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【2020 Solutions】 ASUS AI Deep Learning Image Recognition Makes Defect Detection Easier

For the manufacturing industry, replacing manual visual inspection with automated optical inspection is common, especially when the yield of 3C or semiconductor products is high. General automated optical inspections often face the bottlenecks of insufficient defect samples and difficulties in qualitative and quantitative recognition. Using AI deep learning for image defect detection has become increasingly significant!

AI detects minute defects, ASUS makes smart manufacturing 'visible'

'Initially, we hoped to promote upgrading with our 3C supply chain partners steadily, assisting the industry to enhance and face international competition,' said Chang Quande, ASUS Global Vice President and Co-General Manager of the Smart IoT Business Group. ASUS Smart Solutions Business Unit uses AI deep learning to perform various workpiece defect detections, and layout after accumulating experiences is a priority task.

ASUS Global Vice President and Co-General Manager of the Smart IoT Business Group, Chang Quande

▲華碩全球副總裁暨智慧物聯網事業群共同總經理張權德

For metal component manufacturers, detecting defects on surfaces is relatively difficult due to the reflection of light, which often causes actual defects to be overlooked. Mastery of optical properties and the specifics of component surfaces is crucial. The ASUS Smart Solutions Business Unit not only has AI experts but also a digital imaging technology team with unique post-processing skills and strong augmentation capabilities. They can achieve correct defect data collection and train AI models efficiently even with a very small number of defect samples. 'General optical inspection accuracy is about 85-90%, and high precision-seeking manufacturers would not use it, as it implies a +/-10% defect misjudgment,' said Chang Quande. Whereas manual visual inspection has an accuracy rate of about 93%, it is labor-intensive and carries occupational hazard risks. ASUS has now enabled AI to achieve 98% accuracy, fully capable of replacing manual inspections and certain traditional optical inspections.

Previously, it took three people to manage quality control across three production lines, now only one is needed

In recent years, many manufacturing industries have been returning to invest in Taiwan. Major metal structure stamping plants have also committed to establishing new factories. ASUS has designed their three-in-one defect detection stations, capturing images through edge computing, uniformly training an AI model, and utilizing the same AI inference workstation to perform defect detection calculations. Quality control stations across various production lines now monitor these processes in real-time. Previously, three production lines required three people for quality control; now, only one is sufficient, increasing the detection rate from 93% to 98% and reducing costs by 5%. Accompanied by the reallocation of human resources, the stamping plant has achieved smart manufacturing and has broken the curse of increased production costs due to returning investments.

ASUS IoT Applications Industry

▲ASUS IoT 應用產業

除了金屬機構件之外,塑膠成型件、印刷電路板等電腦周邊元件生產業及系統組裝業都能運用AI 深度學習影像瑕疵檢測做高精度品管,目前也有半導體業正在優化導入華碩AI 深度學習影像瑕疵檢測,以補足自動光學檢測在晶圓層所抓不到的瑕疵,盼藉由AI的助力突破良率瓶頸,降低人工目測或自動光學檢測已知的誤判所造成的損失,更能利用人工智慧大數據針對品質瑕疵種類做統計分類以歸納出瑕疵形成原因,從源頭改善進而減少製程瑕疵。

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

Recommend Cases

【解決方案】瑕疵辨識率達百分百 耐銳利科技獲面板大廠青睞
Defect identification rate reaches 100%, Nairi Technology is favored by major panel manufacturers

