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【2020 Solutions】 AI Enhancements, AOI Inspection Miss Rate at 0.1% Surpasses Manual Effort by 10 Times

Did you know a single golf ball can have up to 28 defect inspections? Manually, one can inspect 500 balls in an hour, but with AI, up to 6,000 balls can be inspected in the same time. Huiwen Technology has developed AOI (Automated Optical Inspection) technology that achieves a miss rate of 0.1%, which is ten times better than human inspection. Besides the golf ball industry, Huiwen Technology's AOI inspections are also being introduced to the textile industry and others.

Geng Cheng Lin, the founder and general manager of Huiwen Technology, has been an expert in artificial intelligence (AI) since 2013, recognizing the future potential and explosive power of deep learning (DL) and AI-based image recognition. AOI has always been a strong demand in the manufacturing industry, mainly to improve product quality for business owners, stabilize the quality of delivered goods, and use data from AOI inspections to improve processes, thus creating a virtuous cycle and further cost reductions.

Due to uncontrollable factors such as human eye fatigue and inconsistent standards, inspection encounters bottlenecks. The limit of human inspection miss rate after training is about 1-2%, and the situation worsens over time. AOI is a stable and capable of mass inspection device, achieving a miss rate of 0.1%, which is ten times that of human eyes, implying a detection rate of 99.9%. Of course, AOI also results in a 5%-10% over-inspection rate, which can be further screened manually. With the help of AOI, the burden of quality inspection is reduced, saving a considerable amount of labor time.

AOI Golf Ball Defect Inspection, Inspection Capacity Increased 12 Times per Hour

The first litmus test of Huiwen Technology's AOI technology was on golf balls. With their highly reflective, uneven surfaces, golf balls were previously inspected manually for defects. A tiny golf ball can have up to 28 defects, and traditionally, only 500 balls could be inspected per hour. A major domestic golf ball manufacturer, meeting the demands of Japanese customers, introduced AOI inspection two years ago. The high-speed, high-precision AOI system combined with AI deep learning image recognition technology conducts defect detection on golf ball surfaces, fully automates the feeding and outfeed process, replacing manual recognition of missed defects, and can immediately record defect conditions and report back, inspecting up to 200,000 packs of golf balls per year per machine, greatly enhancing customer satisfaction. However, this step took Huiwen Technology more than two years.

Golf Ball AOI Recognition Image

▲ Golf Ball AOI Recognition Image

Golf Ball AOI Recognition, 28 Surface Defects Unveiled

▲ Golf Ball AOI Recognition, 28 Surface Defects Unveiled

Lin Geng Cheng says, from data assessment and consulting, followed by data organization and tagging, selecting and verifying AI algorithms to AI training services, the golf ball data is like starting from zero, accumulating one by one. Thankfully, with full support from golf ball manufacturers, the efforts have finally bore fruit. With AI inspection, while manually one might inspect 500 balls in an hour, AI can handle 6,000, achieving effectiveness 12 times greater.

Unlike other companies, Lin believes that AI needs to delve deep into domains to scrape professional data since only with such domain data can AI perform well. Therefore, the company starts from individual projects, rather than setting an AI product from the beginning. Without quality data or a focused domain, the best algorithms cannot succeed in AI. Over the years, Huiwen Technology has accumulated project experience, gradually developing products while focusing on domain data and providing the latest AI algorithms to customers, growing together, creating a tighter collaboration, which is why, different from external fundraising, Huiwen's investors are customers or partners.

Evaluation to Official Launch: AI Introduction Requires Six Phases

The projects undertaken by Huiwen Technology are divided into several phases: 1. Evaluation period, 2. Initial Validation (POC) period, 3. Data Collection period, 4. Repeated Verification period, 5. AI Positive Cycle period, 6. Official Launch. The evaluation period involves understanding and assessing the Domain conditions of the demand side beforehand, followed by POC verification, extensive data collection after POC, entering repeated verification stage, and finally allowing AI to enter a positive cycle phase, achieving a certain level of effectiveness before the official launch. Generally, a project takes about six months to a year to develop. However, with more familiar PCB AOI projects, the first two stages are skipped, starting from data collection, thus significantly reducing the time.

