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【2022 Solutions】 Watertight smart industrial safety inspection Linker Vision’s image analysis AI platform sets a new record of inspection time reduced from 100 minutes to 3 seconds

With the rise of smart manufacturing, there is a demand for industrial safety inspections in high-risk industries such as chemical, energy, and electrical industries. Take pipeline inspection in the chemical industry as an example. It relies heavily on manual regular inspection and monitoring, and lacks intelligent monitoring by a professional AI team. This is not only time-consuming and labor-intensive, but may also cause accidental risks to employees in various industrial safety environments. The image analysis AI platform developed by Xinyun Linke not only improves employee personal safety and reduces risk factors, but also significantly reduces the time for human visual inspection of pipeline abnormalities from an average of 100 minutes to 3 seconds.

Paul Shieh, founder and chairman of Linker Vision Co., Ltd. (Linker Vision), said, "The overall technological development and progress in the United States comes from entrepreneurship. Linker Vision's original intention to start a business in Taiwan has been I hope that through my past experience in entrepreneurship in the United States, I can introduce the American entrepreneurial spirit and culture to Taiwan's budding entrepreneurial fertile ground and truly implement it. "American entrepreneurial culture encourages employees to value ownership and emphasizes that employees regard themselves as owners of the company. Be a part of the company, with a work attitude and spirit that would be better than mine. The company's achievements are your own achievements, breaking the original employer-employee relationship. The company will reward outstanding employees with stocks, share the glory together, and establish a partnership with employees. Partnership. On the other hand, Taiwan still has room for efforts in entrepreneurial culture and management, and it retains the traditional thinking of employers and employees. It is expected that Xinyun Linke's establishment of American entrepreneurial culture and values ​​in Taiwan will serve as a starting point to drive more domestic new companies to follow suit, and then Only by upgrading the business constitution of new software AI entrepreneurs can they break out of the cocoon and go global.

Facing the market, most international players focus on developing AI models and algorithms. They are less willing to invest in data-centered (Data-Centric) AI services. They think that processing large amounts of 2D or 3D data is quite time-consuming. It’s also energy-consuming. Seeing the gap in AI technology and encouraged by Microsoft, Xinyunlinke decided to fully invest in Data-Centric's AI technology layout and deep roots many years ago, and specialize in technical energy in data processing, filtering and accuracy. Therefore, Become an important partnership with Microsoft for AI technology supply. In addition, due to the gap in industrial demand, domestic large factories, whose strength is chemical manufacturing, still rely heavily on manpower for inspection of pipelines in the factory, which is time-consuming and labor-intensive. However, in order to cater to the AI ​​industry, the owner reorganized the IT department originally engaged in database management and control into an AI team. However, due to the owner's lack of professional experience in AI software technology, AI models and related domain know-how, the owner introduced AI implementation. Industrial safety monitoring in the chemical industry is even more challenging.

The world's first AI automatic labeling technology surpasses manual labeling and can visually identify objects with an accuracy of over 95%

In terms of AI technology power, Xinyunlinke has launched the world's first dual-core innovative technology of automatic labeling (Auto-labeling) and automatic machine learning to create an efficient and stable image analysis AI platform to provide customers with the best Advanced and complete AI solutions. In terms of automatic annotation, this AI technology can overcome the most difficult challenge in deep learning, which is to provide customers with the highest quality training data. Taking self-driving cars as an example, how to enable one self-driving car to effectively identify another car is the importance of labeling. In the past labeling methods, we first needed to collect digital images of millions of vehicles, roads, signs, and pedestrians, and spent a lot of manpower. Manually labeling one image at a time was time-consuming, labor-intensive, high in labor cost, and inefficient. Through automatic labeling AI technology, combined with automatic machine learning to automatically label digital images, AI can exclude human error labeling and then throw the correct data into the vehicle's brain for vehicle identification. Compared with manual labeling accuracy of only 60%, the accuracy of automatically labeling and identifying objects with AI can be as high as over 95%. It can also reduce manual labeling time by more than 80% and save at least 80% of labor costs.

AI automatically marks AI behavior recognition used in high-altitude operations

▲AI automatically marks AI behavior recognition for high-altitude operations

In the automatic machine learning part, Xinyunlinke established an AI visual model with continuous learning capabilities to adapt to data changes. By optimizing the overall development process, from AI data ingestion and filtering (Data Selection) to AI labeling (AI Labeling) , model training and verification, deployment and monitoring, so that AI computer vision can continue to learn more quickly and easily. Automatic machine learning can currently be applied to different business cases such as object identification and counting, personnel entry and exit security detection, product defect detection, people flow identification, product shortages on shelves, etc.

