:::

【2021 Application Example】 Optical industry AOI imports AI Great Leap Forward to completely solve the pain points of lens defect detection

The stay-at-home economy such as smartphones and remote working is booming, and the information and communication industry is booming, driving the optical industry to flourish. However, the defect detection of optical lenses is mostly carried out by human eyes, which is not only time-consuming and labor-intensive, but also limited by the fact that human eyes are prone to fatigue. The misjudgment rate is also a lingering pain point for the optical industry. Benefiting from the evolution of AI technology, Shangyang Optics introduced diffraction optical technology for shooting, used the images captured by the system as the data source, introduced AI model training, and integrated the camera system and image recognition into a production line workstation, greatly improving defect identification The rate is as high as over 90%.

Taiwan’s optical production value accounts for 10% of the world’s, and the application range of precision optics is expanding day by day

The optical industry is a mainstream product in consumer electronics. Even though Taiwan was affected by the Sino-US trade dispute in 2019, the output value of optoelectronics still reached US$46.3 billion, accounting for 10% of the world's total. Among them, the "precision optics" segment accounts for NT$87 billion (approximately US$2.9 billion) in output value. In view of the increase in the number of smartphone lenses, precision optics still maintains a sustained growth of 4% compared to the decline in other fields.

Since Sharp launched the world's first camera phone equipped with a rear 110,000-pixel lens in 2000, end consumers' requirements for smartphone camera performance have continued to increase, and with the wave of 5G high-speed Internet The advent of the technology has led to the activation of application markets such as augmented reality (AR) or virtual reality (VR). The innovation and application of its technology have added a lot of momentum to the optical industry, and the application fields have extended from smartphones to popularization. to the mass consumer markets such as automobiles and home entertainment.

Optical lenses are inseparable from the economic development of "precision optics". As semiconductor technology continues to mature and network speeds continue to increase, optical lenses are used not only in smartphones, tablets, traditional cameras, projectors, In the field of people's livelihood vehicles, the demand for engineering visual inspection and security applications in high-precision manufacturing processes continues to grow rapidly.

Optical lens defects Detection is mostly done manually.

▲ Optical lens defect detection is mostly done manually.

"Optical lenses" are essential components of the overall optical-mechanical system. The lens finish inspection after incoming materials and before shipment not only affects the overall production line efficiency development, but also has an impact on the quality commitment of end customers that cannot be underestimated. For a long time, the optical industry has mostly used human eye detection for defect inspection. As production volume continues to increase, not only labor costs continue to rise. As inspectors age, their eyesight gradually declines, and the misjudgment rate increases every year. In addition, manpower recruitment has been difficult in recent years. Even if they are lucky enough to be recruited, it is not easy to develop the inspection technology, and the training time is lengthy, making it impossible to respond to the production line manpower needs in a timely manner.

Introducing diffraction optical technology and AI training model to improve defect recognition rate to more than 90%

The current market is flooded with a large number of automated optical inspection systems, and there are many substantial cases of lens defects. However, after years of market exploration and evaluation by Shangyang Optics, this system still cannot solve the current manual inspection problem. The main reason is that the appearance of the optical lens is curved and transparent, and it is not easy to photograph various defects, and once the defects are around There is interference from other stray lights, making judgment more difficult. Moreover, different types of lenses need to be individually rotated and lit and adjusted according to the defect status before entering the judgment stage. The labor consumption ratio is still high, which is not in line with the efficiency and cost.

Through this, through the matchmaking of the AI ​​project execution team of the Industrial Bureau of the Ministry of Economic Affairs, Xiaoma Optics assisted Shangyang Optoelectronics in establishing an effective defect photography system. Pony Optics provides guidance on precision diffraction optics. Based on the characteristics of "light" fluctuations, lens defects can be obtained through a unified lens shooting method. Current photography systems on the market mostly use geometric optics. Geometric optics uses linear light and is not easy to capture defects such as missing coatings, tiny scratches, and liquid dirt. The cooperation plan introduces diffraction optical technology for shooting. Through precise imaging from all angles, it can achieve higher contrast and better noise reduction than ordinary geometric optical elements, so as to obtain the necessary defective images.

