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

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

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

Quality defect detection AOI technology effectively reduces the wrong kill rate

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

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

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

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

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

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

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

The biggest challenge for enterprises introducing AI: improving customer trust

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

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

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

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

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

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

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

. Intelligent predictive maintenance

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

. Smart dispatch and scheduling planning

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

. Deep learning and automatic optical inspection

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

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

. Smart Situation Room

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

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

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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 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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 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learning, data science, front-end and back-end and other professional team combinations to make the platform operate successfully Xie Yuanbao said that he believes that only through the automatic learning of the visual analysis AI platform, automatic fast and accurate data processing capabilities, and providing customers with complete AI solution services in the cloud, cloud ground Hybrid to pure ground, can we truly Convince customers and stand out from the competition Looking to the future, Xie Yuanbao hopes that Xinyunlin Technology can build an image analysis AI platform for Mobility as a Service to automatically learn in various fields such as self-driving cars, smart warehousing robots, and unmanned buses in smart cities At the same time, I am also grateful to the support of the Industrial Bureau of the Ministry of Economic Affairs for the smooth landing of Xinyunlin Technology in Taiwan and the opportunity to recruit talents from all walks of life to work together In the short-term layout, the company will actively cooperate with domestic players such as Hon Hai and TSMC to implement image analysis AI technology in fields such as self-driving cars, smart industrial safety, and smart warehousing robots In the medium to long term, Xinyunlinke will target the United States, Europe, Japan and other countries as its global market layout, establish investment and cooperation partnerships with major international companies such as Microsoft, and replicate its successful experience and promote it internationally Xinyunlinke official website Xie Yuanbao, founder and chairman of Xinyunlinke 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

這是一張圖片。 This is a picture.
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 isUsingAIto detect。 In the era of rapid technological development, Leike proudly announces significant advances in its laser processing technology, thanks to the innovative applications of artificial intelligenceAILeike is committed to integrating advancedAItechnology into laser processing machines, and in2019year, in collaboration with partners, developed the world's first laser machining system that integratesAItechnology, and on this basis further developed in2023year the first ceramic substrate inspection machine that integratesAOIAILASERtechnology Smart Ceramic Substrate Inspection Machine Through the introduction ofAIand machine learning, along with the accumulation of big data samples, the system becomes smarter, which has led to improved product yield within one year5dramatically reducing the inspection time from originally2minutesper piece to just20secondsper piece, drastically lowering inspection costs, enabling efficient initial detection and post-laser marking to reduce waste in subsequent processes, diminishing overall carbon emissions of the site, allowing the automatic generation of detailed inspection reports for data analysis and optimization, which helps increase equipment capacity, reduce human error, enhancing the value of Leike's equipment, and strengthening the international competitiveness of the country's electromechanical industry Leike CorporationLaser TekFounded in1988year, and officially listed as a publicly traded company in2002year Since its establishment, it has become a leading global service provider and manufacturer of electronic packaging materials,SMDElectronic Packaging Materials,SMTinspection equipment, and laser systems Leike's general manager, with years of laser integration experience, observed that passive 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The simpler the problem, the less data needed for training Method three,AOIandAIDual-track Advancement In the smart manufacturing process, relying solely onAOIorAIis not enough to accomplish the task alone, it must be preceded byAOIfirst marking the characteristics, distinguishing between good and defective parts, then usingAIa method for labeling and training Subsequently, by utilizing a repeating cascade effect, the detection benefits are greater as more training data accumulates,AOIreducing the ratio of errors,AIand gradually increasing the accuracy ratio Post Adjustment Object Detection and Training Through three major methods gradually building system reliability, and categorizing data for defect sorting, ultimatelyAIreturning the judgement results to the main system, utilizing laser machining to control truly defective products at the front end of the process, reducing the inflow of defective products into other stations, thus minimizing losses due to repeated tests or reprocessing Leading in smart laser equipment, chooseLASERTEKthe right one Continuously developed by the Taiwanese brand Raytek, combiningAIsmart detection and laser processing equipment to progressively build a smart monitoring solution stack from raw materials, products, testing, laser equipment, etc, aiming at reducing the energy consumption of the production process, implementing semiconductor advancements, substrates and component processing among other fields, producing equipment products capable of meeting the end-user demands under low carbon conditions, rapidly and with quality products and services expanding both domestic and international markets, enhancing the global competitiveness of localMade in TaiwanMITequipment 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-12-12」

【解決方案】運用極現科技4D無人機雲端平台 巡檢成本降為五分之一
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