CUSTOMER
- O-Net Industry
- Location Shenzhen, China
- Industry: Medical Supply Inspection
- Implementaion: 2020
APPLICATION
An acute shortage of face masks caused by fear of the spreading coronavirus pandemic has been straining global medical supplies since the start of 2020. The smart face mask inspection system designed by O-Net Industry boosts productivity and increases product conformity rate for the manufacturers. By making the inspection process faster and more effective, this solution can both ease the pressing market need and help face mask manu-facturers drive production cost down.
Headquartered in Shenzhen China, O-Net Industry is a leading company dedicated to machine vision automa-tion. The vision systems designed by O-Net Industry are used in various applications including visual inspections, geometry measurement and OCR among others; they are also able to provide customized solutions tailored to the products to be inspected.
Headquartered in Shenzhen China, O-Net Industry is a leading company dedicated to machine vision automa-tion. The vision systems designed by O-Net Industry are used in various applications including visual inspections, geometry measurement and OCR among others; they are also able to provide customized solutions tailored to the products to be inspected.
In a traditional production line, a high scrap rate is inevi-table due to interference by environmental factors and the inconsistent working conditions of face mask making machines, resulting in lower efficiency and conformity rate. The application of a vision inspection in the produc-tion process, however, can significantly improve the situation.
All parts of a face mask need to be inspected, including the covering, the edges, the ear loops and the metal strip that lets the wearer bend the mask around the bridge of the nose (Figure 1). Quality control needs to identify and remove masks that are overlapping, broken, contami-nated, askew or in the wrong size.
All parts of a face mask need to be inspected, including the covering, the edges, the ear loops and the metal strip that lets the wearer bend the mask around the bridge of the nose (Figure 1). Quality control needs to identify and remove masks that are overlapping, broken, contami-nated, askew or in the wrong size.
Face mask inspection is also made more complex by factors including:
- Uneven illumination occurs during inspection due to the grainy surface of the non-woven fabric of face masks
- Face masks to be inspected are mmoving and their positions are random on the conveyor
- The edge, ear loop and metal strip are difficult to distinguish in inspection images
SOLUTION AND BENEFITS
With the help of customized lighting and the Basler ace 5 MP camera, the smart face mask inspection system deve-loped by O-Net can obtain excellent images of each mask. The system can then use the alignment algorithm to check whether the face mask meets standards.
In the inspection process, the system finds the center and corners of the covering part of face masks via the image acquired (Figure 2), to identify products that are miss-hapen. Exact measurement of face masks can also be done. With the center confirmed, the software defines the region of interest (ROI) as well as the baseline, to measure the specific size of a face mask and determine whether it meets standards.
Inspection of ear loops focuses on whether the length of loops and the positions of the fixation points meet the set standards. In the image analysis process, ear loops can be defined as curved lines. The software will detect and extract these curved lines and determine whether they are broken (Figure 6), and if not, calculate their length (Figure 7). The system can detect the fixing points of the ear loops in the image (Figure 8) and measure the dis-tances between the fixation points and their respective neighboring edges, to determine whether they meet standards
Non-woven fabric allows some light to get through, but extra layers can significantly increase its opacity. Thus the folded section of a face mask will appear much darker than the rest in the image. In Figure 4, the upper and bottom part of the face mask appear pale; O-Net’s soft-ware is configured to accept an image where the paler area is 374550 pixels in size. By contrast, the paler area drops to only 28894 pixels, which is almost ten times less, when two face masks overlap (Figure 5). By using such features, O-Net’s system determines whether the face masks are overlapping.
