Special 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
01
2022.9
【2022 Solutions】 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」

2022-09-01
【2021 Solutions】 Motor Protectors: How Haobo Technology Employs AI to Understand the 'Hearts' of Machines

Motors are a critical power source for various devices in modern times, and are key components of many automated equipment, acting like the heart of machines Any malfunctions not only shorten the lifespan of the motors themselves but also affect the entire system's operation, potentially causing delays in production due to downtime Through the use of Smart Vibration Diagnostic and Monitoring Solution SVDM Solution, Haobo Technology utilizes AI to comprehend motors, becoming an indispensable tech partner in intelligent manufacturing The essential industrial motors see an almost 4 annual compound growth rate According to statistics, the market size for industrial motors was 329 billion in 2017, with an expected compound annual growth rate of 363 from 2019 to 2025 Motors have a wide variety of uses, nearly essential in all equipment operations, and represent a technology that is well-developed, with numerous suppliers and a long product lifecycle Haobo Technology, established in 2015, started by solving motor noise issues In recent years, due to the rapidly evolving AI technology, Haobo Technology has continuously innovated and researched, integrating vibration frequency with sound-based audio processing technologies and AI algorithms for noise reduction, along with their self-developed wideband low-noise vibration sensors They introduced a new generation of industry-leading 'Smart Vibration Diagnostic and Monitoring Solution' SVDM Solution, overcoming previous challenges in detecting main vibration frequencies and predicting vibration models in complex environments, making it an essential solution for accelerating industrial intelligence Haobo Technology's 'Smart Vibration Diagnostic and Monitoring Solution' has been successfully applied in PCB drilling machines, semiconductor equipment, machine tools, and medical equipment Haobo Technology's CEO Lu Hongyi states that the Smart Vibration Diagnostic and Monitoring Solution is distinguished not only by its noise reduction capability but also by the AI model's ability to instantly recognize abnormal frequencies in motor vibrations Since general motor sensors are too large to be mounted on the motors, Haobo Technology has customized thin sensors to be installed on the spindle motors, allowing AI models to be computed in real-time on edge devices, significantly reducing the cost of computational resources, with an overall potential reduction in costs by one-fourth Simultaneously, advancements in vibration detection for motor operations have exceeded past technological limits, thus allowing for the immediate detection of the minutest changes and providing early malfunction warnings, helping to extend the lifespan of the motors Haobo Technology has established a vibration data AI analysis platform that constantly monitors the health of motors Haobo Technology's self-developed AI engine is capable of training database modules from collected operational vibration data of motors and establishing a proprietary database for that equipment, which provides real-time comparisons during operation, monitoring if the production equipment is functioning normally Upon detecting any abnormalities, the system instantly issues a warning alert, enabling on-site managers to address the issue immediately to prevent large quantities of finished or semi-finished products from defects Haobo Technology's vibration data AI analysis platform can detect the most subtle vibrations in motors, thus precisely predicting their health status Lu Hongyi mentions that the company independently develops its sensors, hardware, firmware, and AI data analysis platforms, which allows for the detection of the faintest vibrations in motors, thereby accurately predicting their health status This optimization of product quality and preemptive monitoring of production equipment health aims to enhance productivity Haobo's 'Smart Vibration Diagnostic and Monitoring Solution' SVDM Solution has successfully been applied in PCB drilling machines, semiconductor equipment, machine tools, and medical devices, with future plans to actively promote across various industries and enter the international market, hoping to become a pioneer in smart vibration diagnostics Haobo Technology CEO Lu Hongyi「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

2021-10-06
這是一張圖片。 This is a picture.
【2022 Solutions】 AI + Smart Glasses: Hsiung-Hsin Technology Targets Smart Care Market, Ensuring Safety and Security for the Elderly

