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Method for the Investigation of Mold Filling in the Fiber Injection Molding Process Based on Image Processing

Moll, Patrick; Schäfer, Axel; Coutandin, Sven; Fleischer, Jürgen

Fiber Injection Molding is an innovative process for manufacturing 3D fiber formed parts. Within the process fibers are injected in a special mold through a movable nozzle by an air stream. This process allows a resource efficient production of near net-shape long fiber-preforms without cutting excess. For the properties of the preforms the mold filling is decisive, but current state of the art lacks methods to monitor mold filling online. In this paper a system for monitoring the mold filling based on image processing methods is presented. Therefor a camera and back-lighting has been integrated into a fiber injection mold. The detected filling level and fiber distribution is passed to the PLC of the fiber injection molding machine, which allows the operator to monitor the current mold filling state by means of a visual display. The image processing approach consists of preprocessing, binarization and segmentation. For the preprocessing and binarization several methods including a k-means algorithm, the Otsu thresholding method and a convolutional artificial neural network have been implemented and evaluated. Additionally the illumination of the mold has been investigated and found to have a very large influence on the quality of the results of all investigated methods. ... mehr

Verlagsausgabe §
DOI: 10.5445/IR/1000127882
Veröffentlicht am 19.12.2020
DOI: 10.1016/j.procir.2020.01.012
Zitationen: 4
Zitationen: 3
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Produktionstechnik (WBK)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2019
Sprache Englisch
Identifikator ISSN: 2212-8271
KITopen-ID: 1000127882
Erschienen in Procedia CIRP
Verlag Elsevier
Band 86
Seiten 156–161
Bemerkung zur Veröffentlichung 7th CIRP Global Web Conference, CIRPe 2019; Berlin; Germany; 16 October 2019 through 19 October 2019
Schlagwörter Manufacturing Process, Monitoring, Process Control, Mold, Artificial Intelligence
Nachgewiesen in Scopus
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