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【2020 Application Example】 AI Helps Establish the Best AOI Parameter Model for Passive Components, Reducing Production Costs of Over-Screened Components, Saving NT$2.5 million Annually

Traditional AOI uses limited sample images for inspection, facing the problem of high over-screening rates

In the electronic component manufacturing industry, AOI (Automated Optical Inspection) equipment is often used to measure defects in product appearance. For a long time, AOI measurement equipment has used limited sample images in image processing to compare the appearance of products from different external light sources and angles.

This comparison method can automatically screen for defects in product appearance. However, due to current technical limitations, there are often problems with light source parameter adjustment between product batches. If an inexperienced technician handles these adjustments, it will lead to a decrease in machine utilization rate and high over-screening rates.

The maturity of AI image machine learning has brought new opportunities for the AOI process

In terms of Taiwan's passive components, chip resistors and MLCC currently rank in the top two worldwide in terms of market share in 2019. In the long term, various car manufacturers have launched electric vehicles and smart vehicles, and various countries have also developed 5G-related equipment, which will further increase future shipments of passive components. Therefore, besides expanding new product lines, how to help existing products enhance their competitiveness will be the key to the industry's future international competition.

AOI inspection is one of the common stations in the passive component process, limited sample images are used in the current stage to compare the appearance. However, when switching between product batches, there are often problems with light source parameter adjustment, and the condition of these adjustments will affect the over-screening (mis-screening) of good products in each batch. In each batch of defective products in the industry, on average over-screening (mis-screening) occurs 20% of the time.

Relying on the guidance capabilities of the Southern Taiwan Industry Promotion Center, which has been deeply involved in Southern Taiwan for more than a decade, the company was matched with the AI image recognition technology unit of the Industrial Technology Research Institute (ITRI) to address the pain points of the passive component industry, reducing over-screening in the AOI process and also reduce errors caused by manual adjustment.

Using image recognition technology to reduce the occurrence of AOI over-screening

The technical unit of the ITRI that participated this time used image recognition technology to develop AOI technology for passive component processes in the establishment of AI modules.

In the development process, the company in this case first provided product appearance images and corresponding adjustment parameters, and then used the adjustment logic of current production line personnel to construct a product data set and further establish an AI model. When planning the production line test, the first priority is image recognition rate. Image detection and tag search are combined with comparison by an AI module to output AOI adjustment parameters for reference by online personnel.

Image analysis diagram

▲Image analysis diagram

In the future, we also hope to use the help of machine learning to complete the AI learning curve for machine parameter adjustment, further reduce the over-screening rate of product appearance defect detection, simultaneously solve the gap in on-site professional and technical talent, and increase product yield.

Before and after scenario of incorporating machine learning

▲ Scenarios before and after implementing machine learning

Implementing AI applications in processes to lay the foundation for developing unmanned factories

In the future, we hope the guidance of AI HUB will accelerate the application of advanced process technology and establish AI indicators for each station of the passive component process, which will help domestic production of high quality passive component products and increase product yields and prices. It will use innovative thinking to increase the added value of the industry and continue to lead the passive component industry forward.

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【導入案例】屈臣氏導入insider AI 技術平台 加強客戶體驗提升轉換率
Watsons Introduces Insider AI Technology Platform to Strengthen Customer Experience and Enhance Conversion Rates

Watsons Taiwan, holding the leading position in physical chain drugstores in Taiwan, has continued to expand its digital transformation Since establishing Watsons' online store in 2014, apart from actively developing the e-commerce market, the company has significantly enhanced the online and offline OO omni-channel consumer experience by integrating Insider AI technology This integration utilizes extensive in-store sales data, consumer behavior analytics, and AI-driven personalized recommendations delivered at optimal times to increase conversion rates OO Online Plus Offline Boosts Customer Conversion Rate, Driving Business Growth Watsons Group, a global retail giant, has been deeply rooted in Taiwan for the past 30 years specializing in retail, store operation SOPs, and retail supply chain optimizations However, managing an e-commerce platform only began a few years ago Unlike the commonly discussed 'O2O' online to offline in retail, Watsons adopts 'OO', which is offline plus online 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【解決方案】優式AI智能割草機器人 搶攻高爾夫藍海市場
USRROBOT's AI Lawn Mowing Robot Enters the Blue Ocean of Golf Market

An AI smart lawn mowing robot, resembling a vacuum robot, shuttles back and forth on the 30-hectare golf course lawn for weeding This robot, independently developed and designed by Taiwanese, is equipped with the world's first electronic fencing positioning technology which utilizes high-precision GPS integrated with cloud AI computation to determine the most efficient mowing paths, targeting the lucrative blue ocean market of golf courses This AI lawn mowing robot was developed by USRROBOT, a Taiwanese startup established in 2019 Chao-Cheng Chen, the president of USRROBOT, once served as the executive vice president of one of the top five ODM tech companies in Taiwan, and specializes in software and hardware integration When he served as the chairman of the Service Robot Alliance, he knew that the service robot industry was bound grow rapidly due to declining birth rates and the growingly severe labor shortage New demand - The horticulture market is large and the has rigid demand "To develop the core technology of service robots, we must find rigid demand Looking at European and American countries, there is a shortage of labor, but demand for horticulture has increased, and there has been a long-term shortage of 7-10 of horticultural workers" Under this strong "rigid demand," Chao-Cheng Chen established USRROBOT, and the company's first product is the AI lawn mowing robot In terms of overseas markets, the United States is the world's largest horticulture market, accounting for 30-40 of the global output value It is estimated that there are about 1 million horticulture workers, but they have been experiencing a labor shortage of 7-10 in recent years and have not been able to improve the situation The main reasons for labor shortage are Aging population and gardening is a labor-intensive job, so young people don't want to do it Unlike in Taiwan, European and American countries attach great importance to lawn maintenance and have expressly stipulated in the law that heavy fines will be imposed for failing to mow the lawn Therefore, the AI lawn mowing robot has considerable market development potential The introduction of AI multi-device collaborative mowing sensor technology is expected to reduce the burden of staff maintaining the golf course The AI lawn mowing robot developed by USRROBOT is currently in its second generation Domestic universities and well-known art museums are using the latest model M1, and it is also being used by some world-renowned high-tech companies and well-known universities in the United States The company is currently involved in negotiations for subsequent business cooperation USRROBOT stated that the professional RTK system currently used can reduce the original GPS positioning error from tens of meters to about 2 centimeters, allowing the robot to move accurately outdoors After setting the boundaries, it can be easily operated using the app New application - 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【導入案例】東森得易購導入OneID AI流量變現服務 成本效益可達2倍
Eastern Home Shopping Implements OneID AI Traffic Monetization Service, Cost-Effectiveness Up to 2 Times

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