Looking at domestic companies such as TSMC, Formosa Plastics and Hon Hai towards intelligent AI management and purchasing a large number of cameras to meet the image recognition needs of industrial safety surveillance, coupled with the introduction caused by the unfamiliarity of existing customer organizations with AI applications Thresholds and preliminary preparations for image recognition include complicated workflows such as data screening and annotation. To this end, Xinyunlinke has been committed to accelerating the development of AI computer vision applications in recent years, providing client-to-end services, and can flexibly deploy according to customer needs. Complete automated AI solution services in the cloud, on-premises, or cloud + on-premises. Xie Yuanbao said that the AI ​​automation technology process provides data selection (Data Selection) AI technology through domain-type pictures given by customers, helping customers automatically filter out precise (such as 10,000 transactions) from a large amount of data (such as 1 million transactions). Data, and by using the AI ​​algorithm technology of Auto-Labeling to replace manual labeling, it can effectively save customers a lot of labor costs and achieve efficient data labeling processing. In addition, the AI ​​technology of automated machine learning can help clients customize automatic AI model training or repeated training when the factory environment changes, providing more accurate AI models and allowing customers to operate autonomously. Through the above-mentioned key features and advantages of the automated AI technology provided by Xinyunlinke, we believe that it can definitely meet the needs of customers for an automated end-to-end AI independent learning platform, and at the same time, it can significantly save customers the cost of AI team establishment.

In terms of technological competitiveness, in addition to providing the chemical industry with AI image analysis applications in smart industrial safety, Xie Yuanbao said that Xinyunlinke can also extend the process application of automatic annotation and automated machine learning to different industrial landing services, such as Various fields such as self-driving cars, smart warehousing self-propelled robots and self-driving buses in future smart cities are all in line with the spirit of automated mobility of Mobility as a Service. We look forward to the role played by Xinyunlinke. The process of image annotation in different industries accelerates the efficiency of developing image recognition services in different fields. We believe that by providing client-to-end AI solutions and a complete set of automated AI image analysis pre-operation processes from Data Selection AI technology, Auto-Labeling AI technology, and automated machine learning AI technology, we can greatly satisfy our customers. The demand for AI autonomous learning platform.

Image analysis AI platform sets a new record for smart industrial safety inspections from 100 minutes to 3 seconds

Seeing the high demand for industrial safety supervision in high-risk industries such as the chemical industry in recent years, Xinyunlinke launched the "Vision AI Platform", which uses AI image recognition technology. Its main functions include real-time AI streaming It has four major functions: detection, event notification, defining customer-specific AI models and continuous learning. In the real-time AI stream detection part, the Vision AI system can use the customer's factory camera combined with the AI ​​module to perform real-time stream detection of AI image events. It can help customers manage various operations and factory environments and keep track of them anytime and anywhere. Various work situations; in terms of event notification, the Vision AI platform can provide a web version or APP or LINE instant messaging software to provide customers with video records of the events at that time, so that the team does not miss any events, maintains daily production capacity and reduces accidents; in defining customers In terms of exclusive AI models, a variety of basic AI models are available, including 8 detection scenarios (electronic fences, personal safety equipment, construction safety equipment, construction operations, personnel counting, screen availability, smoke detection, pipeline corrosion and damage) , illegal stacking) for use in different industries, customers can build exclusive AI models without spending time writing programs; in the continuous learning part, the Vision AI system can provide customers with the performance and accuracy of AI models, and have the ability to adapt as the environment changes Continuous learning ability.

Vision AI has a simple user interface and intuitive operation. For cross-field industries, this platform has automated and flexible AI capabilities. Customers can build self-defined AI models without spending time writing programs, and Vision AI gives AI models the ability to continuously learn and improve, allowing customers to save the labor cost of building an AI team. In addition, the platform can significantly reduce the manpower allocation for routine inspections required for operational safety management, improve employee safety in the working environment, and reduce on-site accidents/risk factors at various work sites. In the platform operation mode, customers can reduce the risk of manual monitoring operations through remote operations, ensuring normal work operations and uninterrupted production operations. They can also review high-risk operating situations and collect data to assist in the planning and correction of operating processes. In addition, in order to ensure that customers comply with government regulations, Vision AI can help customers control the equipment and safety regulations required in different workplaces at any time through the platform's event notification and management detection.