In the small care room, Mr Wang, who is over eighty, is coughing intensely The nurse gently uses a suction device to help him, hoping to make him more comfortable Meanwhile, a sharp-eyed family member notices that the nurse is wearing smart glasses At the other end, the doctor organizes medical records while simultaneously monitoring Mr Wang's condition on a screen With the advent of precision care, it will soon be a blessing for the care market for doctors to remotely monitor crucial physiological information of the cared-for in real time In fact, Hsiung-Hsin Technology, established in 2020, uses smart glasses combined with AI algorithms to launch smart care services as an AI startup Through AI multiple sensors to achieve effective smart care In 2021, Hsiung-Hsin Technology participated in the Ministry of Economic Affairs Industrial Bureau AI Emerging Selection event, cooperating with smart glasses leader Jozhen Technology Jozhen provided millimeter-wave radar and smart glasses, combined with Hsiung-Hsin Technology's AI algorithms, to launch 'AI Care Recognition Service System' and a life-saving 'Fall Prevention System' The 'AI Care Recognition Service System' uses radar millimeter waves and Time-of-Flight ToF among various sensor technologies combined with point cloud and mmWave deep learning analysis in AI algorithms While protecting personal privacy, it can detect patients' physiological data upon hospital admission as well as detect falls and bed exits during bed care The 'life-saving fall prevention system', on the other hand, utilizes artificial intelligence and 3D technology, combined with radar sensing devices, while protecting personal data through 'de-identification' technology, detecting falls in real-time in the environment Building the AI Care Recognition Service System, Hsiung-Hsin Technology is aiming at the smart care market Lee Jia-Hsin, founder and chairman of Hsiung-Hsin Technology, who has worked for IBM Taiwan for 14 years, states that after placing millimeter-wave radar in the medical test field, combined with AI algorithms, they can obtain physiological signals such as the patient's breath and heartbeat Moreover, when paired with Jozhen's smart glasses, during a doctor's consultation, the physician can immediately see the patient's heartbeat and breathing data through the glasses, enhancing efficiency Additionally, Jozhen has also developed a management platform where physicians and nursing staff can view the patient's physiological data at a glance After integrating the 'AI Care Recognition Service System' and 'Life-Saving Fall Prevention System', they were launched and commercialized in June 2021, and officially introduced into Kaohsiung Municipal Triumph Hospital by the end of November last year It not only helps medical staff understand the residents' physiological conditions, monitoring elders' physiological data continuously, but also reduces the burden on medical institutions while preventing accidents and enabling quick action in emergencies to provide optimal medical care Aside from medical institutions, another major target customer group for Hsiung-Hsin Technology's products are long-term care institutions, with ongoing product implementation plans in Tainan and Eastern Taiwan On-demand lightweight design, easy to use and reasonably priced Lee Jia-Hsin mentions that the company's productsservices are developed in-house, designed to be lightweight Depending on the needs of the institution where they are implemented, they may choose between CPU computing or edge computing for flexible configuration, which is very convenient and also comparatively cost-effective In the future, through Jozhen smart glasses, diagnoses can be made more immediately and quickly The method allows nursing or care staff to wear smart glasses when visiting patients or residents The images seen by the nursing staff's eyes are transmitted in real-time to the backend, allowing doctors to make immediate diagnoses based on real-time images and take appropriate care measures, effectively assessing the patient's condition on time Hsiung-Hsin Technology's smart care services have been listed on the Startup Common Supply Contract Platform Last year, Hsiung-Hsin Technology's productsservices were also listed on the Ministry of Economic Affairs, Small and Medium Enterprise Administration's Startup Common Supply Contract Procurement Platform, available for government agencies, public medical institutions, and long-term care facilities to purchase for lease In the future, they hope to expand to private medical institutions and care centers, enabling more care facilities to utilize technology for transformation and reducing the talent shortage in the care market Furthermore, with more than 300,000 elderly people living alone in Taiwan, Lee Jia-Hsin believes that as the aging society approaches, the health and safety issues of solitary elderly individuals are increasingly receiving attention If technological care medical solutions can be incorporated into the subsidy scope for assistive devices, it can also help reduce the burden on local government institutions for solitary elderly care, effectively lowering societal costs Extended application Smart campuses enhance management safety and efficiency Lee Jia-Hsin points out that the company's core values are making life safer and improving living quality The company has developed its own software and hardware solutions for big data, artificial intelligence, and the Internet of Things Using a hybrid cloud development approach, it addresses various types of medical care pain points, enhances medical management efficiency, and improves residents' safety, thus significantly enhancing overall services by medical institutions Hsiung-Hsin Technology's partners include SI businesses, medical care institutions, large chain restaurants, and major venues In the future, there are plans to develop into an AI SaaS company, extending services to Japan, Southeast Asia, and other overseas markets Additionally, Lee Jia-Hsin, who teaches at Tunghai University in Taichung, is also actively promoting the smart campus initiative Currently, Hsiung-Hsin Technology has established a 'smart campus' at Tunghai University, utilizing up to 700 cameras throughout the campus to build a miniature AI SaaS platform for monitoring This not only allows for mask, human traffic, restricted area, and license plate recognition within the campus but also enables automatic records of the campus's flora and fauna, greatly aiding in the efficiency of campus safety management As the population gradually ages, home care becomes a universal challenge With a low doctor-to-patient ratio, both inside and outside hospitals, including extended to care institutions, medical professionals face a scarcity of manpower Using AI technology to assist the elderly care market presents itself as the best solution Besides smart elderly care and smart campuses, Hsiung-Hsin Technology also applies its image recognition technology in places like factory safety and parking lot license plate recognition, and future applications will continue to expand boundlessly Hsiung-Hsin Technology's founder and chairman, Lee Jia-Hsin「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

2022-03-14
這是一張圖片。 This is a picture.
【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 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 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 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

2022-09-15
這是一張圖片。 This is a picture.

Records of Solutions

【解決方案】新興AI團隊Atelli,以AI廣告投手將廣告優化提升至廣告演化
【2020 Solutions】 Emerging AI Team Atelli, Elevating Advertising Optimization to Evolution with AI Ad Pitcher

Emerging AI technology team Atelli has joined the Taiwan marketing tech circle, developing multifaceted AI products with core algorithm technologies to help businesses enhance their commercial outcomes Atelli, originally branched out from the digital marketing consultancy adGeek Co-founder Chen Jianming pointed out 'Technology is increasingly leading digital marketing, and the use of data will only increase Facing a massive amount of data and competitive external environment, advertisers need to utilize technology to reach potential customers, achieve goals, while also effectively managing manpower and time' Hence, the team started developing AI advertising products a year ago, and now Atelli has become an independent AI technology company, focusing on the development of AI products Atelli launched the first product of its Business Booster series in 2019, the AI Ad Pitcher, helping advertisers execute Google and Facebook ads with AI Within six months, over 500 Facebook ad accounts were accumulated, with a monthly advertising spend of over 50 million, helping customers find potential market customers previously hard to reach manually The team shared many customer experiences with the product besides improving performance, there's no need for complex system setup processes It can go live in just 15 minutes, and automatically optimize ad performance 24 hours a day, indeed reducing 90 of the marketing staff's workload, allowing them to focus on more significant business strategies The thoughtful product design has successfully established customer goodwill and trust Atelli co-founder Huang Yingzhe stated, 'The shift in the marketing environment is truly an evolutionary process We deeply understand the challenges enterprises face, including adapting to technology, the burden of labor costs, and expectations towards goals Using technology to help businesses overcome challenges is the purpose of establishing Atelli, combining AI with data to transform past manual advertising optimization into advertising evolution Positive customer feedback and goal achievement prove that we are on the right track' The biggest competitive advantage of the Atelli AI Ad Pitcher comes from three features achieving the best AI evolutionary algorithms, generating a high-value audience, moving away from rigid rule-based adjustments, considering multiple real-life scenarios, integrating more human elements and comprehensive intelligent adjustments An advertising campaign involves many different setting elements, such as audience interests, agegender, keyword themes, etc, each considered as an 'individual' With AI algorithms, past 'advertising optimizations' are elevated to 'advertising evolution' Atelli's AI Ad Pitcher can automatically adjust bids, thereby reducing advertising costs Image source Atelli Atelli's AI Ad Pitcher can find target audiences that are difficult for the human brain to envision, thus boosting advertising effectiveness Image source Atelli Supported by Atelli, successful cases of enhanced advertising effectiveness are spread across various industries For example, by optimizing operations with AI, the team helped a client running a fashion e-commerce platform to improve the quality of new site visitors, reducing new visitor acquisition costs by 60 and increasing orders by 160 For clients in the health food industry promoting new products online, the team used its core algorithms to precisely determine the target demographic, not only reducing the advertising cost by more than 10 but also increasing new customers by 200 Moreover, through AI automation and ad combination matching to find potential target groups high-value, new customers, the cost of gathering prospects for exclusive events like luxury car shows and online computer courses went down by at least 50 Atelli Product Manager Chen Lin mentioned their AI product with pride, saying, 'We are fully confident in our ability to help advertisers, based on our extensive past ad optimization experience and over five years of accumulated data Whether it's expertise or the volume of data, we're sure we can assist Moreover, integrating all ad campaigns seamlessly, we significantly reduce the customer's execution burden The system is easy to use, time-saving, finds more new customers, and effectively boosts performance The feedback we often hear from customers is that AI-run ads can increase effectiveness by an average of 10-20, with some customers seeing improvements of up to 200-300 Therefore, customers are willing to continue using AI to enhance their brand's competitive edge Atelli will continue to develop diverse AI products to help Taiwanese business owners find the best solutions through technology' To learn more about the Atelli AI Ad Pitcher product details, feel free to contact the Atelli teamContact E-mail csatelliai This article is published with authorization from Atelli on AI HUB「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【解決方案】搭上AI列車,翔威國際結盟華碩搶攻智慧製造
【2020 Solutions】 Riding the AI train, Shinewave forms an alliance with ASUS to tackle smart manufacturing

