methods. The combination of the pre-process data and the fast analysis of the grayscale distribution allows promptly calculating a performance indicator for required process intervention and control.

Download Full-text

In Situ Additive Manufacturing Process Monitoring With an Acoustic Technique: Clustering Performance Evaluation Using K-Means Algorithm

Journal of Manufacturing Science and Engineering ◽

10.1115/1.4042786 ◽

2019 ◽

Vol 141 (4) ◽

Cited By ~ 8

Author(s):

Hossein Taheri ◽

Lucas W. Koester ◽

Timothy A. Bigelow ◽

Eric J. Faierson ◽

Leonard J. Bond

Keyword(s):

Additive Manufacturing ◽

Process Monitoring ◽

Manufacturing Process ◽

Clustering Algorithm ◽

In Situ Monitoring ◽

Process Conditions ◽

Layer By Layer ◽

Acoustic Signatures ◽

Acoustic Technique

Additive manufacturing (AM) is based on layer-by-layer addition of materials. It gives design flexibility and potential to decrease costs and manufacturing lead time. Because the AM process involves incremental deposition of materials, it provides unique opportunities to investigate the material quality as it is deposited. Development of in situ monitoring methodologies is a vital part of the assessment of process performance and understanding of defects formation. In situ process monitoring provides the capability for early detection of process faults and defects. Due to the sensitivity of AM processes to different factors such as laser and material properties, any changes in aspects of the process can potentially have an impact on the part quality. As a result, in-process monitoring of AM is crucial to assure the quality, integrity, and safety of AM parts. There are various sensors and techniques that have been used for in situ process monitoring. In this work, acoustic signatures were used for in situ monitoring of the metal direct energy deposition (DED) AM process operating under different process conditions. Correlations were demonstrated between metrics and various process conditions. Demonstrated correlation between the acoustic signatures and the manufacturing process conditions shows the capability of acoustic technique for in situ monitoring of the additive manufacturing process. To identify the different process conditions, a new approach of K-means statistical clustering algorithm is used for the classification of different process conditions, and quantitative evaluation of the classification performance in terms of cohesion and isolation of the clusters. The identified acoustic signatures, quantitative clustering approach, and the achieved classification efficiency demonstrate potential for use in in situ acoustic monitoring and quality control for the additive manufacturing process.

Download Full-text

A Simple Calibration Method for A Fringe Projection System Embedded within An Additive Manufacturing Machine

Machines ◽

10.3390/machines9090200 ◽

2021 ◽

Vol 9 (9) ◽

pp. 200

Author(s):

Yue Liu ◽

Liam Blunt ◽

Feng Gao ◽

Xiangqian Jiang

Keyword(s):

Additive Manufacturing ◽

Manufacturing Process ◽

Calibration Method ◽

Fringe Projection ◽

Projection System ◽

Powder Bed ◽

Measurement Systems ◽

Measurement Resolution ◽

Manufacturing Machine

In additive manufacturing (AM), especially for advanced powder fusion machines, it is of high importance to develop an in situ inspection system to monitor the printed surface and pre-print powder bed as the build cycle proceeds. Consequently, high resolution, high precision and fast detection measurement systems need to be investigated, as such optically based measurement systems can provide feedback for manufacturing process optimisation. Fringe projection technology has a great advantage in the measurement of topography in such environments. The implementation of a fringe projection system requires that the system is pre-calibrated in order to obtain high measurement resolution and repeatability. This paper presents a simple calibration method for an AM-based in situ fringe projection system using a phase-depth calibration model. If a calibration plate with certificated marks is used, however, the texture of the plate will affect the measured phase accuracy. A simple calibration method to reduce the calibration plate texture effect in the process of calibration is outlined. Experimental results show that the proposed method can eliminated these effects and improve measurement resolution and repeatability. The proposed in situ/in process inspection technique has been implemented within a commercial electron beam powder bed fusion additive manufacturing machine (EBAM), to demonstrate the capability for effective feedback during the manufacturing process.

Download Full-text

A STRUCTURED APPROACH TO REDUCE DESIGN ITERATIONS IN ADDITIVE MANUFACTURING

Proceedings of the Design Society ◽

10.1017/pds.2021.24 ◽

2021 ◽

Vol 1 ◽

pp. 231-240

Author(s):

Laura Wirths ◽

Matthias Bleckmann ◽

Kristin Paetzold

Keyword(s):

Additive Manufacturing ◽

Spare Parts ◽

Design Guidelines ◽

Final Part ◽

Layer By Layer ◽

Powder Bed ◽

Batch Sizes ◽

Manufacturing Technologies ◽

Structured Approach ◽

Design Freedom

AbstractAdditive Manufacturing technologies are based on a layer-by-layer build-up. This offers the possibility to design complex geometries or to integrate functionalities in the part. Nevertheless, limitations given by the manufacturing process apply to the geometric design freedom. These limitations are often unknown due to a lack of knowledge of the cause-effect relationships of the process. Currently, this leads to many iterations until the final part fulfils its functionality. Particularly for small batch sizes, producing the part at the first attempt is very important. In this study, a structured approach to reduce the design iterations is presented. Therefore, the cause-effect relationships are systematically established and analysed in detail. Based on this knowledge, design guidelines can be derived. These guidelines consider process limitations and help to reduce the iterations for the final part production. In order to illustrate the approach, the spare parts production via laser powder bed fusion is used as an example.

Download Full-text