Image analysis AI platform is used in cross-field AI image recognition technology

▲The image analysis AI platform is used in cross-field AI image recognition technology

Generally, for industrial safety inspections in the chemical industry, most rely on the naked eye of personnel to regularly inspect pipeline abnormalities. It takes an average of 100 minutes to scan an area each time, which is time-consuming and laborious, and the pipeline location is difficult to visually observe, which may cause Employees are exposed to accidental risks in various work safety environments. In order to reduce the pain points of industrial safety inspections in the chemical industry, Xinyunlinke assists well-known domestic chemical industry players by using an automated image analysis AI platform, combined with customized virtual electronic fences, and using in-plant cameras to configure AI pipeline leakage modules. , the AI ​​automatic inspection method can effectively reduce the abnormal detection time to less than 3 seconds. In addition, cameras deployed in the factory can automatically record inspection schedules to achieve full-time monitoring, allowing customers to instantly discover and fully control pipelines, minimizing risks. In addition, the automated image analysis AI platform can help customers apply fire warnings in factories. It is conservatively estimated that the return on investment can be less than 9 months to pay back the investment. The longer the platform is used, the higher the cost-effectiveness.

Build an automatic learning image analysis AI platform for Mobility as a Service in various fields

Xie Yuanbao observed that the biggest challenge facing the entrepreneurial culture of software companies in Taiwan is that young new entrepreneurs or employees in Taiwan do not understand the entrepreneurial model and lack the awareness to regard themselves as part of the company owners. This has caused It is a pity that your future is unclear or you have a past-experience mentality that prevents you from staying competent in a new start-up company for a long time. I believe that the essence of true entrepreneurship lies in every employee rolling up their sleeves and working hard, so that they can truly enjoy the fruits of entrepreneurial profits. Otherwise, for young entrepreneurs or employees who often change tracks, it will be like a rolling stone that gathers no moss. , I am unable to take a deep root on the road of entrepreneurship, and I lose my ability to solidly accumulate financial independence.

Regarding the business promotion challenges of Xinyun Linke, Xie Yuanbao said with emotion that because the Taiwan market does not have a deep understanding of AI software applications, it relies more on open source AI visual analysis or machine learning and other resources on the market, but in fact These AI technology resources are limited in their ability to support customers' AI model needs, resulting in uneven quality of AI visual analysis software in the market. Therefore, the impact is more indirect on Xinyunlinke's ability to truly provide customers with professional and data-centric AI image analysis services, and it also reduces the company's original business value in customer reference. In terms of technical research and development challenges, the visual analysis AI platform cannot rely solely on AI model experts. It must gather talents in various fields such as cloud, machine learning, data science, front-end and back-end and other professional team combinations to make the platform operate successfully. Xie Yuanbao said that he believes that only through the automatic learning of the visual analysis AI platform, automatic fast and accurate data processing capabilities, and providing customers with complete AI solution services in the cloud, cloud + ground (Hybrid) to pure ground, can we truly Convince customers and stand out from the competition.

Looking to the future, Xie Yuanbao hopes that Xinyunlin Technology can build an image analysis AI platform for Mobility as a Service to automatically learn in various fields (such as self-driving cars, smart warehousing robots, and unmanned buses in smart cities). At the same time, I am also grateful to the support of the Industrial Bureau of the Ministry of Economic Affairs for the smooth landing of Xinyunlin Technology in Taiwan and the opportunity to recruit talents from all walks of life to work together. In the short-term layout, the company will actively cooperate with domestic players such as Hon Hai and TSMC to implement image analysis AI technology in fields such as self-driving cars, smart industrial safety, and smart warehousing robots. In the medium to long term, Xinyunlinke will target the United States, Europe, Japan and other countries as its global market layout, establish investment and cooperation partnerships with major international companies such as Microsoft, and replicate its successful experience and promote it internationally.

