:::

【2021 Solutions】 Industry-university cooperation shows results. National Taiwan University of Science and Technology’s Artificial Intelligence Operations Management Research Center uses AI to assist enterprises in digital transformation.

In intelligent systems, AI plays a key role. In addition to cultivating professional AI talents, the Artificial Intelligence Operations Management Research Center of the National Taiwan University of Science and Technology also actively conducts various project studies with enterprises to accelerate the implementation of industrial intelligence in Taiwan. One of the cases uses artificial intelligence and machine learning methods to use quality information for maintenance prediction and planning, which greatly improves equipment reliability and product quality. Using quality defect detection AOI technology can reduce the rate of missed defects.

Yu Wenhuang, director of the Artificial Intelligence Operations Management Research Center of the National Taiwan University of Science and Technology, observed that industry demand for AI is increasingly strong, and electronic manufacturing, finance, medical and other fields have greater development potential. On the one hand, the above-mentioned industries have a high degree of informatization, and automation products Online technology and the digital environment are mature and have the conditions for the development of AI technology; on the other hand, because the data required by the industrial environment has been retained, managed and used, it is easier to promote the application and solutions of AI technology when the concepts and data are available plan.

Quality defect detection AOI technology effectively reduces the wrong kill rate

For example, in the field of smart manufacturing, the team of the National Taiwan University of Science and Technology's Artificial Intelligence Operations Management Research Center assisted Taiwan's major electronics manufacturers in constructing a production line equipment diagnostic system and building a sensing network architecture in the production line equipment at the manufacturing site to detect Measure and record the operating status of the machine. Through big data analysis, a warning can be issued when an abnormality occurs on the machine to remind the manager to schedule maintenance. We use the AOI quality defect detection process, combined with machine vision and deep learning technology, to detect defects in electronic parts and perform real-time control and monitoring to assist companies in developing automated optical inspection stations, surface defect algorithms, and management application functional services.

In the flexible printed circuit board (FPC) industry, quality defect detection technology is used for image identification, mainly for re-inspection after the initial inspection, and the original inspection results are designed to be re-inspected. When doing defect detection, ordinary factories often believe that "they would rather kill a hundred by mistake than let one go" and adopt the most stringent testing standards. With the current testing technology and process, it may cause excessive detection and waste the cost of good products. .

National Taiwan University of Science and Technology Artificial Intelligence Operations Management Research Center focuses on intelligence Manufacturing Solutions

▲The Artificial Intelligence Operations Management Research Center of National Taiwan University of Science and Technology focuses on smart manufacturing solutions.

Lecturer Professor Cao Yuzhong, director of the National Taiwan University of Science and Technology Artificial Intelligence Operations Management Research Center, said that the current flaw detection, AI model and algorithm construction and training of the National Taiwan University of Science and Technology Artificial Intelligence Operations Management Research Center have achieved preliminary results. The center hopes to use images to The results of the identification can help companies quickly identify defects and quality status of products during the production process. After that, the next stage can start from the source, how to optimize parameters, improve behavior in the production process, and assist the factory to optimize the process. Better. During the product production process, the parameters of the machine equipment can be used to analyze machine data abnormalities and summarize different patterns for future maintenance and quality management to provide reference for enterprises in the application field.

The epidemic is the biggest catalyst for digital transformation for enterprises. Director Cao pointed out that the introduction of AI to promote digital transformation of enterprises is not necessarily just based on reducing costs or improving production efficiency, but must be based on the fundamental development goals and the essence of the problem. Process analysis, thinking about how to use AI or ICT technology to serve and meet process and customer needs. This process often requires breaking out of the existing framework to help companies reshape new operations and management models to effectively improve corporate performance.

