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【2024 Solutions】 AI Defect Intelligent Detection - Energy Reduction Smart Monitoring Solutions

AIIntelligent Defect Detection-Smart Monitoring Solution to Reduce Process Energy Consumption

When there are over2ten thousand chip resistors on a ceramic substrate, how should one quickly detect defects? The answer is:UsingAIto detect

In the era of rapid technological development, Leike proudly announces significant advances in its laser processing technology, thanks to the innovative applications of artificial intelligence(AI)Leike is committed to integrating advancedAItechnology into laser processing machines, and in2019year, in collaboration with partners, developed the world's first laser machining system that integratesAItechnology, and on this basis further developed in2023year the first ceramic substrate inspection machine that integratesAOI+AI+LASERtechnology.

Smart Ceramic Substrate Inspection Machine
Smart Ceramic Substrate Inspection Machine

Through the introduction ofAIand machine learning, along with the accumulation of big data samples, the system becomes smarter, which has led to improved product yield within one year5%dramatically reducing the inspection time from originally2minutes/per piece to just20seconds/per piece, drastically lowering inspection costs, enabling efficient initial detection and post-laser marking to reduce waste in subsequent processes, diminishing overall carbon emissions of the site, allowing the automatic generation of detailed inspection reports for data analysis and optimization, which helps increase equipment capacity, reduce human error, enhancing the value of Leike's equipment, and strengthening the international competitiveness of the country's electromechanical industry.

Leike Corporation(Laser Tek)Founded in1988year, and officially listed as a publicly traded company in2002year. Since its establishment, it has become a leading global service provider and manufacturer of electronic packaging materials,SMDElectronic Packaging Materials,SMTinspection equipment, and laser systems.

Leike's general manager, with years of laser integration experience, observed that passive component customers can produce over20With many years of laser integration experience, he observed that the production capacity of passive component customers can exceed10billionSMDcomponents every month, but withSMDcomponents per month. However, as component sizes continue to miniaturize, defect detection during production becomes increasingly challenging. With thousands to millions of components on a single ceramic substrate, and as component sizes decrease and their laser processing positions become smaller, the difficulty of detection increases, making production inspection a critical process.

R-SMD Production Inspection Process
R-SMD Production Inspection Process

AOIproblems of yield overkill relying onAIfor oversight,

Yet,AOIthe inspection machine is a widespread and mature type, but the high accuracy on the marketAOIuses a technique that captures small images in a single shot and stitches them into a larger image. Although accurate, this method requires more time for small-sizedSMDcomponents, which are more likely to be influenced by environmental factors like lighting and vibration that can cause misjudgments; as a result,AOIyield rate can only be estimated by sampling, and components with poor sampling yield are not removed individually but discarded together with good ones; manual re-inspection not only increases costs, but the lack of unified inspection standards ultimately results in about2%-5%products that are not detected as defective enter the subsequent manufacturing process monthly at least2,000thousands of such defective componentsSMDthat were not initially detected causing ongoing printing and machining inspections in subsequent processes. Regardless of the waste of ink materials and energy, which increases the cost burden, this also accelerates equipment wear and shortens operational life. Each stage of waste increases the site's carbon emissions, unfavorably impacting the company's carbon footprint.

Post-Adjustment Sample Photo Example 0402
Post-Adjustment Sample Photo Example 0402

TraditionalAOI High false positive rates in Automatic Optical Inspection (AOI) are a major production issue for manufacturers, particularly in the passive components industry where 'it's better to mistakenly reject a hundred than miss one'—a high standard, often leading to AOI setting extremely high parameters which makes devices overly sensitive. Excessive stringency in data parameter settings can lead to high false positive rates. For instance, if the dirt contamination on passive components resembles the color of the printing layers,AOI the misjudgment rate could reach 7 percent.