Image of scratches and defects on the optical lens.

▲Schematic diagram of optical lens scratches and defects.

In order to improve the more detailed defect detection and recognition rate in this case, Shangyang Optics used the image captured by the system as the data source, imported AI model training, and integrated the camera system and image recognition into a production line workstation, which not only improved the defect recognition rate Reaching more than 90%, it is more conducive to the subsequent development of automated production lines.

The AI ​​model training for this cooperation project is provided by Yirui Technology. Currently, most manufacturers have introduced AOI systems for production line defect inspection. Most of them use OCR (optical character recognition), which refers to the analysis and recognition processing of image files of text data. , the process of obtaining text and layout information) technology needs to be 100% accurate, and there is no room for error, resulting in accidental killings often occurring.

After adding the AI ​​training model, optical lens defects The recognition rate is greatly improved
.

▲After adding the AI ​​training model, the optical lens defect recognition rate is greatly improved.

AI+AOI solves the two major pain points of insufficient manpower and high misjudgment rate

This time, Yirui Technology and Xiaoma Optics cooperated to install Yirui's AI system in the optical inspection instruments developed by Xiaoma Optics, adding AI algorithms to the optical detection of defects, and training based on the data and needs provided by customers. AI model identification can greatly improve the accuracy of identification of defects, improve yield rate, and increase production line efficiency. Through the tripartite cooperation between Shangyang Optics, Xiaoma Optics and Yirui Technology, the optical industry AOI is introduced into AI, hoping to completely solve the pain points of industrial lens defect detection.

Since setting up the production line in 2019, Shangyang Optics hopes to introduce a smart production model. In view of the continuous growth of the company's operations and the continuous improvement of production volume, through the introduction and expansion of this achievement, the demand for manpower will be significantly reduced, and the impact of production scheduling can be reduced due to the high accuracy of the discrimination rate index, thereby improving production efficiency.

Shangyang Optics stated that as the development results are implemented, it will lead the technology to be promoted to upstream and downstream players in the optical industry, such as upstream optical lens raw material suppliers to downstream finished product applications, including immersive gaming equipment and related curved glass products , people's livelihood vehicle and security camera devices, etc.

「Translated content is generated by ChatGPT and is for reference only. Translation date:2024-05-19」

Recommend Cases

這是一張圖片。 This is a picture.
Testing Seat Contact Components AI Intelligent Flaw Detection