'Regardless of this project or others, common questions from customers are: 'How much data is enough? When will AI learn?' Facing such questions, Lin points out that the reasons for these questions are: 1. The inexplicability of deep learning technology, as it is a black box; 2. Generally, customers lack the concept of AI technology. Thus, the company must patiently verify data repeatedly, identify the data needed by AI, accumulate and test it, and clarify and resolve all Domain conditions, which requires a lot of time and patience.

During the AI introduction process, customers have high expectations of integrating AI services, thinking that it can immediately replace human labor. Lin points out that this is not the case; the real value of AI lies in accumulating large volumes of high-quality data, which is then transformed and analyzed to establish AI training and verification models to fully address problems generated by manual processes.

Apart from inspecting golf balls, Huiwen Technology is currently targeting the textile industry for items such as fabric and shoelaces, and many industries have conducted POC trials through Huiwen, including the semiconductor industry, PCB industry, and other traditional industries.

AOI Fabric Defect Detection, Top Image Shows Before AOI Inspection, Bottom Image Shows After AOI Inspection

▲AOI Fabric Defect Detection, Top Image Shows Before AOI Inspection, Bottom Image Shows After AOI Inspection

Lin Geng Cheng indicates that the most difficult aspect of entrepreneurship is nurturing talent and customer recognition; customers often demand quick results, not realizing that AI adoption requires data accumulation and repeated verification, processes that cannot show results in less than six months.

Affected by the COVID-19 pandemic, the trend of globalization and centralization of the manufacturing supply chain has been disrupted, replaced by 'short region' supply chains, suggesting small, beautiful factories will flourish everywhere, potentially bringing new opportunities for AOI. Lin notes that high automation indeed offers opportunities for automatic inspection AI, however, relatively high capital investments, including automation equipment, mainframes, GPUs, and sufficient AI maintenance talents, are burdens that small and medium enterprises or small factories cannot bear, requiring government financial resources and input to facilitate smooth transformation.

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

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【解決方案】破壞式創新商模 奇翼醫電推出行動醫療裝置- 心電圖傳感器 打造遠距醫療當中最後一塊拼圖
Disruptive innovative business model Qiyi Medical Electronics launches mobile medical device-ECG sensor to create the last piece of the puzzle in telemedicine

With the advent of the post-epidemic era, the development of global telemedicine is in the ascendant, which has greatly increased the demand for smart medical technology in decentralized medicine Among them, if mobile medical devices can provide real-world at home or outside the hospital data for use in hospitals, it is believed that it will reduce the burden of diagnosis and treatment on doctors or medical personnel and reduce health insurance expenses To this end, Singular Wings Medical has launched a comprehensive telemedicine solution, which combines excellent wearable mobile medical device design, innovative software development, AI algorithms and cloud platform services, and will become the last piece of telemedicine puzzle David Lee, the founder and general manager of Qiyi Medical Electronics, said that his original intention to start the business was because he witnessed Taiwan's long-term pursuit of low-cost mass production, which led to the continuous decline in the value of the industry For example, in the past thirty years, The output value of the former Silicon Valley was similar to that of Taiwan's Hsinchu Science Park, but thirty years later, the output value of Silicon Valley reached US14 trillion at the end of 2020, while the output value of Hsinchu Science Park was less than NT15 trillion at the end of 2021 Seeing Silicon Valley's sensitivity to industry needs and disruptive innovations such as Uber, Airbnb, industry trends and the post-epidemic era have driven a surge in telemedicine services, thereby creating high industry value, so I started a business at the age of 45 and conceived how to combine it with Taiwan After more than ten years of accumulated industrial advantages and Silicon Valley's innovative model, we decided to help Taiwan's industry upgrade and find a new path through the integration of the medical industry, ICT technology industry and innovative business models Seeing that Taiwan has always been a gathering place for the most elite talents in the medical industry and electronics and electrical industry, I believe that through the combination of the two and innovative business models, we can have the opportunity to follow Silicon Valley and create a different business According to Taiwan’s Communication Diagnosis and Treatment Methods, Taiwan’s market demand for telemedicine is divided into two situations emergency such as COVID-19 and special necessity such as special geographical locations such as outlying islands or mountains It is allowed Carry out communication medical diagnosis In fact, the development of global telemedicine decentralized medicine is in the ascendant, but the demand for smart medical technology to meet decentralized medicine still needs to be realized In addition to the medical technology gap, it also includes medical treatment flow, patient identification, remote Remote consultation and collection are fueling the push for smart medical technology Li Weizhong observed that for 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measurement of cardiovascular diseases, the ECG sensor configuration can provide home assessment of sleep apnea OSA During the measurement, patients can discover potential and easily overlooked cardiovascular diseases, and users do not need to stay in the sleep ward for treatment After a boring night, through the ECG sensor patch and AI algorithm, patients only need to sleep at home for one night to receive an OSA test report If needed, doctors can access patient status remotely and instantly via any internet browser Therefore, through the ECG sensor wearable service, users can discover hidden and unknown cardiovascular diseases such as arrhythmias related to sudden death from the measurement process to avoid unnecessary regrets Qiyi Medical Electronics’ business model is mainly B2B2C, hoping to assist individuals, hospitals, enterprises, care services and other units to create a win-win situation Li Weizhong analyzed that the business cooperation model is quite flexible, whether it is 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Electric Energy will become the last piece of the telemedicine puzzle in the health wearable device-electrocardiogram service Li Weizhong said that in the short term, Qiyi Medical hopes to gain a firm foothold in Taiwan and become a common medical device in everyone's home, just like thermometers and blood pressure monitors The company is also constantly developing new indications Starting from electrocardiogram, coupled with AI and big data, it can deal with more chronic diseases In addition to cardiovascular diseases, we have also successively developed sleep apnea and other more special diseases The applications are aimed at the problems of elderly chronic diseases that modern people are very likely to encounter With a mid- to long-term plan, Qiyi Medical will enter the US and EU markets, become an international company, and continue to aim to become a data company, making good use of the company's long-term collection of data applications to provide services in diverse fields such 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【解決方案】小柿智檢 以「AOIAI」雙劍合璧,軟加硬體千錘百鍊 打通外觀瑕疵檢測任督二脈
Xiaoshi Intelligent Inspection uses the two swords of "AOI + AI" to combine software and hardware to open up the two channels of appearance defect detection and supervision.

