PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Vision-based Online Defect Detection of Polymeric Film via Structural Quality Metrics

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Nondestructive and contactless online approaches for detecting defects in polymer films are of significant interest in manufacturing. This paper develops vision-based quality metrics for detecting the defects of width consistency, film edge straightness, and specks in a polymeric film production process. The three metrics are calculated from an online low-cost grayscale camera positioned over the moving film before the final collection roller and can be imple mented in real-time to monitor the film manufacturing for process and quality control. The objective metrics are calibrated to correlate with an expert ranking of test samples, and results show that they can be used to detect defects and measure the quality of polymer films with satisfactory accuracy.
Twórcy
  • Michigan Technological University, College of Computing1400 Townsend Drive, Houghton, MI 49931, USA
  • German Jordanian University, School of Applied Technical Sciences, Jordan
  • Michigan Technological University, College of Computing, USA
  • German Jordanian University, School of Applied Technical Sciences, Jordan
Bibliografia
  • Ajji A. Zhang, X. and Elkoun S. (2006). Biaxial orientation in LLDPE films: Comparison of infrared spectroscopy, X-ray pole figures, and birefringence techniques, Polym. Eng. Sci., Vol. 46, pp. 1182–1189.
  • Alcan P., Sözöz H. and Aydoğmuş S.B. (2017). Production of Market Bag and their Stability and Optimization Parameters, Int. J. Adv. Sci. Technol., Vol. 103, pp. 23–34.
  • Altarazi S.A. and Allaf R.M. (2017). Designing and analyzing a mixture experiment to optimize the mixing proportions of polyvinyl chloride composites, J. Appl. Stat., Vol. 44, pp. 1441–1465.
  • Altarazi S. (2018). Enhancing conformance of injection blow molding by integrating machine learning modeling and Taguchi parameter design, Advances in applications and statistics, Vol. 53, pp. 519–535.
  • Altarazi S., Allaf R. and Alhindawi F. (2019). Machine Learning Models for Predicting and Classifying the Tensile Strength of Polymeric Films Fabricated via Different Production Processes, Materials (Basel), Vol. 12, pp. 1475–1488.
  • ASTM (1995) Subcommittee D20-10 on Mechanical Properties, Standard test method for tensile properties of thin plastic sheeting.
  • ASTM (2020) D1922-15, Standard Test Method for Propagation Tear Resistance of Plastic Film and Thin Sheeting by Pendulum Method. West Conshohocken PA, ASTM International.
  • Belloli D., Savaresi S.M., Cologni A., Previdi, F. and Cazzola D. (2012). Modeling and control of an Internal Bubble Cooling system, 8th International Symposium on Mechatronics and its Applications (ISMA).
  • Callister W. and Rethwisch D. (2011). Materials science and engineering, John wiley & Sons, NY.
  • Costin M.H., Taylor P.A. and Wright J.D. (1982). A critical review of dynamic modeling and control of plasticating extruders, Polym. Eng. Sci., Vol. 22, pp. 393–401.
  • Dominey S. and Goeckel W. (2003). Polymer Defect Detection and Classification Utilizing Camera Optics, Real Time Computation and Small Scale Resin Sample Processing, SPE.
  • Dong, S., He, B., Lin, C., Zhao, Q., & Shen, H. (2015) Calibration method for a structured light measurement system with two different focal length cameras. Measurement, Vol. 73, pp. 462–472.
  • Film Blowing (2023). Industrial Extrusion Machinery: Blown Film Extrusion (Film Blowing), http://www.industrialextrusionmachinery.com/plastic_extrusion_blown_film_extrusion.html. [Accessed: 17-Jan-2023].
  • Gosselin R., Rodrigue D., Ez R. and Duchesne C. (2009). Potential of hyperspectral imaging for quality control of polymer blend films, Ind. Eng. Chem. Res., Vol. 48, pp. 3033–3042.
  • Johnson J.T. (2009). Defect and thickness inspection system for cast thin films using machine vision and fullfield transmission densitometry, (Doctoral dissertation, Georgia Institute of Technology).
  • Khan J. G., Dalu R. S. and Gadekar S. S. (2014). Defects In Extrusion Process And Their Impact On Product Quality, International journal of mechanical engineering and robotics research, Vol. 3, pp. 187–194.