With rapid development in 5G, AIOT, automotive electronics, and other downstream sectors, the entire supply chain is expected to benefit from this consumer market As product demand momentum gradually increases, increasing production efficiency and reducing operational costs become the most important issues In order to meet the needs of customers for various packaging types, Yingwei Technology has been committed to developing highly customized test seats However, a resulting pain point is the inability to mass-produce and fully automate operations with machines some tasks still rely on manual execution In this project, the probe part of the test seat was outsourced in 2021, and under current and future large-scale demands, work hours, costs, supply, and quality are issues Yingwei faces The company achieves a defect detection rate of 9995, which seems high, but with an average inspector able to inspect 10,000 needles per day, there would still be 5 defective needles On a test seat that is only 3 cm wide with approximately 1,000 needles, just one defective needle could potentially lead to faulty testing at the customer end As the current operational mode relies on manual visual inspection, external factors such as fatigue or oversight of personnel, and subjective judgment by inspectors may lead to the outflow of defective products, which necessitates strict quality control of contact components We once sought to utilize optical inspections Rule-based for controlling the quality of appearances, but the metallic material of the contact components leads to light scattering, background noise interference, background scratches, and material issues that could result in misjudgments Therefore, we decided to look for AI technology service providers to solve our detection difficulties Developments of Dedicated AOI Line Scan Equipment To meet the needs for inspecting thousands to tens of thousands of probes within our company's IC test seats, traditional surface imaging and individual needle imaging would be too slow to achieve rapid inspection and labor-saving goals In response, the service provider proposed a trial with an AOI dedicated line scan module solution Utilizing a width of 63mm on the X-axis for reciprocal scanning of all probes on the test seat, the tests allowed for the simultaneous scanning of 8-9 probes, significantly enhancing the future detection efficiency of AOI machines This project will proceed with the aforementioned innovative Proof of Concept POC, focusing on the development of the line scanning equipment and performing imaging, learning, and training on both normal and abnormal probes provided by our company, with initial AI model training aimed at preliminary approval This project's customized line-scan imaging module Ideal future imaging result illustration A Single AI Technology Solution for MeasurementDetection Needs Unified use of AI DL CNN learning methods, instead of the current Rule-based system which necessitates defining each defect individually, to meet the needs for abrasion measurement and appearance defect detection of malfunctionsforeign objects When the same machine uses both measurement and detection technologies, not only does it increase costs, but it also affects the detection speed Hence, the service provider recommends the use of a line scan device for imaging Its resolution is sufficient for AI to simultaneously determine appearance defects and assess the condition of needle tip abrasion, as detailed below Line scan pixel imaging displaying needle tip abrasion conditions This AI detection technology meets both measurement and inspection needs for Yingwei, not only bringing more benefits to future probe testing but also introducing an innovative axis in AI technology Change the method of human inspection, enhance work efficiency and product quality After combining both hardware line scan and software AI model training approaches, we successfully ventured into new AOI detection applications Following the AI implementation POC, including the development and validation of a customized line scan module and an initial AI model, the plan is to officially develop the AOI machine next year and integrate it into the IC test seat production line Future Prospects Probe manufacturers upstream and downstream IC factory users both have needs for the AOI inspection machine upstream can ensure probe quality before leaving the factory, while downstream users can use this machine to regularly inspect the condition of numerous IC test seats in hand Given the future demands, the AOI machine is poised to have a significant positive impact on the IC testing industry in the foreseeable future 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-12-12」

【導入案例】化身大型AIOT科技遊樂場 海科館華麗轉身好吸睛
Transforming into a Large-Scale AIoT Technology Playground: The Spectacular Makeover of the National Museum of Marine Science & Technology