Xinyunlinke official website

Xie Yuanbao, founder and chairman of Xinyunlinke
▲ Xie Yuanbao, founder and chairman of Xinyunlinke

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

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【解決方案】7毫秒內分離人聲 洞見未來科技協助聽損者「聽說更簡單」
Voice Separation in 7 Milliseconds: RelaJet's Future Technology Makes 'Hearing and Speaking Easier' for the Hearing Impaired

One rainy Thursday afternoon near Taipei Arena, the Taipei Experience Center of RelaJet was fully booked with appointments from people with hearing loss eager to try hearing aids made with a voice separation engine For the hearing impaired, having affordable, lightweight, and effective noise-reducing hearing aids is truly a blessing 'We hope to help users in need to hear the world's wonders again' This empathetic expectation by RelaJet's founder and CEO Po-Ju Chen, who is also hearing impaired, illustrates his understanding of the needs of the hearing impaired He hopes that RelaJet's unique voice amplification hearing aid technology will benefit many more people Affordable hearing aids benefit many with hearing loss Founded in 2018 by Po-Ju Chen and his brother Yu-Ren Chen, RelaJet developed a multi-voice separation engine paired with Qualcomm's Bluetooth audio platform, drastically reducing the price of imported hearing aids, typically costing 80,000-100,000 NT dollars, to just under 10,000 NT dollars They aim to develop affordable goods with excellent noise-cancelling capabilities that wirelessly connect to smartphones In its first two years, the company primarily developed the multi-voice separation engine, which significantly improved the noise reduction quality Once equipped with Qualcomm Bluetooth earphone chips, the audio processing time is drastically short, at about 7 milliseconds to enhance main voice projection and reduce ambient noise, less than half the time required by traditional medical standard of 16 milliseconds for hearing aids, nearly 'zero-delay' 洞見未來科技推出平價助輔聽器,大大嘉惠聽損者 Yu-Ren Chen explains that the primary use of Qualcomm chips for edge computing, along with a streamlined algorithm, achieves extremely low latency and better noise reduction The hearing aids can cover 18 channels, whereas traditional hearing aids cover 4-48 channels In the future, RelaJet will progressively increase the number of channels According to statistics, there are 470 million people globally with hearing disabilities, with a 30 average device use rate in developed countries, with the highest in Western countries Taiwan has nearly 15 million people with disabling hearing loss, of which the middle-aged and elderly make up 30, yet the device use rate is only about 10, which is quite low Yu-Ren Chen further analyzes that the low device usage rate is due to two reasons firstly, the high average selling price of international big brands ranges from 80,000 to 200,000 NT dollars with a three-year usability period, which deters many due to the high cost and maintenance Secondly, in noisy environments, the noise is also amplified which does not necessarily ensure clarity for the users, and the sound parameters can't be adjusted in real-time, making it inconvenient to frequently visit stores for tuning Thirdly, most models cannot connect to smartphones, making it inconvenient for the hearing impaired to take phone calls Utilizing Qualcomm Bluetooth chips for rapid product development In light of this, Po-Ju Chen, formerly a semiconductor engineer at MediaTek, leads the technical development, while Yu-Ren Chen, with a legal background, manages the operations Their seamless collaboration, along with their team employing AI algorithms and chip integration, learns from thousands of hours of audio files in databases through neural networks and deep learning technologies to develop low-latency, high-noise-reduction voice amplification technologies for hearing aids In 2019, this sound processing technology was integrated into Qualcomm Bluetooth chips, winning first place in the Qualcomm Taiwan Startup Competition and becoming a partner in Qualcomm's Global Expansion Program, significantly boosting product development pace In 2021, they launched their own Otoadd series of hearingenhancement products in Taiwan, which received both market favor and positive reviews from many with hearing loss Based on different consumer needs, various product 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anticipated to be exported to international markets in the latter half of this year Additionally, a hearing aid product combining Bluetooth functionality, set to launch in June this year, is sized like typical Bluetooth earphones, targeting visually conscious consumers with hearing loss Its small size and attractive wireless earphone design allow for phone calls, and if approved by the Ministry of Health and Welfare, eligible users can apply for government subsidies RelaJet to expand into overseas markets, using the USA as a beachhead An interesting question arises due to the pandemic everyone must wear masks which impedes lip-reading How does this affect those with hearing loss Yu-Ren Chen indicates that this situation highlights RelaJet's advantages As each person with hearing loss has different levels of hearing ability, hearing aids can only augment to an appropriate volume, assisting users to hear about 60-70 content, with the remainder relying on lip reading and gestures During the pandemic, as everyone wears masks, masks also muffle sounds, but RelaJet's voice separation engine can correct and strengthen the separation, making it easier for those with hearing loss to recognize voices Besides the Taiwan market, RelaJet's next stage will be expanding into overseas markets, expecting to obtain ISO 13485 medical device quality management system certification and US medical device approval in 2022 They plan to enter the US market, either under their own brand or through OEM arrangements Apart from the Taiwan market, RelaJet will also enter the US market in the next phase for hearing aids「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【解決方案】滴水不漏的智慧工安巡檢 鑫蘊林科Linker Vision的影像分析AI平台 創造巡檢時間從100分鐘降至3秒新紀錄
Watertight smart industrial safety inspection Linker Vision’s image analysis AI platform sets a new record of inspection time reduced from 100 minutes to 3 seconds