After the outbreak of COVID-19, the global manufacturing supply chain has undergone major changes, and the demand for localized production has greatly increased To help traditional industries achieve digital transformation and enhance their competitiveness, Shinewave, which has more than 20 years of software experience, has also been actively branching out from information technology IT into operational technology OT in recent years, and has jumped on the AI train, working with its parent company ASUS to seize the smart manufacturing market Software expert Shinewave transforms into a solution provider Shinewave is a software subsidiary of ASUS It was established in October 1998 by the product business group team of the Institute for Information Industry III "The company's slogan was 'We deliver quality software' during early periods, but it has now been adjusted to 'We deliver quality solutions'" Chun-Hua You, President of Shinewave, added that Shinewave has also transformed from providing software products to providing total solutions in response to customer needs The solutions provided include software, hardware, and system integration With more than 20 years of experience in manufacturing, Shinewave is now be able to create higher value for customers with the support of AI and IoT The main purpose of Shinewave's "Manufacturing Factory Automation Information Management System" is to help manufacturing customers strengthen the collection of production data in various units of the factory such as materials, production management, manufacturing, quality control, and warehouse management, and to quickly and accurately determine the current condition of production The complete network mechanism allows remote decision-making and factory management to be synchronized, and effectively monitors the manufacturing, quality control, and shipping processes, monitoring production in real time and improving product yields This achieves production efficiency and customer satisfaction, and reduces unnecessary management costs that do not add any value Shinewave helps customers create a blueprint for smart manufacturing with its complete information system framework and solutions Shinewave is committed to developing total software solutions for factory automation in the nbspmanufacturing industry, and has accumulated experience in more than 200 factories so far Its customer base covers 3C product assembly, notebooks, and industrial computers, and has a leading position in relevant markets Besides building strong competitiveness in the electronic and IT product assembly industry, Shinewave also assists corporate customers with widening their lead in the industry, and continues to strengthen data collection from each unit of the production line, allowing remote decision-making and on-site management to be synchronized in real time, while reducing factory management and maintenance costs In terms of future business expansion, traditional industries that are highly dependent on machinery have strong demand for information, visualization and AI This is the industry that Shinewave is currently actively focusing its efforts in Implementation of traceability to enhance the competitiveness of the design process "Wide variety in small quantities and customized markets are an important driving force of smart manufacturing" said Chun-Hua You In the past, foreign companies including HP, IBM, and Dell required Taiwanese foundries to establish a complete "traceability" system The electronics assembly industry is highly labor-intensive, has limited machine control capabilities, and has a large amount of production and testing data The key to competitiveness lies in the collection of data through information systems and providing traceability and analysis capabilities, so that OEMs can design products, improve quality, and improve processes Shinewave provides total solutions for electronic assembly plants In addition, data collection is also widely used in testing and quality inspection Using burn-in operation in the electronics industry as an example, the system automatically downloads and executes the test program by comparing the machine model and material number, monitoring abnormal conditions in real time, adjusting the test environment or suspending operations at any time The product quality can be immediately determined without waiting for the end of the testing process, which also allows companies to reduce labor and time costs Shinewave has accumulated a wealth of experience in electronic assembly processes Chun-Hua You pointed out that the consumer electronics industry adopted information systems earlier, and the main production lines are already in the Industry 30 stage To achieve the goal of Industry 40, future efforts will be directed to AIIoT In terms of AI, Shinewave is actively working with its parent company ASUS in AI image processing, recognition, and defect detection, and expands and deepens AI technology application solutions In terms of IoT, Shinewave has cooperated with a number of manufacturers in connecting machinery to the Internet and data acquisition, helping customers monitor the status of on-site production equipment in real time, reducing losses caused by abnormalities Over the years, Shinewave has combined its experience with major ERP companies in the industry to provide customers with total solutions for information collection at the internal planning and execution levels within the company Now it hopes to use its own capabilities to further integrate AI and IoT, join forces to provide customers with total solutions, and assist manufacturers with building a core information flow system for smart manufacturing through Shinewave's MES, integrating ERP, PLM, APS, and WMS and combining it with the physical layer of equipment automation This will allow vertical and horizontal information to be completely collected and actively used to develop smart factories and move into flexible smart production Chun-Hua You, President of Shinewave nbsp

【解決方案】開必拓打造客製化電極鋁箔AI品檢方案,漏檢率趨近0
【2020 Solutions】 Kapito Develops Customized AI Quality Inspection Solution for Electrode Aluminum Foil with a Missed Rate of Nearly 0%