Contamination and Print Layer Color Similarity Make AOI Prone to Errors

Contamination Dirt

Contamination Dirt and Print Layer Color SimilarityAOIProne to Misjudgment

Raytek stands apart from otherAOIsuppliers by discarding the stitching of small images or line scanning, effectively preventing data loss and discrepancies caused by hardware or environmental conditions during image processing. It employs a large-array photodetector coupled with custom high-resolution lenses, using specialized imaging for composite processing. Throughout this process, each pixel of the photodetector contains light information captured from various positions. By combining this data, the image resolution and detail are enhanced, reaching a resolution of millions, and with multiple automatic light adjustments, a single shot can manage70*70mmachieving an image resolution up to5umobtaining clear images, then throughSmart-AItechniques for analysis and selection.

Three Innovative Methods to Achieve Rapid InspectionSmart -AI

Raytek's General Manager shares, rapidly implementingAItechnology and reducing inspection computation time, further developingSmart-AIthree major approaches:

Method one, initially useAOIto quickly separate good products from those with controversial defects, focusing the detection on the minority of defective identifications.

Method two, an automated labeling platform simplifies the training issue: by using cameras to collect data from machines, automatic labeling replaces manual labeling, progressively training to improve accuracy. The simpler the problem, the less data needed for training.

Method three,AOIandAIDual-track Advancement: In the smart manufacturing process, relying solely onAOIorAIis not enough to accomplish the task alone, it must be preceded byAOIfirst marking the characteristics, distinguishing between good and defective parts, then usingAIa method for labeling and training. Subsequently, by utilizing a repeating cascade effect, the detection benefits are greater as more training data accumulates,AOIreducing the ratio of errors,AIand gradually increasing the accuracy ratio.

Post Adjustment Object Detection and Training
Post Adjustment Object Detection and Training

Through three major methods gradually building system reliability, and categorizing data for defect sorting, ultimatelyAIreturning the judgement results to the main system, utilizing laser machining to control truly defective products at the front end of the process, reducing the inflow of defective products into other stations, thus minimizing losses due to repeated tests or reprocessing.

Leading in smart laser equipment, chooseLASERTEKthe right one!

Continuously developed by the Taiwanese brand Raytek, combiningAIsmart detection and laser processing equipment to progressively build a smart monitoring solution stack from raw materials, products, testing, laser equipment, etc., aiming at reducing the energy consumption of the production process, implementing semiconductor advancements, /substrates and component processing among other fields, producing equipment products capable of meeting the end-user demands under low carbon conditions, rapidly and with quality products and services expanding both domestic and international markets, enhancing the global competitiveness of localMade in Taiwan(MIT)equipment.

「Translated content is generated by ChatGPT and is for reference only. Translation date:2024-12-12」

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【解決案例】神經元科技 動鑑觀顫 以眼為始 最佳智慧醫療輔助者
Neuron Technology, moving and observing, starting with the eyes, the best smart medical assistant