  • Luo H., Xu J., Binh N.H., Liu S., Zhang C. and Chen K. (2014). A simple calibration procedure for structured light system, Optics and Lasers in Engineering, Vol. 57, pp. 6–12.
  • Łukasik K. and Stachowiak T. (2020). Intelligent management in the age of Industry 4.0–an example of a polymer processing company, Management and Production Engineering Review, Vol. 11, pp. 38–49. DOI: 10.24425/mper.2020.133727.
  • Michaeli W., Berdel K. and Osterbrink O. (2009). Realtime defect detection in transparent multilayer polymer films using structured illumination and 1d filtering, Optical Measurement Systems for Industrial Inspection VI, No. 7389, pp. 585–593.
  • Miliūnas V., Voloshin A., Kibirkštis E., Stepanenko A., Buškuvien˙e N. and Ragulskis L. (2017). Detection of the surface defects in thin polymeric films using projection moiré, Journal of measurements in engineering, Vol. 5, pp. 106–114.
  • National Research Council (1994). Polymer science and engineering: the shifting research frontiers. National Academies Press.
  • Pratt V. and Warner J. (2000). Defect inspection in transparent materials, Sensor Review, Vol. 20, pp. 294–298.
  • Rawashdeh N.A, Abu-Khalaf J.M., Khraisat W. and AlHourani S.S. (2018). A visual inspection system of glass ampoule packaging defects: effect of lighting configurations, International Journal of Computer Integrated Manufacturing, No. 9, Vol. 31, pp. 848–856. DOI: 10.1080/0951192X.2018.1447145
  • Ravimal D., Kim H., Koh D., Hong J.H. and Lee S.K. (2020). Image-based inspection technique of a machined metal surface for an unmanned lapping process, International Journal of Precision Engineering and Manufacturing-Green Technology, Vol. 7, pp. 547–557.
  • Ren Z., Fang F., Yan N. and Wu Y. (2022). State of the art in defect detection based on machine vision, International Journal of Precision Engineering and Manufacturing-Green Technology, Vol. 9, pp. 661–691.
  • Shen P., Luo Z., Wang S., Mao F., Su Z. and Zhang H. (2022). Feature Detection of GFRP Subsurface Defects Using Fast Randomized Sparse Principal Component Thermography, International Journal of Thermophysics, Vol. 43, pp. 1–13.
  • Siemann U. (2005). Solvent cast technology-A versatile tool for thin film production, Prog. Colloid Polym. Sci., Vol. 130, pp. 1–14.
  • Tolba A.S. and Raafat H.M. (2015). Multiscale image quality measures for defect detection in thin films, The International Journal of Advanced Manufacturing Technology, Vol. 79, pp. 113–122.
  • Van Drongelen M., Cavallo D., Balzano L., Portale G., Vittorias I., Bras W. and Peters G.W.M. (2014). Structure Development of Low-Density Polyethylenes During Film Blowing: A Real-Time Wide-Angle X-ray Diffraction Study, Macromol. Mater. Eng., Vol. 299, pp. 1494–1512.
  • Wang T., Chen Y., Qiao M. and Snoussi, H. (2018). A fast and robust convolutional neural networkbased defect detection model in product quality control, The International Journal of Advanced Manufacturing Technology, Vol. 94, pp. 3465–3471. DOI: 10.1007/s00170-017-0882-0.
  • Wellstead P.E., Heath W.P. and Kjaer A.P. (1998). Identification and control of web processes: Polymer film extrusion, Control Eng. Pract., Vol. 6, pp. 321–331. DOI: 10.1016/S0967-0661(97)00023-3.
  • Westlake Chemical (2023). Blown Film Troubleshooting Guide, https://www.westlake.com/polyethyleneapplications/blown-film. [Accessed: 17–Jan–2023].
  • Yu J.C., Chen X.X., Hung T.R. and Thibault F. (2004). Optimization of extrusion blow molding processes using soft computing and Taguchi’s method, J. Intell. Manuf., Vol. 15, pp. 625–634. DOI: 10.1023/B:JIMS.0000037712.33636.41.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-7a26c79e-52e0-450c-8883-b42adb46c3a3
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.