:::

【2024 Application Example】 Testing Seat Contact Components AI Intelligent Flaw Detection

With rapid development in 5G, AIOT, automotive electronics, and other downstream sectors, the entire supply chain is expected to benefit from this consumer market. As product demand momentum gradually increases, increasing production efficiency and reducing operational costs become the most important issues. In order to meet the needs of customers for various packaging types, Yingwei Technology has been committed to developing highly customized test seats. However, a resulting pain point is the inability to mass-produce and fully automate operations with machines; some tasks still rely on manual execution. In this project, the probe part of the test seat was outsourced in 2021, and under current and future large-scale demands, work hours, costs, supply, and quality are issues Yingwei faces.
The company achieves a defect detection rate of 99.95%, which seems high, but with an average inspector able to inspect 10,000 needles per day, there would still be 5 defective needles. On a test seat that is only 3 cm wide with approximately 1,000 needles, just one defective needle could potentially lead to faulty testing at the customer end. As the current operational mode relies on manual visual inspection, external factors such as fatigue or oversight of personnel, and subjective judgment by inspectors may lead to the outflow of defective products, which necessitates strict quality control of contact components.
We once sought to utilize optical inspections (Rule-based) for controlling the quality of appearances, but the metallic material of the contact components leads to light scattering, background noise interference, background scratches, and material issues that could result in misjudgments. Therefore, we decided to look for AI technology service providers to solve our detection difficulties.

Developments of Dedicated AOI Line Scan Equipment

To meet the needs for inspecting thousands to tens of thousands of probes within our company's IC test seats, traditional surface imaging and individual needle imaging would be too slow to achieve rapid inspection and labor-saving goals. In response, the service provider proposed a trial with an AOI dedicated line scan module solution. Utilizing a width of 6.3mm on the X-axis for reciprocal scanning of all probes on the test seat, the tests allowed for the simultaneous scanning of 8-9 probes, significantly enhancing the future detection efficiency of AOI machines. This project will proceed with the aforementioned innovative Proof of Concept (POC), focusing on the development of the line scanning equipment and performing imaging, learning, and training on both normal and abnormal probes provided by our company, with initial AI model training aimed at preliminary approval.
This project's customized line-scan imaging module
This project's customized line-scan imaging module
Ideal future imaging result illustration
Ideal future imaging result illustration

A Single AI Technology Solution for Measurement/Detection Needs

Unified use of AI DL CNN learning methods, instead of the current Rule-based system which necessitates defining each defect individually, to meet the needs for abrasion measurement and appearance defect detection of malfunctions/foreign objects. When the same machine uses both measurement and detection technologies, not only does it increase costs, but it also affects the detection speed. Hence, the service provider recommends the use of a line scan device for imaging. Its resolution is sufficient for AI to simultaneously determine appearance defects and assess the condition of needle tip abrasion, as detailed below.

Line scan pixel imaging displaying needle tip abrasion conditions
Line scan pixel imaging displaying needle tip abrasion conditions

This AI detection technology meets both measurement and inspection needs for Yingwei, not only bringing more benefits to future probe testing but also introducing an innovative axis in AI technology.

Change the method of human inspection, enhance work efficiency and product quality!

After combining both hardware (line scan) and software (AI model training) approaches, we successfully ventured into new AOI detection applications. Following the AI implementation POC, including the development and validation of a customized line scan module and an initial AI model, the plan is to officially develop the AOI machine next year and integrate it into the IC test seat production line.

Future Prospects

Probe manufacturers upstream and downstream IC factory users both have needs for the AOI inspection machine; upstream can ensure probe quality before leaving the factory, while downstream users can use this machine to regularly inspect the condition of numerous IC test seats in hand. Given the future demands, the AOI machine is poised to have a significant positive impact on the IC testing industry in the foreseeable future.

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

Recommend Cases

【導入案例】挺進智慧物流50 新竹物流醫材配送班表超高效率
Advancing to Smart Logistics 5.0: Hsinchu Logistics Delivers Medical Materials with Ultra-High Efficiency