Lastly, the edges of a face mask also need inspection. The system needs to check whether the pitting on the edges is well aligned. Two green baselines are defined based on the outer margins of a face mask. Then the vertical dis-tance from each pitting line to the baselines is measured, so that the system can tell if the pitting on the edges is well aligned
Inspection of the length and position of the metal strip in a face mask is also required. By using the cutomized ligh-ting, the inspection image can show both the metal strip inside and the non-woven fabric wrapping it. Once the ends of the metal strip are found in the image, the length can be calculated (Figure 10). Meanwhile, two baselines are drawn to check that the position of the metal strip is centered
The vision inspection systems developed by O-Net can effectively automate the tedious quality check process and significantly improve product conformity rate. On average, each system can replace up to four skilled human inspectors. In factory applications, the visual inspection system usually runs uninterrupted for long periods; there-fore system stability is essential. O-Net decided on the Basler ace acA2440-20gm camera, due to the well-known stability of this key vision component. Mr. Wang, sales manager of O-Net, explains that “the stability of Basler cameras has helped save considerable mainte-nance costs. Our system development is quite smooth thanks to the Basler pylon Camera Software Suite, as it’s genuinely a developer-friendly software suite, and a short time-to-mark gives us competitive advantages. The vision market is booming in China and speed is vital. Our custo-mers are demanding ever-faster delivery, so the fast and reliable lead time ensured by Basler China is another attractive reason for us to work together.”
The smart software system offers high compatibility and can be customized, as O-Net develops everything from operator interface to architecture. This type of vision inspection software solution can apply to many applications.
In the inspection process, the system finds the center and corners of the covering part of face masks via the image acquired (Figure 2), to identify products that are miss-hapen. Exact measurement of face masks can also be done. With the center confirmed, the software defines the region of interest (ROI) as well as the baseline, to measure the specific size of a face mask and determine whether it meets standards.
Inspection of ear loops focuses on whether the length of loops and the positions of the fixation points meet the set standards. In the image analysis process, ear loops can be defined as curved lines. The software will detect and extract these curved lines and determine whether they are broken (Figure 6), and if not, calculate their length (Figure 7). The system can detect the fixing points of the ear loops in the image (Figure 8) and measure the dis-tances between the fixation points and their respective neighboring edges, to determine whether they meet standards
Non-woven fabric allows some light to get through, but extra layers can significantly increase its opacity. Thus the folded section of a face mask will appear much darker than the rest in the image. In Figure 4, the upper and bottom part of the face mask appear pale; O-Net’s soft-ware is configured to accept an image where the paler area is 374550 pixels in size. By contrast, the paler area drops to only 28894 pixels, which is almost ten times less, when two face masks overlap (Figure 5). By using such features, O-Net’s system determines whether the face masks are overlapping.
Lastly, the edges of a face mask also need inspection. The system needs to check whether the pitting on the edges is well aligned. Two green baselines are defined based on the outer margins of a face mask. Then the vertical dis-tance from each pitting line to the baselines is measured, so that the system can tell if the pitting on the edges is well aligned
Inspection of the length and position of the metal strip in a face mask is also required. By using the cutomized ligh-ting, the inspection image can show both the metal strip inside and the non-woven fabric wrapping it. Once the ends of the metal strip are found in the image, the length can be calculated (Figure 10). Meanwhile, two baselines are drawn to check that the position of the metal strip is centered
The vision inspection systems developed by O-Net can effectively automate the tedious quality check process and significantly improve product conformity rate. On average, each system can replace up to four skilled human inspectors. In factory applications, the visual inspection system usually runs uninterrupted for long periods; there-fore system stability is essential. O-Net decided on the Basler ace acA2440-20gm camera, due to the well-known stability of this key vision component. Mr. Wang, sales manager of O-Net, explains that “the stability of Basler cameras has helped save considerable mainte-nance costs. Our system development is quite smooth thanks to the Basler pylon Camera Software Suite, as it’s genuinely a developer-friendly software suite, and a short time-to-mark gives us competitive advantages. The vision market is booming in China and speed is vital. Our custo-mers are demanding ever-faster delivery, so the fast and reliable lead time ensured by Basler China is another attractive reason for us to work together.”
The smart software system offers high compatibility and can be customized, as O-Net develops everything from operator interface to architecture. This type of vision inspection software solution can apply to many applications.
TECHNOLOGIES USED
- Camera: Basler ace acA2440-20gm
- Lightinh: Customized BT series lighting
- Software: SV Smart Vision System by O-Net
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