Digital Image Processing for Quality Control on Injection Molding Products

Sasso, M.; Natalini, Massimo; Amodio, D.

doi:10.5772/15673

Cited by 2 publications

(2 citation statements)

References 2 publications

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“…Optical inspection systems, such as computerized vision inspection systems and laser measurement sensors, are effective strategies for increasing repeatability and reliability and obtaining more relevant information about the processes that can assist in production management (22) . Artificial vision system technology is a computational tool for obtaining relevant information for decision making in production lines involving ex-…”

Section: Discussionmentioning

confidence: 99%

Evaluating the diameter of eyedropper tips using a computer vision system

Machado

Cristovam

Freitas

et al. 2019

Arquivos Brasileiros De Oftalmologia

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This study aimed to determine the variation in diameters of outer and inner apertures of eyedropper tips using a computer vision system. Standardizing the size of eye drop nozzles is crucial to reduce the treatment cost of chronic eye diseases and to ensure a continued use of medication. An eyedropper volume of >20 μL (maximum storage of the conjunctival sac) causes medication wastage and increases treatment costs. Methods: We measured the diameters of the outer and inner apertures of eyedropper tips and evaluated variations in diameters using a computerized visual inspection system. Results: The computer visual inspection system identified anomalies in the apertures of eyedropper tips that resulted in diameter variations. Conclusions: The results of the present study show discrepancies in diameters of eyedropper tips, suggesting a variation in eyedropper size and medication wastage.

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Section: Discussionmentioning

confidence: 99%

Evaluating the diameter of eyedropper tips using a computer vision system

Machado

Cristovam

Freitas

et al. 2019

Arquivos Brasileiros De Oftalmologia

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show abstract

“…The imperative to enhance product quality has compelled manufacturers to elevate the control level applied to both finished and semi-finished components, encompassing both qualitative and quantitative aspects. The adoption of digital image processing (DIP) emerges as an efficacious technique, not only augmenting the consistency and dependability of inspections but also enabling the extraction of valuable insights through DIP algorithms (Sasso et al, 2011). Furthermore, the utilization of DIP technology has the potential to substantially reduce the overall duration required for quality control, while simultaneously expanding the scope of inspected components.…”

Section: Introductionmentioning

confidence: 99%

Qualitative characterization of residual stress of injection molded polycarbonate goggles based on photoelasticity and digital image processing technique

Wang,

He,

et al. 2023

Front. Mater.

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Transparent polymeric materials have gained significant popularity as replacements for glass in various industries due to their low cost, lightweight nature, and high processing efficiency. Injection molding is the primary method for producing transparent polymer parts. However, residual stress often poses a challenge, leading to various defects. Traditional approaches utilize photoelasticity and polarizers to determine stress in transparent parts, which costs time and cannot be easily used for online monitoring and real time quality inspection. The digital image processing (DIP), combined with photoelasticity, offers a promising solution for detecting residual stress and assessing product quality in real-time during manufacturing. In this study, we propose a photoelastic digital image processing (PDIP) approach that combines photoelasticity and DIP techniques to identify residual stress and evaluate part quality using a single digital polarized image without the need for a rotation process. By collecting and analyzing the gray values and variations from the photoelastic images through PDIP, we compared and correlated the gray values of the entire image, a specific area on one side lens, a warp line, and a weft line. Additionally, numerical simulations were performed to validate the proposed method. The results demonstrated the feasibility of this instant identification method. The PDIP technique should be applied to a specific area or line within the parts. By obtaining the average gray value, the instantaneous identification of residual stress can be achieved. The determination of the specific area or line can be tailored according to the quality requirements of the parts.

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Digital Image Processing for Quality Control on Injection Molding Products

Cited by 2 publications

References 2 publications

Evaluating the diameter of eyedropper tips using a computer vision system

Evaluating the diameter of eyedropper tips using a computer vision system

Qualitative characterization of residual stress of injection molded polycarbonate goggles based on photoelasticity and digital image processing technique

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