Looking around the world and in Taiwan, the number of patients suffering from vertigo is increasing year by year When faced with vertigo testing, most people will choose to have it diagnosed by a doctor or hospitalized with neuromedical imaging tools such as MRI or CT for interpretation However, this may lead to misdiagnosis of vertigo, overdiagnosis of patients, waste of medical resources, etc, and cannot be effectively traced back The actual condition of the patient's dizziness In order to solve the long-term clinical pain point of vertigo, Neurobit has developed a smart wearable medical device - NeuroSpeed smart glasses and an AI assistance system It provides an AI smart solution for rapid screening of vertigo, assisting doctors in quickly screening more than 80 of brain diseases Efficient detection power with accuracy and sensitivity of over 90 Neuron Technology was founded in 2016 The co-founders include Yang Juncheng, Chen Weicheng, Huang Jinxun and Wang Jingfu The four of them were studying at the National Taiwan University Medical Engineering Institute and the Creative Entrepreneurship Program to jointly offer the "Biomedical Innovation and Commercialization" course Next, let’s embark on the entrepreneurial journey together The core team members of Neuron Technology are mainly composed of cross-field experts in medical engineering, information technology, neurology, patents, business, etc The common entrepreneurial concept is to continuously explore and explore unsolved pain points in medical clinical practice Seeing that patients were suffering from vertigo, Neuron Technology invented and independently developed an efficient and practical wearable smart medical device, NeuroSpeed Smart Glasses, which combines hardware AI-assisted decision-making system software to provide an AI smart solution for rapid dizziness screening Neuron Technology CEO Yang Juncheng said that the proportion of people in Taiwan and the world who suffer from vertigo is very high In 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can effectively assist doctors in quickly screening for potential brain disease risks in patients with vertigo Field verification with foreign medical centers mainly involves vertigo patients admitted to the emergency department Physicians can use NeuroSpeed smart devices to interpret the phenomenon of stroke diagnosis Currently, the accuracy of clinical trials in the above-mentioned cooperative hospitals reaches 80 and the sensitivity reaches 90 Neuron Technology develops smart wearable medical device NeuroSpeed smart glasses In addition to becoming the best smart medical assistant for doctors to quickly screen brain disease risks in the clinic and emergency department, NeuroSpeed smart glasses also assist doctors in the detection and assessment of strabismus risk They are jointly developed with the Tri-Service General Hospital through neuron technology The "Portable Strabismus and Abnormal Eye Movement Diagnosis System" is implemented in the Tri-Service General Hospital, providing 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in quickly screening brain diseases and eye diseases, extending patients' golden treatment time and reducing social risks health care costs to create a triple win NeuroSpeed smart glasses assist doctors in quickly screening brain and eye diseases Looking at the world, the pioneer of smart medical equipment, a new paradigm of biomedical software and hardware system integration In the early days of Neuron Technology’s entrepreneurship, technology research and development and business expansion faced many challenges Yang Juncheng expressed his sentiments that since the NeuroSpeed product is the first medical smart glasses developed in China, both in terms of obtaining hardware raw materials and developing technical specifications, The challenges associated with building and integrating related systems are higher than those for consumer electronics Additionally, bringing together cross-disciplinary talent and integrating it into a core team is also an entrepreneurial challenge In terms of 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Yang Juncheng hopes that Neuron Technology can become a pioneer in smart medical equipment, with research and development oriented to meet the needs of users and patients, and also hopes to become a model for the integration of biomedical software and hardware systems For the medium and long-term layout, the company will promote industry-university exchanges and cultivate biomedical talents integrate upstream and downstream industry resources to create smart medical solutions and platforms and actively explore foreign sales markets such as the United States and Europe as a basis for sustainable development of the company Vision 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

這是一張圖片。 This is a picture.
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【解決方案】滴水不漏的智慧工安巡檢 鑫蘊林科Linker Vision的影像分析AI平台 創造巡檢時間從100分鐘降至3秒新紀錄
Watertight smart industrial safety inspection Linker Vision’s image analysis AI platform sets a new record of inspection time reduced from 100 minutes to 3 seconds