Quality inspection, like a double-edged sword, has always been a favorite and painful subject for Taiwanese manufacturers When AI deep learning enters the industrial visual inspection of traditional manufacturing industries, it can not only save inspection manpower investment, solve the problem of inconsistent manual visual standards, overcome the limited visual recognition and defect detection blind spots of traditional automatic optical inspection AOI, and also enable real-time traceability Causes of quality problems The overall AIAOI visual inspection solution developed by Xiaoshi Intelligent Inspection integrates software and hardware to create efficient appearance defect detection capabilities, helping electronics OEM customers create high-efficiency products with a miss detection rate of less than 1 and an overkill rate of less than 3 Check the level Xiaoshi Intelligent Inspection was established in 2020 Although it is a new venture two years ago, it did not start from scratch Founder and CEO Hong Peijun and the core team have been deeply involved in Foxconn factories for many years and participated in countless smart factory-related solutions and process improvements , has profound AI deep learning development capabilities, and accumulated rich experience in world-class AI application implementation Seeing that AI industrial inspection must be the last mile for the manufacturing industry to move towards Industry 40, Hong Peijun resolutely decided to implement AI deep learning technology in the field of smart manufacturing with high output value, and specialized in the development of AI industrial visual inspection For the manufacturing industry, product inspection is the most important part of all quality control, but traditional industrial inspection faces two major pain points 1 Manual visual inspection Today, more than 95 of the entire manufacturing industry still relies on manual visual inspection Inspection makes it difficult for manual visual quality inspection standards to be consistent, and visual inspection of fine objects, such as passive components or highly reflective components, will cause long-term vision damage 2 Traditional AOI automatic optical inspection The product has limited visual recognition capabilities and blind spots in defect detection Among them, the detection of appearance defects such as scratches, oil stains, dirt or hair and other unexpected subtle defects has always been a problem in AOI applications Insurmountable difficulties AIAOI visual inspection overall solution is a great boon for appearance defect detection When designing the product roadmap of Xiaoshi Zhikan, customer group positioning and strengthening customer product services and value were important indicators Moreover, appearance defect detection has always been an unresolved pain in the manufacturing industry, Hong Peijun said With industrial quality inspection AI software as the core, Xiaoshi Intelligent Inspection provides an overall solution for AIAOI visual inspection It mainly promotes three major products, including "QVI-T AI deep learning inspection modeling platform software" and "AI six-sided defect inspection and screening machine" ” and “AI Industrial Quality Inspection Platform” The main customer groups served are semiconductor packaging and testing, EMS electronics foundry, small metal parts processing and other industries with high production capacity and high gross profit margin In response to customer needs, Xiaoshi Intelligent Inspection provides corresponding software and hardware services, combining self-developed AI deep learning software and hardware quality inspection equipment to reduce the manual visual burden on the production line and effectively improve the production quality of the factory In order to help equipment manufacturers and technical engineers with development capabilities accurately grasp product appearance defect detection, Xiaoshi Intelligent Inspection independently developed QVI-T deep learning detection software, which can provide customers with defect location, defect classification, defect segmentation, anomaly detection and text recognition Key functions such as this are different from the fixed detection methods of traditional software Algorithms can be refined based on different industrial detection methods and different APIs can be developed to connect devices with different lenses The software design of this platform is very lightweight It is a SaaS software built on public cloudprivate cloud It mainly involves simple image uploading, labeling, training modeling, and verification testing After completion, users can download models, SDKs, APIs, and reports Effectively help customers achieve AI inference functions Currently, most of the industrial inspection services on the market are traditional AOI software industrial inspection machines, which can only measure product contours such as the head and length of fasteners, etc, and cannot truly provide detection of subtle product surface defects such as screw head cracks and tooth damage There is a lack of such high-precision defect detection companies in the market, Hong Peijun observed Xiaoshi Intelligent Inspection developed and independently built the "AI six-sided defect