After incorporating AI technology, traditional logistics companies have seen significant improvements in transportation efficiency and reductions in transportation costs, especially in the transfer of medical materials which involves timely service and rights of hospitals and patients The implementation of intelligent logistics can save medical material businesses the cost of constructing GDP warehouses and other expenses up to millions A major domestic logistics leader, Hsinchu Transport HCT, owns a fleet of 3,500 vehicles and a storage area of 60,000 square meters, providing customized logistics solutions including logistics, commerce, finance, information, distribution, storage, and processing The company handles up to 580,000 parcels per day, with a maximum capacity reaching 900,000 parcels, making the enhancement of transshipment efficiency crucial for HCT Medical materials transportation at hospitals need optimization of current operational processes and enhancements in systematization and intelligence Especially the transportation of hospital medical materials, which encounters various challenges Medical materials suppliers need to cater to varying customer product demands, temperature requirements, and delivery times through multiple logistics providers This highly depends on the experience and careful control of operations staff Whether it is the product shipment or actual logistics process, each step must be interconnected Any human errors can impact the service timing and rights of the hospitals and patients Thus, all concerned businesses, along with the government and hospitals, are working to optimize current operational processes and elevate the level of systematization, automation, and intelligence to minimize service errors and cost losses HCT's distribution process prior to AI implementation Currently, with the government's push for standardized platform operations on the demand side of hospitals, supply-side businesses collaborate through data coordination to improve the accuracy and efficiency of product shipments, enhancing operational quality and management benefits at the demand side At the same time, some businesses are also investing in the standardization and systematization of internal operational processes, thus enhancing operational efficiency and quality In the freight logistics sector, logistics companies' warehouse staff need to expend labor to control different logistics shipment operations If they often receive emergency task notifications for shipments to medical facilities, they usually depend on small regional logistics providers to provide customized delivery services Although this improves delivery times, it does not allow for integrated informational services The new GDP regulations for medical materials require suppliers to undergo GDP compliance certification Therefore, Hsinchu Transport, assisted by the Ministry of Economic Affairs' AI coaching program, not only extends existing logistics services compliant with GDP regulations but will also use data integration and optimized AI technologies to help medical material businesses streamline and improve their logistics operations Complex logistics issues are solved using the Simulated Annealing SA algorithm To meet the 'Good Distribution Practices for Medical Devices,' Hsinchu Transport is not only actively introducing new logistics vehicles but will also implement artificial intelligence-based mathematical optimization technologies to assist in intelligent scheduling at nationwide business points and transshipment stations They aim to optimize the routing of medical materials between business points or regions thereby enhancing efficiency in the distribution process Currently, during the transshipment process of medical materials at Hsinchu Transport, detachable tractor heads and containers are used Each business point and transshipment station differ in location design and staffing, impacting the throughput per unit of time Furthermore, daily cargo conditions size, destination vary, and due to these fluctuating and distinct demands, the deployment of tractor heads and containers changes accordingly Under these circumstances, Hsinchu Transport relies on past experiences to schedule departures at each satellite depot and adjusts daily according to the cargo needs Due to the reliance on empirical scheduling, it is often difficult to consider all variables and considerations, leaving room for improvement in the current departure schedules The cargo delivery planning inherently constitutes an NP-Hard problem, difficult to solve with traditional analytical methods Hsinchu Transport, in collaboration with Singular Infinity, utilizes the Simulated Annealing SA algorithm to find solutions The new logistic service introduced by Hsinchu Transport is 'GDP Container Shift Planning' This planning involves estimating future volumes of medical materials between stations and scheduling container truck shifts accordingly, ensuring timely and quality delivery of medical materials while maximizing operational benefits and reducing travel distances Hsinchu Transport introduces AI-optimized shift planning, constructing the most efficient route from its origin to destination Hsinchu Transport introduces 'Optimized Shift Planning' service, reducing transportation costs by 5 The introduction method involves using cloud software services Hsinchu Transport regularly inputs 'Interchange Item Tables' from station to station into the 'Optimized Shift Planning' service After setting the algorithm parameters, a GDP container shift schedule is generated At the same time, developing a Hsinchu Transport medical material scheduling system allows Hsinchu Transport's medical transport units to compile suitable schedules through the Interchange Item Tables Under the same level of service, it's estimated that this can reduce transportation costs by 5, saving medical material businesses millions in construction costs for GDP warehouses and distribution Due to its requirements for sanitation, temperature, and its fragility, the transportation and transshipment of medical materials should be minimized to reduce exposure and risk However, logistics efficiency and costs must still be considered AI designs the most efficient route for each cargo from its origin to destination, effectively completing daily transportation tasks In response to the future high development demand of industrial logistics, distribution and transshipment AI optimization will be a key issue Through this project, a dedicated project promotion organization will be established, staffed with AI technology, IT, and process domain talents After accumulating implementation experience, the application of AI will gradually expand, comprehensively optimizing and transforming Hsinchu Transport's operational system, and partnering with AIOT and various AI domain partners to accelerate and expand the achievement of benefits「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.
[2023 Case Study] AI Steps into Philanthropy: Stylish Tech at Food Banks