Electrode aluminum foil is a key material for passive components in automotive electronics In the past, it mainly relied on hole detectors that could only detect simple defects With the advancement of automotive electronics, the demand for automotive electronics-related components has become stronger Since the products involve vehicle safety and environmental testing issues, the missed rate should be maintained at 0, while maintaining a misjudgment of less than 05, which are relatively strict quality requirements Smart manufacturing AI company Kapito developed the world's first customized electrode aluminum foil AI quality inspection solution The world's first customized AI quality inspection solution for electrode aluminum foil Kapito is committed to providing global manufacturing innovations and providing reliable AI quality inspection solutions fastableai uses multiple AI algorithms combined with multi-angle optical lenses to assist the manufacturing industry with product appearance inspection, reducing costs, stabilizing quality, improving efficiency, and expanding scale Targeting new business opportunities in automotive electronics in the future, Kapito developed fastableai, a hardware-integrated AI quality inspection solution It has completed the customization of an electrode aluminum foil production line and assisted Liton Technology, a major electrical etching and foil forming manufacturer, with completing production line deployment throughout Taiwan, using AI image recognition technology to effectively improve the quality and efficiency of Liton Technology's production lines Feng-You Sun, founder and CEO of Kapito, said that automotive electronic products have higher requirements in environmental testing because they involve vehicle safety The misjudgment rate of general commercial goods is between 2 and 10 The misjudgment rate for automotive electronics should be maintained at 0 and may not exceed 05 The quality inspection solution for a customized electrode aluminum foil production lines developed by Kapito mainly uses the AI algorithm of fastableai and big data analysis to achieve a misjudgment and missed rate close to 0 fastableai AI The defect detection solution has achieved remarkable results in reducing manpower, increasing scale, and shortening the payback period After Liton Technology deployed fastableai in all production lines in Taiwan, it broke through the bottleneck of quality inspection manpower, and can stably monitor the quality of aluminum foil production 24 hours a day, expanding its production scale In the past, more than ten kinds of aluminum foil defects were difficult to identify due to the limitations of aluminum foil production methods fastableai can accurately detect the defects and further upgrade the quality It is worth mentioning that in addition to quality inspection, fastableai also acts as the brain of production equipment It utilizes big data analysis and management to predict the maintenance cycle of production equipment and effectively improve the availability of equipment Chang-Yuan Chen, spokesperson of Liton Technology, said that through in-depth cooperation with Kapito and the introduction of fastableai into the production line, the quality status can be monitored at any time, which greatly increases the confidence of Liton Technology in the quality of its aluminum foil products in the automotive market, achieving the highest quality products fastableai uses AI algorithms to achieve 0 missed rate and 041 misjudgment rate Kapito was established in 2017 The founding team combined AI technology of Silicon Valley and the wealth of industry experience in Hsinchu Science Park, using cutting-edge technology to solve the most common pain points of Taiwan's traditional manufacturing industry, such as low birth rate and labor shortage fastableai is a device that integrates hardware and software developed by Kapito for "quality inspection" It uses an optical lens to capture images around the product, and then uses multiple AI algorithms for image recognition It can effectively handle extremely complex defects that are difficult to identify with the naked eye, and achieve accurate judgment and analysis capabilities close to the human eye, helping factories automatically complete product appearance inspection fastableai has achieved 0 missed rate and 041 misjudgment rate in the inspection of automotive electronics fastableai AI Defect detection solution applied to the leather inspection system interface In addition, fastableai can be quickly installed in existing production lines based on the applicability of different industries, allowing many manufacturers who are unable to significantly update or change the design of existing production lines to more quickly make key processes smarter, helping them successfully transform data into revenue After research and development is completed, it can be launched in the production line in as fast as 2 weeks Applicable raw materials include metal foil, textile, leather, and mirrorglass It can be applied to a wide range of industries, including textiles, metal processed products, automotive electronic components, semiconductorsprecision products, plastic rubber injection products, and cosmetic products Kapito's customers are mainly electronic products manufacturers Feng-You Sun, founder and CEO of Kapito nbsp

【解決方案】推出國內第一台口罩販賣機業安科技罩得住
【2020 Solutions】 The First Mask Vending Machine in Taiwan Launched! Yeasan Technology Got You Covered!

Taiwan's "mask prevention" strategy in response to COVID-19 has been effective, resulting in the worldrsquos lowest rate of confirmed cases and lowest mortality rates Yallvend Tech built the first mask vending machine with an interactive screen in Taiwan It is equipped with mobile payment, returns transaction data, and manages inventory data It is an embodiment of Taiwan's "epidemic prevention technology" Yallvend Tech's core service was originally to provide vending machine manufacturers with networking equipment, platform construction, and other vending machine upgrade services The Central Epidemic Command Center began implementing name-based mask sales on February 6, 2020 to prevent the spread of COVID-19 In February, Yallvend Tech displayed its mask vending machine technology at Ningxia Night Market in Taipei City It combines facial recognition and blockchain traceability technology in the first smart mask vending machine, which provided 2,000 non-medical masks for free in just one week, benefiting a total of 1,000 people Smart name-based mask vending machine in 6 district health centers in Taipei City, completing transactions online In order to alleviate the queues at pharmacies, a tripartite meeting between the Ministry of Science and Technology, Taipei City Government, and Yallvend Tech reached the decision to place vending machines in the health centers of 6 districts, namely Xinyi District, Wenshan District, Wanhua District, Zhongshan District, Datong District, and Neihu District, one vending machine each Citizens only need to insert their national health insurance card to verify their identity, and then use mobile payment, including Easy Card, Line Pay, Google Pay, or JKOPay, to complete the payment In addition to using mobile payment, Yallvend Tech has also installed simple POS machines in six other health centers, where citizens can quickly swipe their card, make payment, and collect masks at the mask counter Each health center distributes 200 masks every day for the public to purchase The mask vending machine makes it simple and convenient to purchase masks, easily preventing the spread of COVID-19 This time, Yallvend Tech cooperated with Taipei City Government and the Central Epidemic Command Center, successfully gained the support of the Ministry of Health and Welfare's open data database, and paired it with the AIoT human-machine interactive display interface from a well-known e-sports display technology company, so that people no longer need to wait in line and instead use their national health insurance card and online payment to buy masks directly at the vending machine However, this activity will come to an end in July after the epidemic subsides, and the National Health Insurance Administration's open data API may be terminated by then Interfacing with the largest and most important health insurance system in the country is a dream project for many engineers Yallvend Tech completed the connection, testing, and launch in just 12 hours, laying the foundation for the subsequent name-based mask system 30 This was a major technological breakthrough by Yallvend Tech Founded in January 2019, Yallvend Tech has been deeply involved in vending machine upgrade services The vending machines we generally see all sell drinks Yallvend Tech provides the technology that has upgraded vending machines to sell tobacco and alcohol overseas and masks in Taiwan Yallvend Tech has identified the needs of the Southeast Asian market and actively invested in the development of core technologies, such as physical identity digitization, online payment, and consumer feature identification mechanisms It not only attracted attention from major manufacturers such as Coca-Cola at the US Consumer Electronics Show CES in 2019, but also opened up the international market Yallvend Tech Team showcases technologies at the CES Duncan Huang, CEO of Yallvend Tech, pointed out that different countries have different regulations and vending machines are selling a wider variety of products, not only general consumer products such as beverages, but also controlled products such as cigarettes, alcohol, and even adult toys Each product is sold must comply with local regulations, including consumer identity verification This is the key to whether traditional vending machines can be painlessly upgraded into unmanned stores For example, alcohol accounts for the highest percentage in the beverage market, but due to the regulations of each country and its physical effect on consumers, many countries will restrict the age for purchasing alcohol, and the same goes for cigarettes By digitizing identity, smart vending machines will be able to verify the buyer's identity, and buyers who do not meet age requirements will be automatically filtered out Buyers who meet the requirement can freely purchase tobacco, alcohol, and other products on the vending machines At present, Yallvend Tech has exported vending machine upgrade solutions that combine identity verification, mobile payment, return transaction data, and inventory data management systems to the Philippines, Singapore, Malaysia, Japan, and IndonesiaYallvend Tech's product VUK is installed in vending machines on Kokusai Dori in Okinawa, Japan Two major food and beverage leaders adopt smart vending machine systems In Taiwan, Yallvend Tech's smart vending machine system was installed in 700 vending machines nationwide by the two leading domestic food and beverage companies Currently, the vending machines of these two major manufacturers are available in 30 of places close to consumers in factories, offices, and campuses, and real-time promotions will be launched for these vending machines in the future In another aspect, Yallvend Tech is also actively developing AI replenishment planning solutions for major beverage companies, hoping to use vending machine data to assist replenishment personnel with replenishing items, route planning, and more efficiently understanding inventory The company expects to launch related services in about a year