Chair Professor Cao Yuzhong, Director of the Artificial Intelligence Operations Management Research Center of National Taiwan University of Science and Technology
▲Chair Professor Cao Yuzhong, Director of the Artificial Intelligence Operations Management Research Center of National Taiwan University of Science and Technology

The biggest challenge for enterprises introducing AI: improving customer trust

In the process of expanding AI industry-university cooperation, Yu Wenhuang believes that the biggest challenge is to enhance the trust of enterprises in you. For customers, a certain degree of trust is required before the Know-How of the production line can be communicated to you. Share and tell you where the focus of business is. In the absence of business trust, it is difficult for AI industry players to analyze the availability of processes and data. Enterprises usually consider two key points when choosing AI cooperation partners:

1. When cooperating with you, will the data and results be sold to others?

2. Will the cost of customization be too high? Although companies are less wary of academia, Director Yu still believes that gaining customer trust and jointly establishing sustainable AI innovation application capabilities and development goals are the key to The key factors for all ICT companies to face industrial customers and their ability to provide AI solutions.

Regarding the cultivation of AI talents, Yu Wenhuang also has his own unique insights. He observed that the education system from junior high schools, high schools to universities has driven the trend of AI. However, AI technology itself has many theoretical foundations and industrial knowledge that must be integrated. When talking about AI talent cultivation, we should first define how to construct a talent development system or route in the AI ​​field, what types of people are needed to introduce AI into the economic system, systematize talent positioning and characteristics, and let talents who are interested in investing in the AI ​​industry understand how to use their own The goal measures the types of AI skills and jobs that can be developed.

Secondly, it is to help companies that want to promote AI in a systematic way to understand, whether it is developing applications or building technical teams, how to measure the talent needs and technical blueprint corresponding to business goals. It not only plays the role of problem-solving, because AI It is just one of the ways to solve the problem. Only by assisting enterprises to establish innovative consciousness with AI R&D thinking can we truly implement industrial development, strengthen demand and promote both supply and demand at the same time, and accelerate the implementation of AI applications and talent cultivation.

NTUST Artificial Intelligence Operations Management Center provides a number of smart manufacturing solutions

Regarding smart manufacturing solutions, the solutions provided by the Artificial Intelligence Operations Management Center of National Taiwan University of Science and Technology are as follows:

. Intelligent predictive maintenance

Adopting artificial intelligence and machine learning methods, using quality information for maintenance prediction and planning, greatly improving equipment reliability and product quality, establishing failure modes and reliability analysis based on different equipment operating characteristics, and using process control analysis to trace products Quality history helps on-site personnel eliminate operational abnormalities in a timely manner.

. Smart dispatch and scheduling planning

According to the characteristics of the industry, develop intelligent labor dispatch and scheduling algorithms to effectively shorten setup time and total working hours. For example, for a variety of workpieces, the production schedule must meet conditions such as combined material preparation, group production, and specific process sequences. From the group production of workpieces, the assignment of adapted production lines, to the multi-parallel single-machine scheduling that adjusts the production sequence of each production line under grouping, the optimization algorithm is introduced to design a complete smart schedule. system.

. Deep learning and automatic optical inspection

Improve quality defect detection AOI technology, using machine vision and deep learning, which can detect flat and curved surfaces of metal electronic parts, and perform real-time control and monitoring, including automated optical inspection stations, metal AOI defect algorithms, and modular design and other application technologies.

The design elements of this algorithm: 1. Automated optical inspection station 2. Metal AOI defect algorithm 3. Modular design

. Smart Situation Room

Combined with high-end graphics card flexible assembly units, including processing machines, industrial robot arms, collaborative robot arms, engineering inspection stations and conveyor belts, a smart war room with digital twin technology is established. The technical features include real-time monitoring, data integration, data Transparency and data visibility.