Taiwan is a maritime nation When you visit the Badozi Fishing Port or Tidal Park in Keelung, do you also explore the mysteries of the ocean world at the 48-hectare National Museum of Marine Science amp Technology To get more people closer to marine technology, Keelung's Marine Museum has introduced technological services, transforming the venue into a large technology playground that delights both children and adults, fully utilizing the 'learning through play' approach After a lengthy planning process, Northern Taiwan's largest marine science museum in Keelung opened in January 2014 The museum focuses on marine education and technology, boasting Taiwan's largest IMAX 3D ocean theater The unique themes and modern viewing facilities should make it a well-known landmark in Keelung However, the original exhibition planning was static and highly specialized, lacking sufficient interaction with the public Visitors who have attended the museum also reported that the exhibits were limited and quite boring, leading to poor overall consumer experience ratings The top three dissatisfactions with the museum were weak connections to surrounding attractions, unengaging display content, and lack of exhibit material According to statistics from the Marine Museum, the ratio of local to visiting guests is approximately 64, with most foreign visitors coming from the north transportation is primarily by car and bus common types of visits include family, parent-child, and friends and the stay duration is generally 1 to 2 hours Upon deeper investigation, the top three visitor complaints were weak linkages to surrounding attractions, unengaging display content, and insufficient number of exhibits The museum analyzed potential reasons, including some displays being too specialized, making it difficult for the public to understand, and a lack of interactive elements, making the exhibition boring and the visit hurriedly brief Analysis of visitor profiles revealed that since half of the museum's visitors are locals, and accessing the museum is not so easy for out-of-towners who must travel by car or public transport, the design of the venue and exhibitions must incorporate more interactivity and intrigue to encourage locals to return and extend the duration of visitors' stays while using technological services to highlight the museum's unique features Through a recommendation from the Information Software Association, part of the Ministry of Economic Affairs' Industrial Bureau AI team, the Marine Museum commissioned Jugu Technology to resolve the issue of uninspiring venue attractions Preliminary interviews by Jugu Technology revealed that many visitors were attracted by the architectural design of the museum, notices posted on nearby walls, flags, or events being held the most interesting feature for visitors was the 3D ocean theater, indicating that content presented through audio-video and physical scenic methods was more engaging Seven major AI technologies lead to a boost in regional tourism at the Marine Museum Through the introduction of technology services, Jugu Technology designed the 48-hectare site with seven major services AI voice tours, treasure hunt puzzle games, AI exhibit interactive revitalization, AI space exhibition interactive experience, AI crowd control, Face AI interactive experience, and AI voice customer service system By utilizing AIoT and cloud technology, they made the exhibition more interesting, not only solving the issue of boring static viewings for children but also doubling the learning efficiency and dramatically improving public perception of the Marine Museum, thus increasing visitor intent and boosting regional tourism The National Museum of Marine Science and Technology introduced seven major technological application services including AI voice guide Jugu Technology aimed to improve the space optimization of the Marine Museum, using the special exhibition of coastal birds in northern Taiwan as a prototype, integrating 'face', 'limb', 'crowd' as three main axes to enhance functionality and assist in improving the museum's application of AI Practically, the Marine Museum and Jugu Technology selected the on-site special exhibits to avoid any installation of water and electricity works or pipelines in active exhibits, thereby maintaining the quality of the viewing experience Instead, they selected exhibits that were not yet open to introduce a series of technological services tailored to the unique characteristics of the exhibits In the coastal bird special exhibition inside the Marine Museum, initial construction discussions with the curators utilized Bella X1 for a welcoming interactive introduction at the exhibition entrance This was followed by an AI-powered smart guide in both Chinese and English using X1 for narration, coupled with a fun treasure hunting stamp-collecting activity - APP X1, allowing visitors to participate in challenges Subsequently, bird species within the bird exhibition were brought to life interactively using X1, and AR scenarios X1 were introduced into the exhibition space to add elements of fun and entertainment Finally, Face AI was used to interactively test facial expressions and score smiles The gorgeously transformed Marine Museum will become the best travel destination for families with children ImageMarine Museum FB Page The AIoT services introduced by the Marine Museum could be extended to various exhibition-type museums and even static art galleries in the future, tailored to the unique characteristics of different venues They could also be promoted through government projects and related plans, aiding in rural revitalization, making visits more than just sightseeing in rural areas, and breaking free from stereotypes associated with different venues The applications of these services are broad「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

這是一張圖片。 This is a picture.
AI Assists the Red Cross for Smarter Emergency Response