【解決方案】華碩AI深度學習影像辨識 讓瑕疵檢測更輕鬆
【2020 Solutions】 ASUS AI Deep Learning Image Recognition Makes Defect Detection Easier

For the manufacturing industry, replacing manual visual inspection with automated optical inspection is common, especially when the yield of 3C or semiconductor products is high General automated optical inspections often face the bottlenecks of insufficient defect samples and difficulties in qualitative and quantitative recognition Using AI deep learning for image defect detection has become increasingly significant AI detects minute defects, ASUS makes smart manufacturing 'visible' 'Initially, we hoped to promote upgrading with our 3C supply chain partners steadily, assisting the industry to enhance and face international competition,' said Chang Quande, ASUS Global Vice President and Co-General Manager of the Smart IoT Business Group ASUS Smart Solutions Business Unit uses AI deep learning to perform various workpiece defect detections, and layout after accumulating experiences is a priority task 華碩全球副總裁暨智慧物聯網事業群共同總經理張權德 For metal component manufacturers, detecting defects on surfaces is relatively difficult due to the reflection of light, which often causes actual defects to be overlooked Mastery of optical properties and the specifics of component surfaces is crucial The ASUS Smart Solutions Business Unit not only has AI experts but also a digital imaging technology team with unique post-processing skills and strong augmentation capabilities They can achieve correct defect data collection and train AI models efficiently even with a very small number of defect samples 'General optical inspection accuracy is about 85-90, and high precision-seeking manufacturers would not use it, as it implies a -10 defect misjudgment,' said Chang Quande Whereas manual visual inspection has an accuracy rate of about 93, it is labor-intensive and carries occupational hazard risks ASUS has now enabled AI to achieve 98 accuracy, fully capable of replacing manual inspections and certain traditional optical inspections Previously, it took three people to manage quality control across three production lines, now only one is needed In recent years, many manufacturing industries have been returning to invest in Taiwan Major metal structure stamping plants have also committed to establishing new factories ASUS has designed their three-in-one defect detection stations, capturing images through edge computing, uniformly training an AI model, and utilizing the same AI inference workstation to perform defect detection calculations Quality control stations across various production lines now monitor these processes in real-time Previously, three production lines required three people for quality control now, only one is sufficient, increasing the detection rate from 93 to 98 and reducing costs by 5 Accompanied by the reallocation of human resources, the stamping plant has achieved smart manufacturing and has broken the curse of increased production costs due to returning investments ASUS IoT 應用產業 除了金屬機構件之外,塑膠成型件、印刷電路板等電腦周邊元件生產業及系統組裝業都能運用AI 深度學習影像瑕疵檢測做高精度品管,目前也有半導體業正在優化導入華碩AI 深度學習影像瑕疵檢測,以補足自動光學檢測在晶圓層所抓不到的瑕疵,盼藉由AI的助力突破良率瓶頸,降低人工目測或自動光學檢測已知的誤判所造成的損失,更能利用人工智慧大數據針對品質瑕疵種類做統計分類以歸納出瑕疵形成原因,從源頭改善進而減少製程瑕疵。「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【解決方案】AI助攻 智合科技打造世界最小鑽石篩選機
【2020 Solutions】 AI Assistant - Zhihe Technology Develops the World's Smallest Diamond Sorting Machine