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

Recommend Cases

【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」

【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 telemedicine decentralized medicine to be successfully implemented, it is best to use telemedicine devices that are used outside the hospital or at home and are easily available in daily life Among them, the data of the device is the key It can provide doctors with out-of-hospital real-world data Real World Data or Real World Evidence that they can trust and apply, so that they can improve their diagnosis and treatment methods In fact, this type of telemedicine device is not popular, making remote medical care difficult to complete In addition, as the number of wearable devices such as bracelets and watches increases, most of the data that these devices can truly provide is insufficient for medical purposes and is not easy to validate and verify Li Weizhong said that people are paying more and more attention to health awareness, which is a positive encouragement for telemedicine devices He believes that as long as there is an appropriate business model and the right way to cooperate with hospitals and doctors can reduce the burden on doctors or medical personnel and reduce health insurance expenditures, Qi Yi Medical Electronics will definitely have the opportunity to become the last piece of the puzzle in telemedicine Founded in 2015, Qiyi Medical Electronics’ core team consists of 22 diversified professionals, including young engineers with medical, engineering and information backgrounds and experienced entrepreneurs, working together to create an overall solution for remote healthcare The solution includes hardware design, software development and backend cloud platform services for the mobile medical device Beatinfor Health electrocardiogram sensor Electrocardiogram ECG is one of the most important vital signs body temperature, pulse, respiration and physiological data of the human body, which can reflect various physiological changes in the human body, such as cardiovascular health, inflammation, infection, bleeding, injury or anxiety index changes For this core concept, Qiyi Medical is committed to using wearable electrocardiograms as its core technology, while collecting important vital signs and environmental parameters such as electrocardiograms, and building AI algorithm systems and backend cloud platform services based on big data and machine learning to help solve remote problems Specific chronic diseases such as cardiovascular disease, sleep problems, and metabolic diseases are the most important in medical treatment Electrocardiogram sensor continuous physiological data monitoring reduces the risk of death in acute heart failure patients by 11 within 30 days after discharge In order to realize remote medical services, Qiyi Medical Electronics has launched a complete set of remote medical care solutions, including wearable mobile medical devices-electrocardiogram sensor BEATINFO ECG, BEATINFO HEALTH APP, and AI algorithms , web pages and BEATINFO HEALTH cloud service platform The BEATINFO ECG sensor is an exclusive device for the BEATINFO HEALTH APP health cloud platform It can be used continuously for 40 hours when fully charged The device is only 15g This sensor can collect the user's electrocardiogram, respiration, and skin temperature through a patch or chest strap , body movements, postures and environmental parameters Currently, BEATINFO ECG sensor has 8 patents in the United States and Taiwan, and won 2 German iF Design Awards in 2017 Mobile medical device-electrocardiogram sensor can provide continuous physiological data monitoring In terms of overall technical features, the BEATINFO HEALTH cloud service platform has four key physiological data detection characteristics continuity, long-range, real-time and dynamic In terms of operation, users can download the BEATINFO HEALTH APP on Android or iOS systems Its interface can provide physiological data status, order health assessment reports such as one-day sleep assessment report or cardiovascular health assessment report, and high-intensity exercise test Cardiovascular assessment reports, third-party remote medical consultation services and other functions Users use patch-type or chest-strap ECG sensors paired with end-to-cloud platforms for continuous physiological detection Before being transmitted to the cloud for further calculations, all data will be de-identified and made available to professionals Data reports are provided for physician judgment The BEATINFO HEALTH cloud service platform has powerful noise filtering processing capabilities, fast waveform recognition and judgment, as well as highly complex cloud architecture and communication technology Why is the noise filter processing capability so important Because medical equipment in general hospitals must require users to complete short-term measurements under static conditions Usually, data in life situations outside the hospital cannot be collected by the hospital, and this data is very important to doctors It is increasingly important to understand the progression of the disease and the condition of patients leaving the hospital Therefore, if we continue to record very weak ECG signals in daily life, we actually need to overcome a very high technical threshold After these signals are processed by the noise, they will first be judged by the AI algorithm before preliminary and rapid conclusions can be made Users can instantly avoid certain fatal risks The cloud architecture provides a deeper level of second-order computing and also covers the business model architecture It provides service models such as user management, automatic report generation, record keeping, alarm notifications, and connection with more services such as third-party alarms Emergency rescue, third-party medical consultation, doctor and patient docking, medical treatment cash flow and other functions In terms of competitive advantages in the industry, compared with the industry's braceletwatch products, Qiyi Medical's electrocardiogram sensor BEATINFO ECG provides accurate medical-level measurements, and can continuously record and