With the rise of smart manufacturing, there is a demand for industrial safety inspections in high-risk industries such as chemical, energy, and electrical industries Take pipeline inspection in the chemical industry as an example It relies heavily on manual regular inspection and monitoring, and lacks intelligent monitoring by a professional AI team This is not only time-consuming and labor-intensive, but may also cause accidental risks to employees in various industrial safety environments The image analysis AI platform developed by Xinyun Linke not only improves employee personal safety and reduces risk factors, but also significantly reduces the time for human visual inspection of pipeline abnormalities from an average of 100 minutes to 3 seconds Paul Shieh, founder and chairman of Linker Vision Co, Ltd Linker Vision, said, "The overall technological development and progress in the United States comes from entrepreneurship Linker Vision's original intention to start a business in Taiwan has been I hope that through my past experience in entrepreneurship in the United States, I can introduce the American entrepreneurial spirit and culture to Taiwan's budding entrepreneurial fertile ground and truly implement it "American entrepreneurial culture encourages employees to value ownership and emphasizes that employees regard themselves as owners of the company Be a part of the company, with a work attitude and spirit that would be better than mine The company's achievements are your own achievements, breaking the original employer-employee relationship The company will reward outstanding employees with stocks, share the glory together, and establish a partnership with employees Partnership On the other hand, Taiwan still has room for efforts in entrepreneurial culture and management, and it retains the traditional thinking of employers and employees It is expected that Xinyun Linke's establishment of American entrepreneurial culture and values in Taiwan will serve as a starting point to drive more domestic new companies to follow suit, and then Only by upgrading the business constitution of new software AI entrepreneurs can they break out of the cocoon and go global Facing the market, most international players focus on developing AI models and algorithms They are less willing to invest in data-centered Data-Centric AI services They think that processing large amounts of 2D or 3D data is quite time-consuming It’s also energy-consuming Seeing the gap in AI technology and encouraged by Microsoft, Xinyunlinke decided to fully invest in Data-Centric's AI technology layout and deep roots many years ago, and specialize in technical energy in data processing, filtering and accuracy Therefore, Become an important partnership with Microsoft for AI technology supply In addition, due to the gap in industrial demand, domestic large factories, whose strength is chemical manufacturing, still rely heavily on manpower for inspection of pipelines in the factory, which is time-consuming and labor-intensive However, in order to cater to the AI industry, the owner reorganized the IT department originally engaged in database management and control into an AI team However, due to the owner's lack of professional experience in AI software technology, AI models and related domain know-how, the owner introduced AI implementation Industrial safety monitoring in the chemical industry is even more challenging The world's first AI automatic labeling technology surpasses manual labeling and can visually identify objects with an accuracy of over 95 In terms of AI technology power, Xinyunlinke has launched the world's first dual-core innovative technology of automatic labeling Auto-labeling and automatic machine learning to create an efficient and stable image analysis AI platform to provide customers with the best Advanced and complete AI solutions In terms of automatic annotation, this AI technology can overcome the most difficult challenge in deep learning, which is to provide customers with the highest quality training data Taking self-driving cars as an example, how to enable one self-driving car to effectively identify another car is the importance of labeling In the past labeling methods, we first needed to collect digital images of millions of vehicles, roads, signs, and pedestrians, and spent a lot of manpower Manually labeling one image at a time was time-consuming, labor-intensive, high in labor cost, and inefficient Through automatic labeling AI technology, combined with automatic machine learning to automatically label digital images, AI can exclude human error labeling and then throw the correct data into the vehicle's brain for vehicle identification Compared with manual labeling accuracy of only 60, the accuracy of automatically labeling and identifying objects with AI can be as high as over 95 It can also reduce manual labeling time by more than 80 and save at least 80 of labor costs AI automatically marks AI behavior recognition for high-altitude operations In the automatic machine learning part, Xinyunlinke established an AI visual model with continuous learning capabilities to adapt to data changes By optimizing the overall development process, from AI data ingestion and filtering Data Selection to AI labeling AI Labeling , model training and verification, deployment and monitoring, so that AI computer vision can continue to learn more quickly and easily Automatic machine learning can currently be applied to different business cases such as object identification and counting, personnel entry and exit security detection, product defect detection, people flow identification, product shortages on shelves, etc Looking at domestic companies such as TSMC, Formosa Plastics and Hon Hai towards intelligent AI management and purchasing a large number of cameras to meet the image recognition