On the machine tool production line, there are some slight differences in the first step of assembly Accumulated tolerances will cause the assembly work to be repeated, which is time-consuming and labor-intensive, resulting in shipment delays that will impact the company's reputation Narili Technology Company focuses on the field of smart manufacturing and provides various AI solutions It uses machine learning models to inherit the experience of old masters In the CNC processing machine assembly and casting process, it uses AI to analyze production line data, accurately adjust various data, and improve Production accuracy is 25 This AI production line data analysis system is called "Master 40" by Huang Changding, chairman of Naruili Technology It is the most evolved version of the master plus artificial intelligence It has been used in machine tool processing factories with remarkable results In addition, Nairi Technology used AI defect detection technology to participate in the 2021 AI Rookie Selection Competition of the Industrial Bureau of the Ministry of Economic Affairs, assisting AUO in advanced panel image defect detection, with an accuracy rate of 100, and won the award Assisted panel manufacturer AUO to solve problems with 100 accuracy in defect detectionHuang Changding further explained that during the production of general panels, edges and corners are There may be defects in the corners Although the defects are visible to the naked eye, AOI is often difficult to identify, causing the detection error rate to often exceed 30 Therefore, re-inspection must be carried out with manpower to improve the accuracy rate However, in response to the demand for a small number of diverse products and insufficient manpower, using AI detection is indeed a good method Nairui Technology, founded in 2018, has been able to win the favor of major panel manufacturers with its AI technology in just three years In fact, it has been honed in the field of CNC machine tools for a long time Tang Guowei, general manager of Narili Technology, pointed out that the top three CNC machine tool factories in Taiwan hope to introduce AI into the two production lines of assembly and casting Among them, on the assembly line, in order to maintain the accuracy of assembly, every part of the component is designed Tolerances are designed During assembly, each component is within the tolerance However, the cumulative tolerance still fails the final quality inspection and must be dismantled and reassembled This is not only time-consuming and labor-intensive, but also causes waste "After entering the production line, I realized that some masters have accumulated a lot of experience and are good at adjustment After his adjustment, the accuracy rate has improved a lot and the speed is faster" On the contrary, the new engineers did not Based on experience, it takes a long time to adjust and may not pass the quality inspection The yield rate of Master 40 system has increased significantly from 70 to 95Tang Guowei then said that the original size data set by Master during assembly All were recorded on paper After the information was written, it was stored in the warehouse and sealed No one studied the relationship between the dimensions Narili assists customers in designing the Fu 40 system Through the human-machine panel, the master can directly input the measured dimensions and related data during assembly After collecting data from different masters, AI algorithms are used to analyze the relationship between the data and create an AI model The AI model automatically notifies the operator what size to adjust to, and the quality inspection will definitely pass In this way, the yield rate will be improved It has increased significantly from 70 to more than 95 Narili Technology Company focuses on the field of smart manufacturing and provides various AI solutionsTang Guowei added, assembling the spindle of a CNC processing machine It took four hours In the first step, the machine made measurement errors, including vibration, temperature, speed, etc that were out of range It had to be dismantled and reinstalled, which took another four hours How to adjust after disassembly depends on the experience of the master At first, the master may have done the best assembly method based on experience, but the error rate was also 30, and the assembly took several days With the assistance of AI masters, the assembly time only takes half a day, and the yield rate reaches over 95, saving a lot of time and manpower "Use the AI model of machine learning to