How should one inspect diamonds that are only half the size of human hair The answer is to use AI for the inspection Zhihe Technology has developed the world's smallest diamond sorting machine By integrating AI and machine learning, along with accumulating large sample data, the system becomes smarter, increasing the yield rate from 70 to 96 within two years Moreover, by incorporating AI technology into the laser cross-cutting machine capable of handling 500-nanometer laser machining optical measurements, it becomes the first laser machine globally implanted with an AI system 2016年從中國大陸回流的智合科技,是一家專門提供微測距影像量測系統服務的新創公司,其主要的服務項目包括微米級m甚至奈米nm級的微測距應用、半導體檢測、鑽石相關產品、高米密度刀具量測及非標準件檢測。 Zhongxuan Li, General Manager of Zhihe Technology, has over a decade of experience in AOI inspection After returning to Taiwan from mainland China, he established Zhihe Technology At that time, semiconductor processes evolved from 8 nanometers to 3 nanometers Due to high difficulty levels in processing, Li saw a significant market opportunity Plus, AI's development accelerated after Google released the TensorFlow software in February 2017 TensorFlow is an open-source software library for machine learning applications in various perception and language understanding tasks World's Smallest Diamond Sorting Machine - Improved Yield to Over 96 Consequently, combining his expertise in AOI and AI, Li chose the diamond sorting machine as their first proving ground Zhihe Technology assisted a major industry company specializing in grinding, cutting tools, optics, wafer refurbishment, and other precision industries with automating human visual inspection process of diamond operations This company's star product, the 'Diamond Disk,' uses diamonds the size of half a human hair Previously, the company used traditional visual inspection, employing over 80 workers per production line, many of whom were foreign labor or older employees The process was time-consuming, output was low, and labor costs were high Most importantly, their semiconductor clients demanded automation, digitization, and increased precision for diamond inspections With Zhihe Technology's help, they supported a semiconductor equipment supplier in fully automating their manual diamond inspection process They helped create the world's smallest AI-equipped diamond sorting machine, increasing the yield rate from below 70 to over 96, gathering millions of diamond data points per day 靠AI技術打造全球最小的鑽石篩選機 運用AOI及AI交互應用,大幅提升鑽石篩檢效率 此外,智合科技在2019年10月與雷射設備廠商雷科科技共同合作開發雷射十字加工機,簡單說,就是在只有髮絲二分之一的尖點上,打上十字,其精度及準度的要求更高。智合採用AOI方式自動標注,測量位置與角度對位及加工高度,再運用AI訓練位置與角度估算核心,反覆校調後,耗費4個月時間,開發出全球第一台植入AI系統的雷射十字加工機,有了AI技術的加持,讓原有的雷射機價格翻了三倍之多。 智合與雷科科技合作,共同打造全球第一台AI 雷射機 Three brilliant methods to make Auto-AI digital transformation so easy Zhongxuan Li shared that Zhihe Technology is able to quickly integrate AI technology and develop Auto-AI, allowing enterprises to rapidly adopt and smoothly transition into digital transformation There are three main methods of implementation Method 1, Simplifying training issues with an automated labeling platform Use cameras to collect data from machine manufacturers, replace manual labeling with automated labeling, and progressively train to improve accuracy The simpler the problem, the less data is needed for training Method 2, Parallel advancement of AOI and AI In smart manufacturing processes, relying solely on either AOI or AI cannot achieve everything First, AOI should be used to mark features and distinguish between good and defective parts, followed by AI for labeling and training Using them in tandem enhances their effectiveness, and as the training data accumulates, the proportion of AOI decreases while that of AI gradually increases Method 3, Enhancing the integration capabilities of embedded system peripherals Establishing new computation platforms embedded systems or IPC platforms continuously enhances the computing power of AI, thus lowering the industrial threshold for AI applications 為降低AI使用門檻與成本,智合科技建立自主開發核心-Auto-AI又稱為傻瓜系統,目前已經跟國內知名工控電腦大廠進行合作,提供使用者更簡易的AI 使用環境。李忠軒表示,台灣是全球最適合作AI系統的國家,擁有超強的電腦設計能力與系統整合能力,若能再加上軟核心平台,將可大幅提升AI落地應用的實證。 AOI與AI交互並行,將AI應用落地時程大幅縮減 智合科技有研發能力相當強的機械控制及AI演算法的專業團隊,主要是公司的薪酬制度不同,智合將70的利潤分享給員工,讓員工共同享受公司的成長果實,因此能吸引優秀人才投入,即時協助解決客戶痛點,在不更新設備的情況下,藉由AI技術的導入,提升原有設備價值。李忠軒也自許,智合將從純粹業務推銷性質的設備商,轉變成為工業升級服務方案商,並將客戶的滿意度與安全感,轉變成為市場行銷上的卓越口碑。 智合團隊,圖左二為總經理李忠軒「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【解決方案】20分鐘產出AI新聞稿,安普樂發介接品牌商與媒體的精準曝光
【2020 Solutions】 AI Press Releases in 20 Minutes - SparkAmplify Bridges Brands and Media for Accurate Exposure

What should small and medium-sized businesses or startups that want to export their products do when they lack PR resources, media exposure, and journalist contacts SparkAmplify, a company that builds global market platforms using big data, has created a precise media marketing platform SaaS that aggregates data from over 80,000 global media journalists With AI technology, it analyzes data and generates press releases within 20 minutes, matching them with accurately targeted international journalists to greatly increase exposure and achieve marketing goals internationally SparkAmplify's main service is a brand-media matching marketing SaaS platform Since its launch in 2018, it has continually analyzed international media trends and has already analyzed over 3 million international media reports, helping more than 1,200 companies from 25 countries achieve precise media exposure It has partnerships with major events such as CES and Computex, as well as famous incubation accelerators like TechStars, BootUp, Taiwan's TSS, Garage "Media are searching for news, companies are searching for media" By applying AI data, a balance has been found Jian-Qun Li, founder of SparkAmplify, explains, "From observing the demands of both suppliers and consumers in the media marketing market, there's a rigid demand for a platform that matches 'brands with journalists' based on both parties’ needs" Thus, SparkAmplify utilizes machine learning Logistic Regression algorithms to filter specific categories of news text and uses the LDA topic discovery algorithm to identify the hottest news trends, rolling out the 'AI Exploration of Media Trends' service Generate AI Press Releases in 20 Minutes to Find Suitable Media This system service only requires three major steps to disseminate the products or services of brands, small and medium-sized enterprises, and startups on the international market through international media coverage Step One, Material Preparation SparkAmplify sets up a dedicated brand page where brand managers prepare and upload complete materials including company profile, product names, service features, images, related product diagrams, etc步驟二、品牌故事撰寫:透過專家系統及運用機器學習Logistic Regression邏輯回歸演算法,將特定類別的新聞文本篩選出來,並透過主題探勘演算法LDA,找出最熱門新聞趨勢,系統會自動按結構、格式、片詞、文法、關鍵字等等,在短短20分鐘內自動生成AI新聞稿,再加以人工優化。步驟三、精準推薦:將公司及產品介紹、新聞稿等,媒合國際媒體共8萬名記者,將對的主題推薦到對的記者身上,主動提供記者報導素材,以增加媒體露出及曝光機率。 AI探勘媒體趨勢服務協助品牌公司精準國際曝光 Jian-Qun Li points out that traditional methods of gaining media exposure include holding press conferences or distributing press releases widely However, at international exhibitions, brand owners and small and medium-sized business leaders might not have sufficient PR resources Additionally, understanding industry trends and journalists' reporting preferences poses a significant challenge Aside from the challenges of data collection, extracting meaningful insights and trends can often be ineffective, time-consuming, and labor-intensive The 'AI Media Trend Exploration' technology can effectively and accurately collect data, use text mining and machine learning to unearth underlying information, and, by executing periodically, keep track of market changes to products 鎖定科技新聞領域 協助品牌業者精準曝光 善於資料分析的李健群,運用媒體大數據的分析技術,打造以機器學習進行分析的行銷系統平台,專攻歐美市場數據行銷決策與社群行銷,幫助行銷能力不足的的新創團隊,或有想要獲得國際媒體青睞的品牌業主,能以大數據分析找尋適合投放的媒體。 在AI技術的應用上,安普樂發使用NER命名實體識別技術,Named Entity Recognition技術來增加不同的屬性。例如人、組織、產品等,最後再透過知識圖譜Knowledge Graph建立屬性之間的關係,才能迅速達成預估目標。 由於新聞領域五花八門,包括財經、科技、政治、社會、運動、娛樂、美食、時尚設計等,資料數量眾多,但受限於儲存等資源,無法一一掌握,安普樂發將重點擺在科技新聞領域,與CES、Computex等大型國際科技展緊密結合,提供參展商在公關媒體上操作的資源,爭取國外媒體曝光機會,負責找對的媒體將品牌效益傳達、延伸出去。 三步驟完成媒體精準投放流程 SparkAmplify 商業模式主要為訂閱制,每月收取399美元,透過簡單步驟即可輕鬆完成品牌與媒體的對接服務。至於除了英語之外,未來是否會推出中文服務李健群表示,要跨到落地的語系需要重新建立一套模型,中文又比英文要複雜許多,處理過程要刪除非常多的雜訊。然而,因應中文化的需求日益殷切,未來在資源配置足夠的情況下,有機會也會推出中文服務。 SparkAmplify 團隊 SparkAmplify 創辦人李健群「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【解決方案】精實AI, 開源智造協助企業快速打造AI部隊
【2020 Solutions】 Lean AI, open source intelligent manufacturing helps companies quickly build AI teams