detection and screening machine" from customized services in the past to providing standardized services for customers at the current stage It provides standardized testing services for fasteners in measurement and surface defects, as well as passive components High-speed surface defect detection of similar products This professional machine uses the AI deep learning AOI composite algorithm technology independently developed by Xiaoshi Intelligent Inspection Through parallel computing technology, it can achieve model inference up to 3 milliseconds per picture, and realize multiple complex defect detection on the electrodes and body of passive components This professional machine is mainly used for the inspection of fasteners, small metal parts and passive components In terms of competitiveness in the industry, the software hardware integration provided by the AI six-sided defect inspection and screening professional machine is an important core competitive advantage of Xiaoshi Intelligent Inspection It is not as simple as it sounds Hong Peijun said with emotion that this special machine is very important in the industrial inspection industry Commonly known as the highly integrated integration of optical mechanisms, electronic controls, software and algorithms, the process requires continuous optimization and iteration, and requires multiple client verifications and modifications After a long period of hard work, the technical threshold has also been raised The AI six-sided defect detection and screening professional machine will be the main product promotion direction of Xiaoshi Intelligent Inspection in the next 3-5 years It is believed that AI combined with measurement technology and surface defect detection will be an important source of core competitiveness of Xiaoshi Intelligent Inspection, Hong Peijun said AI six-sided defect detection and screening professional machine will be the main product promotion direction of Xiaoshi Intelligent Inspection in the next 3-5 years Faced with the booming development of Industry 40 in smart factories, customers often ask "Does quality inspection data have secondary use value" Hong Peijun said that the "AI Industrial Quality Inspection Platform" launched by Xiaoshi Intelligent Inspection has a machine learning mechanism , which can be used for secondary use of quality inspection data to provide customers with multiple functions including real-time monitoring and early warning of production quality, quality traceability analysis, quality factor assessment, process parameter prediction and recommendation Taking the successful introduction into the automotive parts factory as an example, through the prediction and recommendation of process parameters provided by the AI industrial quality inspection platform, when we know the product defects, we build a set of models based on the experience of past masters, coupled with the network connection data from the previous stage, After integration, we have process data, incoming material data, and quality inspection data We can predict whether these machine parameters have run out, and we can recommend whether the process parameters of certain sections should be adjusted up or down Through the AI industrial quality inspection platform, Xiaoshi Intelligent Inspection can help customers connect visual quality inspection results, process data and acceptance standards with the existing MES system of the customer's factory to improve production quality, improve efficiency and reduce costs In terms of business model, Xiaoshi Zhiqian also provides a software subscription system for the deep learning detection modeling platform software It provides public cloud customers with traffic subscription and charges based on the amount of image uploads, while private cloud customers adopt an annual license fee license charging mechanism In addition, the company also provides customers with a buyout charging mechanism for the overall solution equipment, and provides a one-year warranty, after which consumables and software update maintenance fees are charged annually Going in the opposite direction, using both hard and soft methods, with a missed detection rate of less than 1 and rapid modeling in 15 minutes Faced with various small-volume and multi-sample inspection needs in the manufacturing industry, general AI deep learning visual inspection usually requires customers to collect a large number of photos of defective products, which is time-consuming to label, and also causes customers to have difficulty in importing AI, and defective products cannot be collected The introduction cycle is long and implementation is full of risks If there are not enough bad samples, the model will be inaccurate Kosaki Chikan goes in the opposite direction and uses its product "AI Visual Inspection Model Development Tool" to train models through pictures of good products provided by customers It is relatively easy for AI to learn good products, no labeling is required, and the time can be quickly compressed to complete the modeling Take the implementation of IPC electronics industry - AAEON Technology as an example In order to reduce the manpower input of the quality inspection station in the PCBA production line and have