needs of industrial safety surveillance, coupled with the introduction caused by the unfamiliarity of existing customer organizations with AI applications Thresholds and preliminary preparations for image recognition include complicated workflows such as data screening and annotation To this end, Xinyunlinke has been committed to accelerating the development of AI computer vision applications in recent years, providing client-to-end services, and can flexibly deploy according to customer needs Complete automated AI solution services in the cloud, on-premises, or cloud on-premises Xie Yuanbao said that the AI automation technology process provides data selection Data Selection AI technology through domain-type pictures given by customers, helping customers automatically filter out precise such as 10,000 transactions from a large amount of data such as 1 million transactions Data, and by using the AI algorithm technology of Auto-Labeling to replace manual labeling, it can effectively save customers a lot of labor costs and achieve efficient data labeling processing In addition, the AI technology of automated machine learning can help clients customize automatic AI model training or repeated training when the factory environment changes, providing more accurate AI models and allowing customers to operate autonomously Through the above-mentioned key features and advantages of the automated AI technology provided by Xinyunlinke, we believe that it can definitely meet the needs of customers for an automated end-to-end AI independent learning platform, and at the same time, it can significantly save customers the cost of AI team establishment In terms of technological competitiveness, in addition to providing the chemical industry with AI image analysis applications in smart industrial safety, Xie Yuanbao said that Xinyunlinke can also extend the process application of automatic annotation and automated machine learning to different industrial landing services, such as Various fields such as self-driving cars, smart warehousing self-propelled robots and self-driving buses in future smart cities are all in line with the spirit of automated mobility of Mobility as a Service We look forward to the role played by Xinyunlinke The process of image annotation in different industries accelerates the efficiency of developing image recognition services in different fields We believe that by providing client-to-end AI solutions and a complete set of automated AI image analysis pre-operation processes from Data Selection AI technology, Auto-Labeling AI technology, and automated machine learning AI technology, we can greatly satisfy our customers The demand for AI autonomous learning platform Image analysis AI platform sets a new record for smart industrial safety inspections from 100 minutes to 3 seconds Seeing the high demand for industrial safety supervision in high-risk industries such as the chemical industry in recent years, Xinyunlinke launched the "Vision AI Platform", which uses AI image recognition technology Its main functions include real-time AI streaming It has four major functions detection, event notification, defining customer-specific AI models and continuous learning In the real-time AI stream detection part, the Vision AI system can use the customer's factory camera combined with the AI module to perform real-time stream detection of AI image events It can help customers manage various operations and factory environments and keep track of them anytime and anywhere Various work situations in terms of event notification, the Vision AI platform can provide a web version or APP or LINE instant messaging software to provide customers with video records of the events at that time, so that the team does not miss any events, maintains daily production capacity and reduces accidents in defining customers In terms of exclusive AI models, a variety of basic AI models are available, including 8 detection scenarios electronic fences, personal safety equipment, construction safety equipment, construction operations, personnel counting, screen availability, smoke detection, pipeline corrosion and damage , illegal stacking for use in different industries, customers can build exclusive AI models without spending time writing programs in the continuous learning part, the Vision AI system can provide customers with the performance and accuracy of AI models, and have the ability to adapt as the environment changes Continuous learning ability Vision AI has a simple user interface and intuitive operation For cross-field industries, this platform has automated and flexible AI capabilities Customers can build self-defined AI models without spending time writing programs, and Vision AI gives AI models the ability to continuously learn and improve, allowing customers to save the labor cost of building an AI team In addition, the platform can significantly reduce the manpower allocation for routine inspections required for operational safety management, improve employee safety in the working environment, and reduce on-site accidentsrisk factors at various work sites In the platform operation mode, customers can reduce the risk of manual monitoring operations through remote operations, ensuring normal work operations and uninterrupted production operations They can also review high-risk operating situations and collect data to assist in the planning and correction of operating processes In addition, in order to ensure that customers comply with government regulations, Vision AI can help customers control the equipment and safety regulations required in different workplaces at any time through the platform's event notification and management detection The image analysis AI platform is used in cross-field AI image recognition technology Generally, for industrial safety inspections in the