With the rise of smart manufacturing, there is a demand for industrial safety inspections in high-risk industries such as chemical, energy, and electrical industries Take pipeline inspection in the chemical industry as an example It relies heavily on manual regular inspection and monitoring, and lacks intelligent monitoring by a professional AI team This is not only time-consuming and labor-intensive, but may also cause accidental risks to employees in various industrial safety environments The image analysis AI platform developed by Xinyun Linke not only improves employee personal safety and reduces risk factors, but also significantly reduces the time for human visual inspection of pipeline abnormalities from an average of 100 minutes to 3 seconds Paul Shieh, founder and chairman of Linker Vision Co, Ltd Linker Vision, said, "The overall technological development and progress in the United States comes from entrepreneurship Linker Vision's original intention to start a business in Taiwan has been I hope that through my past experience in entrepreneurship in the United States, I can introduce the American entrepreneurial spirit and culture to Taiwan's budding entrepreneurial fertile ground and truly implement it "American entrepreneurial culture encourages employees to value ownership and emphasizes that employees regard themselves as owners of the company Be a part of the company, with a work attitude and spirit that would be better than mine The company's achievements are your own achievements, breaking the original employer-employee relationship The company will reward outstanding employees with stocks, share the glory together, and establish a partnership with employees Partnership On the other hand, Taiwan still has room for efforts in entrepreneurial culture and management, and it retains the traditional thinking of employers and employees It is expected that Xinyun Linke's establishment of American entrepreneurial culture and values in Taiwan will serve as a starting point to drive more domestic new companies to follow suit, and then Only by upgrading the business constitution of new software AI entrepreneurs can they break out of the cocoon and go global Facing the market, most international players focus on developing AI models and algorithms They are less willing to invest in data-centered Data-Centric AI services They think that processing large amounts of 2D or 3D data is quite time-consuming It’s also energy-consuming Seeing the gap in AI technology and encouraged by Microsoft, Xinyunlinke decided to fully invest in Data-Centric's AI technology layout and deep roots many years ago, and specialize in technical energy in data processing, filtering and accuracy Therefore, Become an important partnership with Microsoft for AI technology supply In addition, due to the gap in industrial demand, domestic large factories, whose strength is chemical manufacturing, still rely heavily on manpower for inspection of pipelines in the factory, which is time-consuming and labor-intensive However, in order to cater to the AI industry, the owner reorganized the IT department originally engaged in database management and control into an AI team However, due to the owner's lack of professional experience in AI software technology, AI models and related domain know-how, the owner introduced AI implementation Industrial safety monitoring in the chemical industry is even more challenging The world's first AI automatic labeling technology surpasses manual labeling and can visually identify objects with an accuracy of over 95 In terms of AI technology power, Xinyunlinke has launched the world's first dual-core innovative technology of automatic labeling Auto-labeling and automatic machine learning to create an efficient and stable image analysis AI platform to provide customers with the best Advanced and complete AI solutions In terms of automatic annotation, this AI technology can overcome the most difficult challenge in deep learning, which is to provide customers with the highest quality training data Taking self-driving cars as an example, how to enable one self-driving car to effectively identify another car is the importance of labeling In the past labeling methods, we first needed to collect digital images of millions of vehicles, roads, signs, and pedestrians, and spent a lot of manpower Manually labeling one image at a time was time-consuming, labor-intensive, high in labor cost, and inefficient Through automatic labeling AI technology, combined with automatic machine learning to automatically label digital images, AI can exclude human error labeling and then throw the correct data into the vehicle's brain for vehicle identification Compared with manual labeling accuracy of only 60, the accuracy of automatically labeling and identifying objects with AI can be as high as over 95 It can also reduce manual labeling time by more than 80 and save at least 80 of labor costs AI automatically marks AI behavior recognition for high-altitude operations In the automatic machine learning part, Xinyunlinke established an AI visual model with continuous learning capabilities to adapt to data changes By optimizing the overall development process, from AI data ingestion and filtering Data Selection to AI labeling AI Labeling , model training and verification, deployment and monitoring, so that AI computer vision can continue to learn more quickly and easily Automatic machine learning can currently be applied to different business cases such as object identification and counting, personnel entry and exit security detection, product defect detection, people flow identification, product shortages on shelves, etc Looking at domestic companies such as TSMC, Formosa Plastics and Hon Hai towards intelligent AI management and purchasing a large number of cameras to meet the image recognition needs of industrial safety surveillance, coupled with the introduction caused by the unfamiliarity of existing customer organizations