standardized quality inspection, Xiaoshi Intelligent Inspection provides an overall solution for PCBA AI visual inspection software and hardware services, and conduct in-line inspection on the factory's highly automated assembly line, effectively saving inspection manpower investment, improving the standardization of quality inspection rates, and improving the problem of inconsistent standards caused by manual visual inspection Through the introduction of AI visual inspection software and hardware integrated solutions, we have effectively helped customers maintain an overkill rate of less than 3 in the past two years, and achieved high-efficiency performance with a missed detection rate of less than 1 In addition, this solution allows practitioners who do not understand AI to quickly operate modeling By installing the modeling tool on the device, when the customer has a new product number and needs to create a model, he only needs to provide 10 pictures of good products to scan under the device It only takes 15 minutes to quickly train the model In terms of product core strategic layout, compared with market competitors who rely solely on general software services to seize all manufacturing markets, it is not feasible to apply it to industrial inspection Hong Peijun has observed over the past 10 years and believes that only software hardware can With technical thresholds and focusing on one industry and field, only by adopting a standardized company's AI six-sided defect detection and screening special machine can it be replicated and scaled up, and the company can truly continue to move towards optimization and create product competitiveness, even if there are other competing products It’s not easy to compete for this pie, Hong Peijun said Xiaoshi Intelligent Inspection’s overall AIAOI visual inspection solution creates rapid modeling and excellent results for customers with a missed detection rate of less than 1 The most competitive AIAOI overall solution provider with global presence For new entrepreneurs, facing business expansion is a challenge every day Hong Peijun said that small companies are easily snatched away by large companies, company talents are poached by high salaries, lack of deep customer relationships, and the business team is not large enough, etc How to overcome this Hong Peijun believes that the key to success and competitiveness of a new start-up company is to be diligent in making up for mistakes, provide better services, provide more immediate feedback, and create more professional solutions to convince customers Since its establishment in 2020, Xiaoshi Intelligent Inspection has always gone against the grain in terms of product core strategic layout, surpassing the competitive market among its peers, and actively taking root in the overall solution of AI visual inspection software and hardware Hong Peijun hopes that Xiaoshi Intelligent Inspection will become the world's most competitive AIAOI overall solution provider for the electronics and semiconductor industries in the future, and provide the top AIAOI professional machines and equipment to the electronics and semiconductor industry customer base Hong Peijun said that the technical capabilities of the company's AI six-sided defect detection and screening professional machine have reached the top domestic level In order to speed up the research and development of professional machines to become more standardized and sell them to overseas markets, the company will conduct a fundraising plan at this stage, hoping to use legal persons such as the Capital Strategy Council to assist in more business connections and fundraising channels For the medium and long-term goals, Xiaoshi Intelligent Inspection will lay out the global market including mainland China and Southeast Asian countries At the same time, it will follow the international footsteps of major OEMs in global layout Under the target inspection project, it will continue to develop specialty products and spread towards the international field 「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.
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In construction site operations, implementing safety protection measures and establishing related processes are essential for controlling workplace safety Every business owner strives to minimize industrial safety risks To reduce the probability of workplace accidents, it is particularly important to inspect personal protective equipment PPE and safety measures The Yongyi Smart Construction Site Security Platform utilizes an AI-embedded system, not only to detect whether workers are properly wearing helmets, but also to manage access control at construction site entrances and verify worker identity The Smart Construction Site Security Platform is also a part of the government's push for the Smart Construction Label Initiative 'Smart Site Management' is one of the three main items under the 'Maintenance Management' indicator, highlighting the importance of 'Smart Site Management' This solution includes access management, surveillance management, safety management, and environmental monitoring as aspects of its AIOT solution Feature Highlights 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-11-09」