Does AI cost a lot Is importing AI time-consuming and labor-intensive How to build consensus within the enterprise and build a solid AI team All the above problems are common problems faced by enterprises in AI digital transformation Huang Mingshi, the founder and CEO of the AI startup Kaiyuan Intelligent Manufacturing Company, provides customized AI solutions on a "subscription basis" so that traditional enterprises that want to undergo digital transformation can quickly introduce AI solutions The term "Lean Production" appeared for the first time in the book "The Machine That Changed the World" in 1990 When it comes to business operations, there is no waste of resources Phenomenon, the process operates smoothly and creates the most profit with the minimum investment AI subscription service solution to quickly assist in importing tools Huang Mingshi graduated from Jiaotong University and received a PhD in Electrical Engineering from Penn State University in the United States He also worked for a start-up company in Silicon Valley for five years He was the chief data scientist and led a team of 10 people to develop multiple AI projects, including real-time image recognition , 5GAI, prediction system for dynamic expansion of cloud resources, etc Huang Mingshi returned to Taiwan to start his own business and established Open Source Intelligent Manufacturing in May 2019 The development direction is to promote AI subscription services He hopes to make AI practical and practical, help small and medium-sized enterprises with AI application needs, and accelerate the cultivation of practical capabilities of AI talents Huang Mingshi believes that the scale of AI project software and hardware equipment, which can easily cost NT2 to 3 million, is an "unbearable burden" for small and medium-sized enterprises with limited funds and human resources However, for those who lack For small and medium-sized enterprises with limited resources, AI can indeed solve the problem of automation, reduce costs and improve efficiency for enterprises in a short period of time, and is an indispensable tool for digital transformation Therefore, Huang Mingshi follows the principle of "lean production" to prepare AI digital transformation tools for small and medium-sized enterprises, using small projects to get started, from corporate health clinics to identify problems, corporate training, consulting to providing AI model solutions Done within a year In the process of project promotion, we assist the company's middle- and high-level managers to empower them and help them understand the company's pain points, what problems AI can help solve, and introduce benefit analysis By then, it will be relatively easy to introduce medium and large-scale AI projects Open Source Intelligent Manufacturing’s customized solution for the legal industry is the development of a “food advertising text recognition and analysis” tool A medium-sized law firm wants to help clients solve the problem of "identifying food advertising violations" According to statistics, there are more than 4,000 cases of advertising violations in the food industry every month The traditional method is to assign 2-3 lawyers to search for exaggerations or claims of efficacy in food advertisements published by major media The cost of each lawyer is calculated at NT5,000-10,000, which means the overall cost is considerable However, by collecting relevant information through the crawler system, and then importing AI technologies such as natural algorithm NLP to develop food advertising text recognition and analysis tools, the recognition rate can reach 90, which can also greatly reduce personnel costs In addition, Kaiyuan Intelligent Manufacturing has successfully applied face recognition to applications such as smart tourism and smart door locks, achieving an accuracy of 95 It has also used graphic recognition to help digital advertisers achieve the function of AI image removal , reducing the time designers spend on repetitive memorization by more than 80 It is worth mentioning that for designers, it often took 2 hours to memorize photos in the past Using the AI model, 1,000 photos can be memorized in 10 seconds, which is amazingly efficient This means that designers do not need to spend too much time memorizing photos, and can use their time to come up with creative ideas When photos are needed, they can use AI technology to quickly memorize them for ordinary consumers, when making presentations When designing PPT, you can also use photos that have been reversed to speed up the presentation production time In the future, it will also be connected to Google Flickr's personal photo album or image search, so that you can directly memorize the required photos and complete the task in one go At this stage, the open source intelligent manufacturing project is cooperating with APP manufacturers to remove the photos and create a free website to benefit more people working in the design industry Open Source Intelligent Manufacturing develops an AI model for hair back removal, the effect is comparable to that of professional designers In the medical industry, Kaiyuan Intelligent Manufacturing has also developed obstetrics and gynecology organ image recognition technology and conducted education and training in schools to help students make correct judgments Kaiyuan Intelligent Manufacturing also cooperates with the Taiwan Suicide Prevention and Control Association to use AI models to find people who are emotionally distressed, have depression, or have negative emotions and comments on online forums such as PTT and social networking sites such as Facebook, and design Prepare a suicide risk assessment and submit relevant information to the Taiwan Society for Suicide Prevention and Control to prevent it before it happens and reduce possible tragedies Four-step import method to complete the goal within one year In order to help small and medium-sized enterprises achieve the goal of AI application through subscription services, Kaiyuan Intelligent Manufacturing hopes to use methods to find enterprise pain points in the shortest time and at the same time enhance the commercial value of AI applications The methods are as follows 1 AI Discovery Workshop Guide companies to explore their needs through workshops or corporate health clinics 2 Enterprise AI training The introduction of AI requires the full support of the company's senior managers and the consensus of all employees to be successful Through a one-month training, it can quickly transform into an AI-empowered enterprise 3 AI consulting What is important is the technical feasibility assessment Not a set of AI solutions can solve any problem Different AI models must be established according to the different needs of the enterprise in order to prescribe the right medicine 4 Subscribe to AI solutions Four steps of import method Huang Mingshi pointed out that the services provided by Kaiyuan Intelligent Manufacturing are not a single solution, but customized AI solutions for enterprises There is no problem with talents such as AI algorithms What is more difficult is how to market this set of consulting services to customers in a simple way Fortunately, Kaiyuan Intelligent Manufacturing has participated in the "AI HUB" and "AI GO" projects of the Industrial Bureau of the Ministry of Economic Affairs Through the method of "industry raising problems and talents solving problems", we can understand the needs of enterprises, solve problems accordingly, and launch customer services Customized AI solutions The open source intelligent manufacturing team won the excellence award in the AI GO problem-solving competition The picture first from the right is the founder Huang Mingshi 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【解決方案】AI助攻,AOI檢測漏檢率達01 超過人工10倍
【2020 Solutions】 AI Enhancements, AOI Inspection Miss Rate at 0.1% Surpasses Manual Effort by 10 Times