Taiwan Food Bank AssociationHereinafter referred to as 'the Association'With the mission of providing food aid, poverty relief, reducing food waste, and building a hunger-free network, there are locations across Taiwan that gather donations from wholesalers, intermediaries, retailers, manufacturers, and even generous individuals These sites also rescue food that would otherwise be discarded, properly allocate and distribute it to needy households, thus aiding local vulnerable families55Food banks at various locations collect daily donations from wholesale stores, intermediaries, retailers, manufacturers, and even benevolent individuals from all over Taiwan These places also rescue about-to-be-discarded edible materials, properly sort them, and distribute to needy households, assisting local vulnerable populations However, each location requires significant human and volunteer resources to manage daily operations using traditional methods of communication with non-profit organizations and donors After receiving donations, these resources are then allocated to needy families or individuals There is a potential issue of uneven distribution of resources due to a lack of digitalization and integrated information management in these processes Warehouse and Transportation Centers and Mini Food Banks Distributing Resources to the Disadvantaged The location under validation by the Kaohsiung Charitable Organizations Association,Hereinafter referred to as 'Kaohsiung Charity' In109year6month24Officially inaugurated Taiwan's first 'Food Bank-Warehouse and Transportation Center' at a location measuring200square meters, enhancing the efficiency of food resource redistribution, proper storage, and management So far, nearly two hundred tons of vegetables and fruits have been saved, serving over a hundred organizations and benefiting over5thousand vulnerable households, and continues to serve19mini food banks, with planned completion across multiple districts in Kaohsiung, distributing food resources to over10ten thousand vulnerable families Kaohsiung Charity 'Food Bank-Warehouse and Transportation Center' in the Dasha Community Photo Source Kaohsiung Charitable Organizations Association Challenges in Labor and Food Resource Management Facing the needs of a large number of economically disadvantaged families, the management of the 'Food Bank-Warehouse and Transportation Center' is particularly critical During procurement, tasks such as sorting, purging, and bookkeeping must be performed, while during shipment, food resource needs suggested by social workers must be followed These activities rely on manual judgment and accumulated experience Many volunteers involved are elderly and have limited physical strength, making warehouse tasks physically demanding and recruitment challenging If a large batch of food resources arrives, space and manpower are consumed in sorting and inventory management, raising concerns about the effective use of resources and turnover rate This highlights the challenge of scaling up food bank services while lacking corresponding labor and material management systems At the same time, food bank resources come from various donations, thus they vary greatly in type, shelf life, standards, and quantity Volunteers at mini food banks, mostly also elderly, must handle multiple responsibilities such as case services, food resource management,resource allocation, and resource development Sometimes they must also explain and accept immediate, large quantities of specific resources, such as adults receiving baby formula 'Food Bank-Warehouse and Transportation Center' Resource Inventory Relies Entirely on Manual Labor Mini Food Bank Volunteers Handle Multiple Responsibilities Photo Source Taiwan Food Bank Association Reducing Scrap Resources60 Increasing Speed of Resource Transfer80 To enhance resource management and ensure effective use of materials, and to address personnel shortages, this field validation case has introduced 'Food Bank Warehouse Resource CollectionAITo advance resource management, ensure effective use of resources, and solve manpower shortages, this validation site has implemented an 'Automated Early Warning Needs Assessment System' for the food bank's warehouse resource gathering The first part involves building a classification model, setting up and collecting warehouse information at the site, andAItraining the model Past sitewarehouse information is collected and stored in a database, allowingAIfor preprocessing, classification, and other tasks At the same time, depending on the dependency conditions of the types of goods as features, algorithms are introduced for computation and modeling, and the data collected is used for retraining, ultimately validating the field and organizing data for the five most common types of goods into training and test datasets as required The second part involves constructing the classification model using AI techniques further use of reinforcement learning constructs the management mechanism for the food bank's warehouse, perfecting the classification of donated goodsRNNTechnical construction of classification models further use of reinforcement learning constructs food bank warehouse management mechanisms, making the classification of donated goods perfectlike white rice, instant drinks, noodles, instant noodles, and canned goodscan then be automatically assigned storage based on storage assignment principles AI Service System Process and Description Source Taiwan Food Bank Association AtAIUnder forecasts, it can optimize the speed of resource transfer and allocation, effectively and accurately match resource donations reducing the loss in the donation process, increase the accuracy of resource distribution, and improve the service rate—the successful donation rate—reducing the waste of resources due to incorrect items, and enabling instant monitoring of food resource stock, ensuring operators can respond quickly to needs, effectively providing resource assistance WithAIthe system's introduction and the establishment of data intelligence, it helps the operations of the warehouse and transportation center, allowing more time for the allocation of donated goods The introduction aims to accelerate the digital service rollout for social welfare organizations, thoroughly addressing the needs of the overall vulnerable segments of society Using the system for resource allocation and dispatching Photo Source Kaohsiung Charitable Organizations Association Following this field validation, it is possible to expand the system to other food bank service pointsAIThe system can also collaborate with more non-profit organizations, public welfare groups, and charitable organizations, expanding 'Food Bank Warehouse Resource CollectionAIAutomated Early Warning Demand Assessment System' application range such as medical supply distribution, helping more organizations manage and distribute more intelligently, reducing resource wastage, and enhancing social welfare 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-12-12」