with AI applications Thresholds and preliminary preparations for image recognition include complicated workflows such as data screening and annotation To this end, Xinyunlinke has been committed to accelerating the development of AI computer vision applications in recent years, providing client-to-end services, and can flexibly deploy according to customer needs Complete automated AI solution services in the cloud, on-premises, or cloud on-premises Xie Yuanbao said that the AI automation technology process provides data selection Data Selection AI technology through domain-type pictures given by customers, helping customers automatically filter out precise such as 10,000 transactions from a large amount of data such as 1 million transactions Data, and by using the AI algorithm technology of Auto-Labeling to replace manual labeling, it can effectively save customers a lot of labor costs and achieve efficient data labeling processing In addition, the AI technology of automated machine learning can help clients customize automatic AI model training or repeated training when the factory environment changes, providing more accurate AI models and allowing customers to operate autonomously Through the above-mentioned key features and advantages of the automated AI technology provided by Xinyunlinke, we believe that it can definitely meet the needs of customers for an automated end-to-end AI independent learning platform, and at the same time, it can significantly save customers the cost of AI team establishment In terms of technological competitiveness, in addition to providing the chemical industry with AI image analysis applications in smart industrial safety, Xie Yuanbao said that Xinyunlinke can also extend the process application of automatic annotation and automated machine learning to different industrial landing services, such as Various fields such as self-driving cars, smart warehousing self-propelled robots and self-driving buses in future smart cities are all in line with the spirit of automated mobility of Mobility as a Service We look forward to the role played by Xinyunlinke The process of image annotation in different industries accelerates the efficiency of developing image recognition services in different fields We believe that by providing client-to-end AI solutions and a complete set of automated AI image analysis pre-operation processes from Data Selection AI technology, Auto-Labeling AI technology, and automated machine learning AI technology, we can greatly satisfy our customers The demand for AI autonomous learning platform Image analysis AI platform sets a new record for smart industrial safety inspections from 100 minutes to 3 seconds Seeing the high demand for industrial safety supervision in high-risk industries such as the chemical industry in recent years, Xinyunlinke launched the "Vision AI Platform", which uses AI image recognition technology Its main functions include real-time AI streaming It has four major functions detection, event notification, defining customer-specific AI models and continuous learning In the real-time AI stream detection part, the Vision AI system can use the customer's factory camera combined with the AI module to perform real-time stream detection of AI image events It can help customers manage various operations and factory environments and keep track of them anytime and anywhere Various work situations in terms of event notification, the Vision AI platform can provide a web version or APP or LINE instant messaging software to provide customers with video records of the events at that time, so that the team does not miss any events, maintains daily production capacity and reduces accidents in defining customers In terms of exclusive AI models, a variety of basic AI models are available, including 8 detection scenarios electronic fences, personal safety equipment, construction safety equipment, construction operations, personnel counting, screen availability, smoke detection, pipeline corrosion and damage , illegal stacking for use in different industries, customers can build exclusive AI models without spending time writing programs in the continuous learning part, the Vision AI system can provide customers with the performance and accuracy of AI models, and have the ability to adapt as the environment changes Continuous learning ability Vision AI has a simple user interface and intuitive operation For cross-field industries, this platform has automated and flexible AI capabilities Customers can build self-defined AI models without spending time writing programs, and Vision AI gives AI models the ability to continuously learn and improve, allowing customers to save the labor cost of building an AI team In addition, the platform can significantly reduce the manpower allocation for routine inspections required for operational safety management, improve employee safety in the working environment, and reduce on-site accidentsrisk factors at various work sites In the platform operation mode, customers can reduce the risk of manual monitoring operations through remote operations, ensuring normal work operations and uninterrupted production operations They can also review high-risk operating situations and collect data to assist in the planning and correction of operating processes In addition, in order to ensure that customers comply with government regulations, Vision AI can help customers control the equipment and safety regulations required in different workplaces at any time through the platform's event notification and management detection The image analysis AI platform is used in cross-field AI image recognition technology Generally, for industrial safety inspections in the chemical industry, most rely on the naked eye of personnel to regularly inspect pipeline abnormalities It takes an average of 100 minutes to scan an area each time, which is time-consuming and laborious, and the 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」