Did you know a single golf ball can have up to 28 defect inspections Manually, one can inspect 500 balls in an hour, but with AI, up to 6,000 balls can be inspected in the same time Huiwen Technology has developed AOI Automated Optical Inspection technology that achieves a miss rate of 01, which is ten times better than human inspection Besides the golf ball industry, Huiwen Technology's AOI inspections are also being introduced to the textile industry and others Geng Cheng Lin, the founder and general manager of Huiwen Technology, has been an expert in artificial intelligence AI since 2013, recognizing the future potential and explosive power of deep learning DL and AI-based image recognition AOI has always been a strong demand in the manufacturing industry, mainly to improve product quality for business owners, stabilize the quality of delivered goods, and use data from AOI inspections to improve processes, thus creating a virtuous cycle and further cost reductions Due to uncontrollable factors such as human eye fatigue and inconsistent standards, inspection encounters bottlenecks The limit of human inspection miss rate after training is about 1-2, and the situation worsens over time AOI is a stable and capable of mass inspection device, achieving a miss rate of 01, which is ten times that of human eyes, implying a detection rate of 999 Of course, AOI also results in a 5-10 over-inspection rate, which can be further screened manually With the help of AOI, the burden of quality inspection is reduced, saving a considerable amount of labor time AOI Golf Ball Defect Inspection, Inspection Capacity Increased 12 Times per Hour The first litmus test of Huiwen Technology's AOI technology was on golf balls With their highly reflective, uneven surfaces, golf balls were previously inspected manually for defects A tiny golf ball can have up to 28 defects, and traditionally, only 500 balls could be inspected per hour A major domestic golf ball manufacturer, meeting the demands of Japanese customers, introduced AOI inspection two years ago The high-speed, high-precision AOI system combined with AI deep learning image recognition technology conducts defect detection on golf ball surfaces, fully automates the feeding and outfeed process, replacing manual recognition of missed defects, and can immediately record defect conditions and report back, inspecting up to 200,000 packs of golf balls per year per machine, greatly enhancing customer satisfaction However, this step took Huiwen Technology more than two years Golf Ball AOI Recognition Image Golf Ball AOI Recognition, 28 Surface Defects Unveiled Lin Geng Cheng says, from data assessment and consulting, followed by data organization and tagging, selecting and verifying AI algorithms to AI training services, the golf ball data is like starting from zero, accumulating one by one Thankfully, with full support from golf ball manufacturers, the efforts have finally bore fruit With AI inspection, while manually one might inspect 500 balls in an hour, AI can handle 6,000, achieving effectiveness 12 times greater Unlike other companies, Lin believes that AI needs to delve deep into domains to scrape professional data since only with such domain data can AI perform well Therefore, the company starts from individual projects, rather than setting an AI product from the beginning Without quality data or a focused domain, the best algorithms cannot succeed in AI Over the years, Huiwen Technology has accumulated project experience, gradually developing products while focusing on domain data and providing the latest AI algorithms to customers, growing together, creating a tighter collaboration, which is why, different from external fundraising, Huiwen's investors are customers or partners Evaluation to Official Launch AI Introduction Requires Six Phases The projects undertaken by Huiwen Technology are divided into several phases 1 Evaluation period, 2 Initial Validation POC period, 3 Data Collection period, 4 Repeated Verification period, 5 AI Positive Cycle period, 6 Official Launch The evaluation period involves understanding and assessing the Domain conditions of the demand side beforehand, followed by POC verification, extensive data collection after POC, entering repeated verification stage, and finally allowing AI to enter a positive cycle phase, achieving a certain level of effectiveness before the official launch Generally, a project takes about six months to a year to develop However, with more familiar PCB AOI projects, the first two stages are skipped, starting from data collection, thus significantly reducing the time 'Regardless of this project or others, common questions from customers are 'How much data is enough When will AI learn' Facing such questions, Lin points out that the reasons for these questions are 1 The inexplicability of deep learning technology, as it is a black box 2 Generally, customers lack the concept of AI technology Thus, the company must patiently verify data repeatedly, identify the data needed by AI, accumulate and test it, and clarify and resolve all Domain conditions, which requires a lot of time and patience During the AI introduction process, customers have high expectations of integrating AI services, thinking that it can immediately replace human labor Lin points out that this is not the case the real value of AI lies in accumulating large volumes of high-quality data, which is then transformed and analyzed to establish AI training and verification models to fully address problems generated by manual processes Apart from inspecting golf balls, Huiwen Technology is currently targeting the textile industry for items such as fabric and shoelaces, and many industries have conducted POC trials through Huiwen, including the semiconductor industry, PCB industry, and other traditional industries AOI Fabric Defect Detection, Top Image Shows Before AOI Inspection, Bottom Image Shows After AOI Inspection Lin Geng Cheng indicates that the most difficult aspect of entrepreneurship is nurturing talent and customer recognition customers often demand quick results, not realizing that AI adoption requires data accumulation and repeated verification, processes that cannot show results in less than six months Affected by the COVID-19 pandemic, the trend of globalization and centralization of the manufacturing supply chain has been disrupted, replaced by 'short region' supply chains, suggesting small, beautiful factories will flourish everywhere, potentially bringing new opportunities for AOI Lin notes that high automation indeed offers opportunities for automatic inspection AI, however, relatively high capital investments, including automation equipment, mainframes, GPUs, and sufficient AI maintenance talents, are burdens that small and medium enterprises or small factories cannot bear, requiring government financial resources and input to facilitate smooth transformation「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

rows
Rows:115, 13 pages