Influence of AFP Process Parameters on the Temperature Distribution Used for Thermal in-process Monitoring

Schmidt, Carsten; Denkena, Berend; Hocke, Tristan; Völtzer, Klaas

doi:10.1016/j.procir.2017.03.220

Cited by 15 publications

(8 citation statements)

References 5 publications

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“…No industrial use has been reported so far [2,6]. Research done by Gregory et al [6,7], Schmidt and Denkena et al [2,9,10] use similar approach adopted in this paper but lack either holistic data analysis or system behavior identification. This paper tries to fill in that gap that can serve to actively control the process.…”

Section: Defect Detectionmentioning

confidence: 91%

“…A multitude of defects can arise during the layup which can be categorized either by cause of occurrence or method of detection. Common defect types classified by cause of incidence and crucial for quality assurance according to DIN29971 [10] are: positioning defects like gaps, overlaps, missing tows, twisted tows; bonding defects such as bridging, air pockets; foreign object defects (FOD) such as fuzzball and tow defects such as splice. A summary of defects being capable of detected inline are shown in Figure 1.…”

Section: Defect Typesmentioning

confidence: 99%

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Ply-by-ply inline thermography inspection for thermoplastic automated tape layup

Yadav

Oswald-Tranta

Schledjewski

et al. 2021

Advanced Manufacturing: Polymer & Composites Science

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Automated tape layup (ATL) largely employs post manufacturing manual visual inspection techniques for defect detection, which severely affects the productivity. Inline monitoring and defect prediction can help in making the process faster and more reliable. The presented work details the use of thermography as an inspection tool for thermoplastic tape material. A new online monitoring system is developed containing Infrared camera integrated on a purpose build ATL test rig. The capability of the tool to identify various defects is analyzed. Moreover, detailed temperature and cooling behavior analysis is done for defect prediction.

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Section: Defect Detectionmentioning

confidence: 91%

Section: Defect Typesmentioning

confidence: 99%

Ply-by-ply inline thermography inspection for thermoplastic automated tape layup

Yadav

Oswald-Tranta

Schledjewski

et al. 2021

Advanced Manufacturing: Polymer & Composites Science

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“…Fraunhofer IIS investigates polarisation camera monitoring systems 26,27 and NASA as well as the Institute of Production Engineering and Machine Tools -University Hanover (IFW) focused on thermographic imaging inspection. [28][29][30][31][32][33] These sensors acquire only 2D image data. The suppliers and industrial developers, mentioned above, have focussed on LLSS based systems.…”

Section: Fiber Placementmentioning

confidence: 99%

Algorithm assessment for layup defect segmentation from laser line scan sensor based image data

Meister

Wermes

Stüve

et al. 2020

Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2020

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The Automated Fiber Placement process is established in the aerospace industry for the production of composite components. This technique places several narrow material strips in parallel. Within current industrial Automated Fiber Placement processes the visual inspection takes typically up to 50 % of overall production time. Furthermore, inspection quality highly depends on the inspector. Therefore, automation of visual inspection offers a great improvement potential. To ensure reliable defect detection the segmentation of individual defects must be investigated. For this reason, this paper focusses on an assessment of defect segmentation algorithms. Therefore, 29 structural, statistical and spectral algorithms from related work were assessed, theoretically, using the 12 most relevant criteria as assessed from literature and process requirements. Then, seven most auspicious algorithms were analysed in detail. For reasons of determinism, Neural Network approaches are not part of this paper. Manually labelled prepreg defect images from a laser line scan sensor were used for tests. The test samples contain five defect types with 50 samples of each. Additionally, layups without defects were analysed. It was concluded that Adaptive Thresholding works best for global defect segmentation. The Cell Wise Standard Deviation Thresholding performs also quite well, but is very sensitive to grid size. Feasible algorithms perform reliable defect segmentation for layed up material.

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“…'Inspection' [14,21,30,49] more often defines an act of looking at the quality as an ad-hoc [70] step, therefore at a certain state after a production step. Aside from these, there is a frequent use of the terms 'inline' [71][72][73] and 'online' [74][75], also called in-process [46,76] or rarely in-situ [32], quality control. Online control, compared to inline control, is characterized by a shorter time frame between sampling and analyzing of the results.…”

Section: Types Of Quality Control Systemsmentioning

confidence: 99%

“…Due to fewer geometrical restrictions compared to 3D scanning, the point of measurement can be closer to the nip point. Although the lay-up velocity does not significantly influence the heat-up behavior, a temperature model to forecast the temperature distribution for certain process parameters is necessary as a basis for reliable and robust thermal online monitoring [76].…”

Section: Infrared Thermographymentioning

confidence: 99%

A literature review of quality control for automated lay-up processes

Schlegel¹

2019

Zeitschrift Kunststofftechnik

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A literature review of quality control for automated lay-up processes of CFRP Automated lay-up of carbon fiber reinforced polymers is an established method for producing large parts in the aerospace industry. Currently, the quality control for this automated manufacturing process is performed by humans. In the last years, research has focused on increasing productivity of automated lay-up, thus the automation of the quality control has been taken into consideration. The objectives of the paper are to review the requirements for quality control based on an overview of the possible defects in automated lay-up and to evaluate their fulfilment by both visual quality control by humans and automated quality control systems. Literaturübersicht zur Qualitätskontrolle von automatisierten Ablegeverfahren von CFK Automatisiertes Ablegen von kohlenstofffaserverstärkten Kunststoffen ist eine etablierte Methode zur Herstellung großer Flugzeugteile. Zurzeit wird die Qualitätskontrolle dieses automatisierten Fertigungsverfahrens noch von Menschen durchgeführt. In den letzten Jahren hat sich die Forschung auf die Automatisierung der Qualitätskontrolle fokussiert um die Produktivität zu erhöhen. Die Ziele dieser Literaturübersicht sind, die Anforderungen für die Qualitätskontrolle basierend auf den vorkommenden Fehlern festzulegen und die Erfüllung dieser Anforderungen durch die visuelle Qualitätskontrolle durch den Mensch als auch durch automatisierte Systeme zu bewerten.

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Influence of AFP Process Parameters on the Temperature Distribution Used for Thermal in-process Monitoring

Cited by 15 publications

References 5 publications

Ply-by-ply inline thermography inspection for thermoplastic automated tape layup

Ply-by-ply inline thermography inspection for thermoplastic automated tape layup

Algorithm assessment for layup defect segmentation from laser line scan sensor based image data

A literature review of quality control for automated lay-up processes

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