chemical industry, most rely on the naked eye of personnel to regularly inspect pipeline abnormalities It takes an average of 100 minutes to scan an area each time, which is time-consuming and laborious, and the 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back the investment The longer the platform is used, the higher the cost-effectiveness Build an automatic learning image analysis AI platform for Mobility as a Service in various fields Xie Yuanbao observed that the biggest challenge facing the entrepreneurial culture of software companies in Taiwan is that young new entrepreneurs or employees in Taiwan do not understand the entrepreneurial model and lack the awareness to regard themselves as part of the company owners This has caused It is a pity that your future is unclear or you have a past-experience mentality that prevents you from staying competent in a new start-up company for a long time I believe that the essence of true entrepreneurship lies in every employee rolling up their sleeves and working hard, so that they can truly enjoy the fruits of entrepreneurial profits Otherwise, for young entrepreneurs or employees who often change tracks, it will be like a rolling stone that gathers no moss , I am unable to take a deep root on the road of entrepreneurship, and I lose my ability to solidly accumulate financial independence Regarding the business promotion challenges of Xinyun Linke, Xie Yuanbao said with emotion that because the Taiwan market does not have a deep understanding of AI software applications, it relies more on open source AI visual analysis or machine learning and other resources on the market, but in fact These AI technology resources are limited in their ability to support customers' AI model needs, resulting in uneven quality of AI visual analysis software in the market Therefore, the impact is more indirect on Xinyunlinke's ability to truly provide customers with professional and data-centric AI image analysis services, and it also reduces the company's original business value in customer reference In terms of technical research and development challenges, the visual analysis AI platform cannot rely solely on AI model experts It must gather talents in various fields such as cloud, machine learning, data science, front-end and back-end and other professional team combinations to make the platform operate successfully Xie Yuanbao said that he believes that only through the automatic learning of the visual analysis AI platform, automatic fast and accurate data processing capabilities, and providing customers with complete AI solution services in the cloud, cloud ground Hybrid to pure ground, can we truly Convince customers and stand out from the competition Looking to the future, Xie Yuanbao hopes that Xinyunlin Technology can build an image analysis AI platform for Mobility as a Service to automatically learn in various fields such as self-driving cars, smart warehousing robots, and unmanned buses in smart cities At the same time, I am also grateful to the support of the Industrial Bureau of the Ministry of Economic Affairs for the smooth landing of Xinyunlin Technology in Taiwan and the opportunity to recruit talents from all walks of life to work together In the short-term layout, the company will actively cooperate with domestic players such as Hon Hai and TSMC to implement image analysis AI technology in fields such as self-driving cars, smart industrial safety, and smart warehousing robots In the medium to long term, Xinyunlinke will target the United States, Europe, Japan and other countries as its global market layout, establish investment and cooperation partnerships with major international companies such as Microsoft, and replicate its successful experience and promote it internationally Xinyunlinke official website Xie Yuanbao, founder and chairman of Xinyunlinke 「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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AIIntelligent Defect Detection-Smart Monitoring Solution to Reduce Process Energy Consumption When there are over2ten thousand chip resistors on a ceramic substrate, how should one quickly detect defects The answer isUsingAIto detect。 In the era of rapid technological development, Leike proudly announces significant advances in its laser processing technology, thanks to the innovative applications of artificial intelligenceAILeike is committed to integrating advancedAItechnology into laser processing machines, and in2019year, in collaboration with partners, developed the world's first laser machining system that integratesAItechnology, and on this basis further developed in2023year the first ceramic substrate inspection machine that integratesAOIAILASERtechnology Smart Ceramic Substrate Inspection Machine Through the introduction ofAIand machine learning, along with the accumulation of big data samples, the system becomes smarter, which has led to improved product yield within one year5dramatically reducing the inspection time from originally2minutesper piece to just20secondsper piece, drastically lowering inspection costs, enabling efficient initial detection and post-laser marking to reduce waste in subsequent processes, diminishing overall carbon emissions of the site, allowing the automatic generation of detailed inspection reports for data analysis and optimization, which helps increase equipment capacity, reduce human error, enhancing the value of Leike's equipment, and strengthening the international competitiveness of the country's electromechanical industry Leike CorporationLaser TekFounded in1988year, and officially listed as a publicly traded company in2002year Since its establishment, it has become a leading global service provider and manufacturer of electronic packaging materials,SMDElectronic Packaging Materials,SMTinspection equipment, and laser