|Project title||Optical quality control for extrusion 3D printing (Quali3D)|
|Project duration||01.07.2019 – 30.09.2021|
Additive manufacturing is a fast-growing market. Especially for small and medium-sized companies extrusion based additive manufacturing is interesting due to the large number of processable materials and application areas. However, as a supplement to existing manufacturing technologies a nationwide use of extrusion based additive manufacturing is not in progress. Deficits in the knowledge of process qualities and control variables lead to quality problems and a lack of acceptance regarding to the technology. In addition, with today's 3d-printers process errors will not be detected or only after the completion of a part.
The aim of this research project is to assure the additive manufacturing process with optical measuring technology. The inline quality assurance system works layer by layer. The project will contribute to the further industrialization of additive manufacturing.
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- 15.05.2020, 13:30 h - 16:00 h
- IPH Hannover gGmbH | Hollerithallee 6 | 30419 Hannover
- 13.09.2019, 10:30 h - 14:30 h
- IPH Hannover gGmbH, Hollerithallee 6, 30419 Hannover
Publications about the project
Additive Manufacturing Oleff, A.; Küster, B.; Stonis, M.; Overmeyer, L.: Process monitoring for material extrusion additive manufacturing: a state-of-the-art review. In: Progress in Additive Manufacturing, Springer Nature (2021), Vol. 6, pp. 705-730. DOI: 10.1007/s40964-021-00192-4.
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.
Material extrusion, Fused deposition modeling, Process monitoring, Sensor technology, Research gaps
Additive Manufacturing Oleff, A.; Küster, B.; Stonis, M.; Overmeyer, L.: Optische Qualitätsprüfung für die additive Materialextrusion. In: ZWF - Zeitschrift für wirtschaftlichen Fabrikbetrieb, Carl Hanser Verlag, 115. Jg. (2020), H. 1-2, S. 52-56. ISSN 0947–0085.
Quality assurance methods are a central success factor for the further industrialization of additive manufacturing. This paper presents an approach for an optical inspection system that controls the quality of additive material extrusion layer by layer. The inspection task gets analyzed, hardware components for data acquisition are designed and a first step towards texture-analytical detection of defects is presented.
additive manufacturing, 3d printing, material extrusion, fused deposition modeling, image processing
Additive Manufacturing Oleff, A.; Küster, B.: Schichtweise Überwachen. Optisches Inline-Prüfsystem für die additive Fertigung. In: QZ – Qualität und Zuverlässigkeit, Carl Hanser Verlag, 65. Jg. (2020), H. 1, S. 32-33. ISSN: 0720-1214.
Quality assurance methods are a central success factor for the further industrialization of additive manufacturing. In the IGF research project "Optical quality inspection for extrusion 3D printing (Quali3D)", a testing system is therefore being developed which monitors the quality of the additive process layer by layer. This should enable a comprehensive evaluation.
3D printing, additive manufacturing, optical metrology, image processing