More Preparation Less Loss The Taiwan Food Bank Association, a non-profit organization, collects donations daily from wholesalers, retailers, manufacturers, and even kind-hearted individuals across Taiwan They also rescue consumable materials that are about to be discarded, properly allocate and deliver to households in need, aiding local underprivileged populations When natural disasters such as earthquakes, landslides, mudslides, typhoons, floods, and droughts occur in Taiwan, the food bank's resources can be immediately deployed for disaster relief This field verification unit is the Nantou County Red Cross AssociationOne of the food bank locations, hereinafter referred to as the Nantou Red CrossIs responsible for tasks like pre-disaster supplies preparation and disaster relief material distribution, helping the government bear the responsibility of disaster relief and aid In Taiwan, various natural disasters have characteristics of different duration and spatial coverage, wide or narrow With the normalization of extreme weather, the scale and number of disasters are gradually increasing and becoming harder to predict The required amount and type of materials differ by disaster, and they must address the lifestyles of the affected areas, rescue needs, traffic conditions, geographical restrictions, and other factors for varied material allocation, facing numerous challenges Typhoon Kanu severely damaged transportation in Nantou mountain areas Nantou County Red Cross planned the mountainous route Puli gt Fazhi Elementary School gt Qin'ai Village gt Aowanda to deliver supplies Disasters happen repeatedly We need to be prepared at all times Effective disaster preparedness can mitigate the impact, including swift response to material needs in affected areas, aid distribution, and even psychological support, providing added security for life and property of those in disaster zones Lack of Timeliness in Disaster Information To improve the living conditions and address the lack of supplies in remote areas, the Taiwan Food Bank Association has partnered with the Nantou Red Cross and has successively established food bank points in Nantou City, Puli, and Ren'aiLixing, Ruiyan, XinyiWangmei, Tongfu, Shuili, Lugu and Caotun among others9establish food bank locations, providing supplies worth a certain amount per household every month6001000in New Taiwan Dollars However, many challenges still need to be overcome during natural disasters For example, when typhoons, earthquakes, and landslides occur, the information source for disaster relief dispatch systems relies on post-disaster reports The time lag between reporting, response, and execution prevents timely adjustment and distribution of 'disaster relief' supplies based on the needs of affected areas, affecting rescue efficiency due to lack of timely information The 'preparedness' supplies of the Nantou Red Crosssuch as dry food, water, instant noodles, etc,are recorded manually in terms of stock, expiration dates, and distribution,When a disaster occurs, there is a chance that 'preparedness' supplies have expired and cannot become 'disaster relief' supplies It’s also possible that both conditions mentioned above occur simultaneously, leading to a need for more time to reassign 'preparedness' supplies into usable 'disaster relief' materials On the other hand, upon receiving information about shortages in disaster areas, the supplies donated by the public often grossly differ from the actual needs of the disaster zone, leading to an excess of supplies The Process of Material Operations Before and After a Natural Disaster AIAnticipating Natural Disasters Reinforcing the Accuracy of Preparedness Material Dispatch Application API Technology connects to compute the state of the climate, the intensity of disaster rescues, prioritizing the main tasks of the Nantou Red Cross and the needed areas of search and rescue Coordinated with the existing heavy rain and typhoon simulation disaster training of the Nantou Red Cross, a 'Natural Disaster Emergency Preparedness Material Dispatch and Supplement Decision System' is establishedreferred to as the Emergency Preparedness Material System。 In material management, inventory data along with immediate supply data are entered into the Emergency Preparedness Material System for comparison and analysis, helping the Nantou Red Cross quickly recognize materials like cookiesdry food, beverages, frozen food, toilet paper, etc, and determining whether they should be 'preparedness' materials or regularly distributed materials Adding to this, information forecasting understands the potential disaster conditions in remote areas, facilitating food delivery, addressing both front-end food wastage and backend practical needs When a natural disaster occurs, it enables faster response and decision-making, completing material deployment, hence increasing the speed of material operation transition20。 AI Emergency Preparedness Material System Helps Rapidly Adapt Material Distribution Through the field verification of the Nantou Red CrossAIthe system, material management, and related applications are promoted to more emergency response organizations in different areas, while continuously improving the alert functions within the Emergency Preparedness Material System, strengthening the technological foundation for alerts, enhancing prediction accuracySystem immediacy, and optimizing the data collection and analysis process Simultaneously, it can collaborate with government agencies, meteorological departments, or other rescue teams to discuss integrating more data sources, establishing a mechanism to share resources and data promptly, sharing information in real-time, helping more emergency response organizations enhance their disaster response abilities, seizing the golden rescue time 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-12-12」