collect the experience of all the masters and provide it for AI learning The first step is digitalization, and the second step is knowledgeization This is the transformation of the enterprise "An important key", Huang Changding believes that Narili Technology is an important partner in the transformation of traditional manufacturing from automated production to digital transformation In addition, another industry that Naili Technology focuses on is the smart car dispatching system of the leading brand of elevator manufacturers The so-called car dispatch referring to the elevator car means that if there are more than two elevators, group management is required In the past, car dispatching was based on fixed rules If the elevator was closer to the requested car, that elevator would be automatically dispatched On the one hand, it did not take into account that dispatching a car if the elevator was called too many times might make other people wait longer The previous vehicle dispatching model did not take into account the usage characteristics of the building, resulting in a lot of waste For example, in an office building, there are peak hours in the morning, lunch break, and afternoon after work AI smart car dispatch can be flexibly adjusted according to off-peak and peak hours, increasing the efficiency of car dispatch, reducing waiting time, and reducing wasted electricity Introducing elevator smart dispatch to improve transportation efficiency and have environmental protection functionsHuang Changding added that just like the previous traffic lights at intersections, the system has already The number of seconds to stop and pass on highways, sub-trunks and small streets is programmed Smart traffic lights are now used to flexibly adjust waiting times to make road sections prone to congestion smoother Using AI to learn usage scenarios and introducing a smart dispatch system into elevators will improve transportation efficiency and make it more environmentally friendly In addition to introducing smart elevator dispatching, Nairili also introduced AI into the smart production and shipment scheduling system of elevator factories Elevator factories often cannot accurately estimate the customer's elevator delivery date For example, office buildings or stores must be completed to a certain extent before the elevator can be installed on the construction site If affected by unexpected factors such as delays in the customer's construction period, the elevator factory will often be idle or the schedule will be difficult to arrange Tang Guowei pointed out that generally those who understand the progress of client projects may be from business or engineering, but overall, the accuracy rate of shipments is only about 60, which means that 40 of them will not be shipped as scheduled Therefore, if the shipping schedule can be accurately estimated, the production line can be freed up for emergency orders or other product production needs The AI smart scheduling system will analyze past shipment data, about 20-30 parameters such as climate, distance between the factory and the construction site, and customer credit, and put them into the AI algorithm to accurately predict whether shipments can be made as scheduled goods Huang Changding also specifically stated that the machine learning of Naili Technology is not ordinary machine learning, but also incorporates various calculation methods such as traditional image processing technology and statistics Only by being very familiar with the domain knowledge can we make good products AI models are also where the company’s competitiveness lies He emphasized that the data that general SaaS platforms can process is very limited, and the accuracy rate has increased from 70 to 75 at most Naili’s strength lies in AI algorithms and machine learning, and it must be coupled with in-depth industry knowledge to produce output Good AI model Narili Technology started with the AI project, gradually deepened the technology, chose to start with the more difficult tasks, and accumulated rules of thumb It is expected to develop SaaS services this year 2022, based on customer needs starting point, gradually gaining a foothold and becoming an important partner in smart manufacturing The picture left shows the general manager of Naruili Technology Tang Guowei and Chairman Huang Changding right「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.
Understand customers better than they do themselves, business opportunities created by the pandemic doubles the performance of Spingence Technology