【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 - Implementation in golf courses solves the problem of labor aging and shortage Chao-Cheng Chen further explained that the National Land Surveying and Mapping Center is a RTK service provider RTK provides the error reference map of the positioning point USRROBOT can access the positioning error value of a specific position through 4G Internet access The AI algorithm of USRROBOT reduces the general 10-20 m error of GPS to 2 cm After positioning, USRROBOT then uses six-axis accelerator positioning, gyroscopes, and wheel differential sensing devices for software and hardware integration Only by matching the wheel's movement pattern and the terrain can accurate mowing path planning be achieved The AI lawn mowing robot, which is 62 cm wide, 84 cm long, 46 cm high, and weighs only 25 kg, can set the mowing boundaries in the cloud It can avoid pools and sand pits through settings, using AI algorithms to automatically calculate the optimal path It is able to mow approximately 150 ping of grass in one hour The battery can be used continuously for more than 6 hours The battery life is currently the highest in the world In addition to general gardening companies, with the assistance of the AI project team of the Industrial Development Bureau, Ministry of Economic Affairs, USRROBOT's AI lawn mowing robot has been applied to golf course lawn mowing A well-known golf course located in Taiping District, Taichung City currently has a staff of 5 people who are responsible for the lawn, planting maintenance, and other landscape maintenance of the entire 30-hectare course However, the average age of staff is as high as 55 years old, and the golf course has been unable to recruit new staff members for a long time In view of the aging staff and the shortage of manpower, the golf course hopes to mitigate the impact with AI technology, and is therefore using AI multi-device collaborative mowing sensor technology, in hopes of reducing the burden of staff maintaining the golf course New challenges - Expert systems are needed to overcome difficulties with different grass species "This AI lawn mowing robot has low noise, low pollution, low labor costs, and is waterproof and anti-theft In the lawn mowing process, it can identify and avoid obstacles through ultrasonic sensors while maintaining mowing quality, maintaining aesthetic and consistent grass length" Chao-Cheng Chen went on to say that the most important part about golf courses is that the grass pattern should be beautiful and free from diseases and pests Based on the site survey, golf courses are mainly divided into three major areas green, fairway and rough There is no problem using the current mowing robot to mow the rough area, and it can overcome slopes within 20 degreesThe short grass in the fairway area may only be two centimeters long, and the grass types are also different, so the cutterhead design needs to be modifiedAs for the grass in the green area, the grass must be mowed close to the ground and maintained in a consistent direction because it affects the putting speed Many factors will affect the green index, and this part requires more research and testing The AI lawn mowing robot can identify and avoid obstacles through ultrasonic sensors while maintaining mowing quality The AI smart lawn mowing robot has a built-in camera that can be used to detect the health condition of the lawn Chao-Cheng Chen said that in the future, an expert system will also be introduced for early determination of whether there are diseases, pests in the lawn or whether there is sufficient moisture, and provide lawn health data analysis to customers, so that they can take preventive and response measures sooner to reduce disaster losses Chao-Cheng Chen, who is also a good golfer himself, said that golf has developed well in Taiwan However, due to weather factors, such as rainy and humid climate and typhoons, Taiwan's golf courses have harder soil and more potholes compared with top tier golf courses overseas If AI lawn mowing robots are to be widely introduced into golf courses, there are still many difficulties that must be overcome However, Taiwan's difficult terrain creates a good testing ground Once Taiwan can overcome the many problems and successfully introduce the robot, it will be able to expand to overseas markets and seize new market opportunities in a blue ocean Chao-Cheng Chen, President of USRROBOT nbsp