collect physiological data, improving any Sudden or sporadic symptoms may occur Compared with the electrocardiogram patch of its peers, it provides real-time data return and web-based management tools, and can produce various reports for managers to remotely manage a large number of users on the web According to statistics from Beijing Medical University, the mortality rate of patients with acute heart failure within 30 days after discharge is as high as 11 If an electrocardiogram sensor is installed on the patient for continuous and real-time monitoring for 30 days, it is possible to reduce part of the risk of death, and at the same time, it can Significantly reduce health insurance costs Additionally, in the case of cardiovascular disease, if the user wears the device for a period of time, regular cardiovascular assessment reports can be obtained and provided for follow-up in-depth examinations by doctors In addition to the 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 leasing or buying out wearable measurement devices, or providing annual report subscriptions to reduce the cost of purchasing devices for users, such as including 2-minute electrocardiogram, Flexible subscription package including 7-day cardiovascular health assessment, exercise cardiovascular health assessment, sleep health assessment report, etc Group cardiovascular monitoring system solution creates a many-to-many real-time physiological information monitoring platform to replace diagnosis with prevention In addition to providing individual users with remote mobile physiological data measurement, the BEATINFO cloud platform provides a "group cardiovascular monitoring system" solution that can create many-to-many real-time physiological information monitoring through network technology Based on the platform, patients only need to wear a lightweight monitoring patch, and the back-end system can grasp the changes in their physiological information, so that prevention can replace diagnosis and reduce the chance of sudden cardiovascular death This platform provides 3 functions, including the ability to manage different users into groups and hierarchically, and the number of users can reach tens of thousands it can display users’ basic physiological information in real time on web tools, and can be used under certain preset conditions When triggered, this platform will immediately send out an alarm historical data can also be reviewed on the platform, which is very suitable for doctors to check the patient's disease progression outside the hospital during consultation For the application of the "Group Cardiovascular Monitoring System" solution, taking high-intensity exercise as an example, such as long-distance running and cycling, mountain climbing activities or traveling abroad, a prior cardiovascular health assessment is required activities, and corresponding evaluation reports This report allows users to share it with doctors, so that participants can make assessments before the event or test their training effectiveness, which can significantly reduce the risk of accidents during the event beforehand During the activity, the group cardiovascular monitoring system also provides real-time on-site monitoring of a large number of participants It can be monitored in real time by the AI in the background at the moment of exercise Once an accident occurs, the platform can immediately issue an alarm and even report the accident GPS positioning of the location, and continuously transmits back the user's physiological information during search and rescue, striving for golden rescue time In sports monitoring applications, taking golf as an example, how to improve golfers' puttinghitting performance A player's performance and concentration are usually directly related to personal emotional stability Li Weizhong said that through HRV analysis of Qiyi Medical's electrocardiogram device, it can help determine the player's emotional and stress index performance, and at the same time help golf coaches select and train players The group cardiovascular monitoring system can create a many-to-many real-time physiological information monitoring platform Establish a firm foothold in Taiwan, move towards the US and European markets, and move towards the goal of a data company Faced with the challenges of technology research and development and market promotion, Qiyi Medical Electronics’ automatic identification of electrocardiograms requires a large amount of data for AI calculation development For this reason, Qiyi Medical Electronics must cooperate with hospitals and develop jointly Finish At present, the company has established good cooperative relations with many medical centers and research units, and has overcome these technical bottlenecks one by one In terms of market promotion, Li Weizhong said that the biggest challenge facing Qiyi Medical Electronics is to communicate with the market and let the public understand the differences between competitors' bracelet and watch products and the company's mobile device-electrocardiogram sensor Compared with the common bracelet and watch products on the market that collect electrocardiogram data in a discontinuous manner, it may take a long time to collect discontinuous data before potential cardiovascular problems can be discovered by luck Qiyi Medical Electronics actively promotes electrocardiogram to the public in a continuous manner The competitive functional characteristics of sexual detection data and emphasize that it is a very important means to assist in the detection of many potential diseases, replacing diagnosis with prevention and reducing the occurrence of unnecessary cardiovascular diseases In addition, in terms of business promotion, we also hope to create more opportunities for business matching and new venture capital raising with the assistance of the Corporate Resource Strategy Council Looking to the future, Li Wei and Xu Qiyi Medical 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 as new drug development and vaccine development application to create business opportunities and profits 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【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」