"After the COVID-19 pandemic, even though we could not expand business overseas, the pandemic increased demand for AI automated optical inspection AOI and drove another wave of rapid growth in performance," said Jesse Chen, Founder and President of Spingence Technology The company started early in AOI and accumulated a wealth of experience, resulting in performance in 2021 growing multiple times compared with the previous year Spingence Technology's AI technology has great potential, and its fundraising plan successfully attracted strategic investors, such as the leading industrial computer company Founded at the end of 2015, Spingence Technology started out as a developer of automation software to help customers lower the barrier to automation In just two years from 2017 to 2018, AI technology quickly took off At that time, Jesse Chen observed that product defect detection caused headaches for companies in the process of automating manufacturing The traditional method of manual visual inspection was time-consuming and laborious Moreover, human error easily occurred and AI deployment could not be customized, resulting in high investment costs for enterprises Seizing the AOI market, successful application of AI optical defect detection "The gap in AOI is defect detection Since defects cannot be clearly defined, conforming products were often labeled as non-conforming products to meet the customer demand of not releasing defective products As a result, the overkill rate is often very high, which not only increases the cost of the manufacturing plant, but also lead to a waste of resources" In addition, there is strong demand for process automation due to the shortage of labor in the production line, which created a rare business opportunity for Jesse Chen AI optical defect detection has become the focus of Spingence Technology's AI applications After accumulating nearly 8 years of experience in production line automation, Spingence Technology target customers in three major industries, namely passive components, connectors, and semiconductors, and established a huge database for the production line product defect data it collected Since Spingence Technology started early, it enjoys the advantages of a first mover and continues to optimize database data Its wealth of experience enables it to quickly determine customer needs and propose solutions Spingence Technology uses image recognition and deep learning technologies to develop AOI algorithms, and developed AI defect detection solutions with an accuracy greater than 99 In terms of specific benefits, the overkill rate in the semiconductor industry can be significantly reduced from an average of 5-8 to less than 3, and the overkill rate of passive components can also be reduced from 5 to 12, which can save customers nearly NT300 million in expenses This not only reduces the waste of human resources, but also makes Spingence Technology a good helper for customers' sustainable intelligent manufacturing The outbreak of COVID-19 at the end of 2019 has changed the way people live and work around the world During the pandemic, demand on automation in the manufacturing industry significantly increased due to the need to avoid frequent contact between people Spingence Technology has a good reputation in the industry, so business kept coming in and doubled the number of customers and revenue The secret to winning Follow the footsteps of customers and always think more than customers In addition to Taiwan, Spingence Technology has also extended its reach to markets such as China and Vietnam, where Taiwanese businessmen gather The team in China is expected to increase from 3-4 people to 10 people, and Vietnam also hopes to have a team of 5 people to provide closer services to customers "Spingence Technology always follows the footsteps of its customers We are wherever our customers are" Jesse Chen went on to say that although the pandemic has brought another wave of demand for AI automatic detection, due to the impact of border controls, it was hard to go on business trips Meanwhile, overseas markets on-site personnel to provide nearby services, including consultation and diagnosis, AI implementation, and calibration, all of which require dedicated personnel Spingence's automation software development platform integrates modularized visual inspection, motion control, IO control, and AI analysis functions Coupled with the AI training software "AINavi", one heat sink inspection machine can complete multiple inspections and continue to train the AI deep learning model, which will further lower the miss rate of the machine and improve its inspection quality The integration of AINavi and automation is already sufficient to meet most functional requirements of customers, and then a small number of customized services are provided for different industries and customer needs This allows the company to quickly provide solutions needed by different customers Popular among strategic investors, the company has attracted investments from industrial computer companies and venture capital Spingence Technology has made a mark in the field of AIAOI inspection in the manufacturing industry, and has gain the favor of strategic investors In 2019, a leading industrial computer company made a strategic investment in Spingence Technology and integrated the AINavi deep learning visual inspection tool with the company's complete hardware platform The cooperation between the two parties provides more complete service solutions to customers, creating an example of win-win through "big large company leading small start-up" In February 2022, Spingence Technology reported another good news in its fundraising and received an investment from venture capital, all of its original major shareholders also increased their investment, and nbspSpingence Technology successfully completed the Pre-A round of funding The company will continue to expand its business in the short term, and establish a foothold in China and Vietnam In the future, it plans to build expert systems for passive components, connectors, and semiconductor industries, deepening its domain knowledge and data analysis to create greater value for customers Spingence Technology prides itself as a management consulting company for the manufacturing industry, that is, it provides customers with the most appropriate and valuable consulting services through consulting services, diagnosis, introduction, system launch, personnel training, model optimization, and AI model management