systems Leike's general manager, with years of laser integration experience, observed that passive component customers can produce over20With many years of laser integration experience, he observed that the production capacity of passive component customers can exceed10billionSMDcomponents every month, but withSMDcomponents per month However, as component sizes continue to miniaturize, defect detection during production becomes increasingly challenging With thousands to millions of components on a single ceramic substrate, and as component sizes decrease and their laser processing positions become smaller, the difficulty of detection increases, making production inspection a critical process R-SMD Production Inspection Process AOIproblems of yield overkill relying onAIfor oversight, Yet,AOIthe inspection machine is a widespread and mature type, but the high accuracy on the marketAOIuses a technique that captures small images in a single shot and stitches them into a larger image Although accurate, this method requires more time for small-sizedSMDcomponents, which are more likely to be influenced by environmental factors like lighting and vibration that can cause misjudgments as a result,AOIyield rate can only be estimated by sampling, and components with poor sampling yield are not removed individually but discarded together with good ones manual re-inspection not only increases costs, but the lack of unified inspection standards ultimately results in about2-5products that are not detected as defective enter the subsequent manufacturing process monthly at least2,000thousands of such defective componentsSMDthat were not initially detected causing ongoing printing and machining inspections in subsequent processes Regardless of the waste of ink materials and energy, which increases the cost burden, this also accelerates equipment wear and shortens operational life Each stage of waste increases the site's carbon emissions, unfavorably impacting the company's carbon footprint Post-Adjustment Sample Photo Example 0402 TraditionalAOI High false positive rates in Automatic Optical Inspection AOI are a major production issue for manufacturers, particularly in the passive components industry where 'it's better to mistakenly reject a hundred than miss one'—a high standard, often leading to AOI setting extremely high parameters which makes devices overly sensitive Excessive stringency in data parameter settings can lead to high false positive rates For instance, if the dirt contamination on passive components resembles the color of the printing layers,AOI the misjudgment rate could reach 7 percent Contamination Dirt and Print Layer Color SimilarityAOIProne to Misjudgment Raytek stands apart from otherAOIsuppliers by discarding the stitching of small images or line scanning, effectively preventing data loss and discrepancies caused by hardware or environmental conditions during image processing It employs a large-array photodetector coupled with custom high-resolution lenses, using specialized imaging for composite processing Throughout this process, each pixel of the photodetector contains light information captured from various positions By combining this data, the image resolution and detail are enhanced, reaching a resolution of millions, and with multiple automatic light adjustments, a single shot can manage7070mmachieving an image resolution up to5umobtaining clear images, then throughSmart-AItechniques for analysis and selection Three Innovative Methods to Achieve Rapid InspectionSmart -AI Raytek's General Manager shares, rapidly implementingAItechnology and reducing inspection computation time, further developingSmart-AIthree major approaches Method one, initially useAOIto quickly separate good products from those with controversial defects, focusing the detection on the minority of defective identifications Method two, an automated labeling platform simplifies the training issue by using cameras to collect data from machines, automatic labeling replaces manual labeling, progressively training to improve accuracy The simpler the problem, the less data needed for training Method three,AOIandAIDual-track Advancement In the smart manufacturing process, relying solely onAOIorAIis not enough to accomplish the task alone, it must be preceded byAOIfirst marking the characteristics, distinguishing between good and defective parts, then usingAIa method for labeling and training Subsequently, by utilizing a repeating cascade effect, the detection benefits are greater as more training data accumulates,AOIreducing the ratio of errors,AIand gradually increasing the accuracy ratio Post Adjustment Object Detection and Training Through three major methods gradually building system reliability, and categorizing data for defect sorting, ultimatelyAIreturning the judgement results to the main system, utilizing laser machining to control truly defective products at the front end of the process, reducing the inflow of defective products into other stations, thus minimizing losses due to repeated tests or reprocessing Leading in smart laser equipment, chooseLASERTEKthe right one Continuously developed by the Taiwanese brand Raytek, combiningAIsmart detection and laser processing equipment to progressively build a smart monitoring solution stack from raw materials, products, testing, laser equipment, etc, aiming at reducing the energy consumption of the production process, implementing semiconductor advancements, substrates and component processing among other fields, producing equipment products capable of meeting the end-user demands under low carbon conditions, rapidly and with quality products and services expanding both domestic and international markets, enhancing the global competitiveness of localMade in TaiwanMITequipment 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-12-12」