【解決方案】五年磨一劍 太奇雲端專注影像辨識 獲智慧城市創新應用獎
After five years of hard work in image recognition, Touch Cloud won the Smart City Innovation Application Award

During the opening ceremony of the 2022 Smart City Summit amp Expo co-organized by the National Development Council, Ministry of Foreign Affairs, Taipei City Government, Taoyuan City Government, Kaohsiung City Government, and Taipei Computer Association on March 22, 2022, founder and president of Touch Cloud Cheng-Hsun Li went on stage to receive the "2022 Smart City Innovation Application Award_Smart Security Award" This award is hard-won because after five years of hard work, Touch Cloud brought its core technology of AI image analysis back to Taiwan after gaining popularity in overseas markets, becoming an important smart city solutions provider "Since the company was established, we have positioned ourselves to make AI products that are stable, easy to use, and truly needed by the market" The company's positioning is very clear, this step took Touch Cloud five years It was not until the beginning of 2020 that Touch Cloud launched its first intrusion detection product In less than two years, Touch Cloud has now launched seven products, with each product receiving excellent reviews from the market Specializing in the field of smart cities, Touch Cloud successfully entered the Asian market Founded in February 2016, Touch Cloud originally focused on AOI defect detection However, the definition of defects is different for every customer As a result, applications in this field are mostly project development and could not be commercialized The company later directed its efforts to AI Application Box, a product that integrates software and hardware, and focused on smart cities, including transportation, industrial safety, and security related markets In view of the high acceptance and price advantage of AI in overseas markets, Cheng-Hsun Li targeted the overseas market in the early stages of the company's development, and has produced many successful results in several major countries, including Hong Kong, Singapore, and Thailand Among them, Touch Cloud successfully entered the Hong Kong market with its debut in the Hong Kong International Airport project In 2018, Hong Kong International Airport planned to monitor ships around airline oil storage platforms to prevent ships from colliding with the oil storage platform However, the oil storage platform is located in the middle of the sea and lacks electricity and Internet connection, so it could only set up a camera on shore 3 km away from the platform In addition to the long distance and poor line of sight, monitoring was also affected by weather conditions, such as clouds and fog, and was ineffective Touch Cloud customized an AI algorithm specifically for the project, and continuously collected image data for model training It took half a year of discussions with the customer and system corrections to finally achieve an accuracy rate of 98, successfully completing the goal Touch Cloud won the 2022 Smart City Innovation Application Award_Smart Security Award Minister of Economic Affairs Mei-Hua Wang on the left, Touch Cloud founder and president Cheng-Hsun Li on the right Touch Cloud products have three advantages that provide customers with a better AI user experience 1 Plug and play 2 Provides flexible services, in addition to standard products, customized services meet customers' needs for quick launch and reliable problem solving 3 High adaptability and ability to achieve extremely high recognition accuracy in different environments Cheng-Hsun Li believes that the design of AI products should be as simple as using a "home appliance" and have a clear purpose Therefore, Touch Cloud built an AI Application Box to design products from the perspective of scene applications, focusing on image analysis related to "people" and "vehicles" At present, a total of seven products have been developed, including KekkAI personnel intrusion detection, card swiping and tailgating detection, KekkAI-H construction site safety detection, Abaci-P people flow and head count, Abaci-V traffic flow and vehicle count, Greygoose personnel intrusion detection and people flow, GotchA cross-camera person tracking search, and AISense license plate recognition Cross-camera tracking product GotchA won the Smart City Innovation Application Award GotchA is the product that won the Smart City Innovation Application Award This cross-camera tracking product is unique in the market Its system uses AI technology to search and track people by analyzing their features at the time Users can use image search to search for the path of a specific person in multiple cameras they can also use multiple appearance features to find suitable target groups Using GotchA, you can actively search for lost people, understand the shopping behavior of VIP customers in the mall, and even manage the footprints of visitors in the building For example, it is not uncommon for children to get lost in hypermarkets GotchA can access footage from the entrance camera for an image search, and compare the walking path of the child to quickly find the missing child Using GotchA in shopping malls and amusement parks, where people come and go, to find lost people It not only significantly reduces the time spent by 90, but also transforms the traditional approach of the service counter making an announcement to the lost person into an active search based on image analysis, thereby improving service levels and accuracy Touch Cloud's excellent AI image analysis technology is favored by large enterprises Cheng-Hsun Li said that his experience abroad has taught him to help customers find AI usage scenarios For example, a T-Bar large advertising billboard operator in Thailand wants to attract business, and advertisers want to understand the flow of people to evaluate advertising effectiveness The T-Bar company has more than 1,000 cameras and can determine the type of vehicle from the images and then calculate the number of people, which can be converted to advertising effectiveness After Touch Cloud used the data for training, it can even identify special vehicle types in various countries For example, the nbsp"pickup truck" is a special vehicle type in Thailand Model training is carried out through Open Data, scenario data, and Touch Cloud's self-built database, and can accurately identify traffic flow and vehicle type, which is used to estimate the number of people reached by the advertisement Rapid business development after returning to the Taiwan market from overseas Touch Cloud currently accounts for 70 of the overseas market, with customers in Thailand, Hong Kong, Singapore, Malaysia, Japan, South Korea, and the Philippines In the future, it will also develop into other Asian markets, such as Vietnam In addition to the Asian market, Touch Cloud has not forgotten to serve Taiwanese customers, and began to actively recruit partners to jointly develop the Taiwan market in June 2021 So far, the number of customers has quickly accumulated to more than a hundred Touch Cloud's excellent AI image analysis technology is favored by many companies, and most investors are strategic partners, working together to create synergies and allow Touch Cloud's technology to be quickly applied Cheng-Hsun Li said that it often takes more than five years for an AI startup to get its operations on track, and it takes at least three years to cultivate good AI talents Results are gradually emerging thanks to the considerable flexibility and space given by strategic investors to the company Touch Cloud products are already being put into practical use in major Asian countries such as Hong Kong, Singapore, Thailand, South Korea, and Japan, and are expected to enter more Asian countries within two years, driving more advanced image analysis applications The company hopes to complete representative cases in Asian markets every year, and move towards an IPO as a company featuring AI products