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 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 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 about2-5products 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 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 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 manage7070mmachieving 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 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」

Artificial intelligence AI has gradually changed the way various industries operate in recent years However, most of the work is still done by humans, with AI playing a supporting role This has led to emergence of the term "AI Copilot," which stands for "AI-driven tools or assistants" that aim to assist users in completing various tasks and improve productivity and efficiency The concept of AI Copilot comes from the role of "co-pilot" During flight, the co-pilot assists the main pilot in completing various tasks to ensure flight safety and efficiency In fact, there have been signs of various "machines" beginning to play the role of "copilot" in different fields since the Industrial Revolution, assisting humans in completing heavy physical and repetitive tasks, greatly improving factory production efficiency, and driving rapid economic development Following the advancement of computing equipment and breakthroughs in machine learning, deep learning, and image recognition technologies, the concept of AI Copilot has gradually taken shape The development of AI Copilot marks the transition from "machine-assisted to AI-assisted" Early robots could only complete preset repetitive tasks, but today's AI copilot can learn and adapt to new environments and tasks, and continuously optimize its performance in practical applications This transformation not only changes human-machine interactions, but also has a profound impact on various industries The application scope of AI copilot covers various industries, including finance, healthcare, manufacturing, education, retail, etc, and are everywhere to be seen Application of AI copilot in the retail industry AI image recognition checkout In the retail industry, the application of AI copilot has begun to show concrete results Take Viscovery's AI image recognition checkout system as an example This system is a type of AI copilot model that helps store clerks speed up checkout or assists consumers in simplifying the self-service checkout process The store clerk needs to scan the product barcodes one by one in the regular checkout method If a product does not have a barcode, such as bread and meals, the clerk needs to first visually confirm the items, and then input them into the POS checkout system one by one Based on actual measurements at a chain bakery, it takes 22 seconds for an experienced clerk from "visual recognition" to "entering product information of a plate of 6 items into the checkout system" New clerks may need even more time In addition, according to a Japanese bakery operator, it takes 1 to 2 months to train employees to become familiar with products Now with AI image recognition technology, store clerks let AI handle the "product recognition" step, and AI will play the role of copilot, quickly identifying items within 1 second, speeding up checkout to save 50 of checkout time, and optimizing customers'shopping experience The time cost of training employees to identify bread can also be effectively shortened Even for products with barcodes, AI can quickly identify multiple items in one second, which is more efficient than scanning barcodes one by one The self-checkout system "assisted" by AI image recognition allows consumers to successfully complete shopping without the help of store clerks, eliminating the trouble of swiping barcodes or searching for items on the screen, which improves the shopping experience In a time when store clerks are hard to hire due to labor shortage, this also helps stores reduce operating costs AI quickly identifies multiple checkout items in just one second Source of image Viscovery Recently, startups dedicated to developing AI image recognition checkout solutions have emerged in various countries The most lightweight solution currently known is in Taiwan It can be immediately used by installing a Viscovery lens and a tablet installed with Viscovery AI image recognition software at the checkout counter to connect to the store's existing POS checkout system There are various integration methods, including plug-and-play and API solutions integrated with the store's POS system Viscovery AI image recognition system can be painlessly integrated with the store's existing POS system Source of image Viscovery Example of AI image recognition checkout Currently, the Viscovery AI image recognition system is being used in bakery chains in Taiwan, Chinese noodle shops in Singapore, micromarkets in department stores in Sendai, Japan, and Japanese bakeries and cake shops Over 7 million transactions were completed through this AI system, which identified more than 40 million items These use cases demonstrate the extensive application of the Viscovery AI image recognition system in the retail industry In the future, the company will continue to explore the various possibilities of using Vision AI in retail and catering nbsp The Viscovery AI image recognition system is already being used in bakeries, cake shops, restaurants, and convenience stores in Japan, Singapore, and Taiwan Source of image Viscovery

Compared to Japan, where 90 of golf courses operate without caddies and use an automated service model, golf course management in Taiwan still heavily relies on human labor Facing a labor shortage of up to 70, adopting a site and membership management platform to provide intelligent golf services may be a transformation worth considering for golf course operators 'Taiwan's software technology is comparable to international standards and definitely has the capability to compete in the global market,' says Tsung-Che Liao, co-founder and CEO of Golface, established in 2014 with the vision to leverage technology at its core, aiming to create Taiwan's first golf entertainment platform With over 9 years vested in cultivating intelligent golf services, Liao is well-versed in the nuances of golf course services He has considerable domain knowledge and has launched a comprehensive intelligent golf solution The world's first networked smart golf cart hits the road automation of golf courses is no longer just a dream In mid-May, Golface's newly developed ARES Smart Golf Cat, the world's first networked smart golf cart, officially became operational Equipped with a dedicated vehicle computer mainframe, dual network systems, AI-based visual recognition cameras, and high-precision GPS tracking, golf courses can now confidently allow golfers to drive themselves The system enables real-time monitoring of any driving violations, and the presence of digital consumption traces allows for insurance coverage The procedure is as follows golfers book the cart via a reservation platform, receive a QR code, pay through the platform, and unlock the cart with the QR code at the golf course The golf cart can then be driven onto the course The course management platform can monitor and restrict the areas through which the cart can travel, ensuring it does not leave the paths Upon completion, the cart is returned through a tablet in the cart In instances of any infractions, penalties are applied directly through the user's account, and for severe violations, future access to the carts may be prohibited This achieves the goal of 'automation' ARES Smart Golf Cat is the world's first networked smart golf cart, officially in service since May 2022 'As labor costs continue to rise, recruiting and training caddies are becoming common pain points in the market While Taiwan's courses still employ caddies, there's a 70 labor shortage,' Tsung-Che Liao added This smart golf cart tablet, combined with a mobile app, has become the ultimate smart caddy Golface is striving to complete the last piece of the 'automated golf course' puzzle Amassing digital consumption trails for advanced client segmentation services Starting with consumer needs, Golface has sequentially launched services like the golf cart tablet, mobile app, golf reservation platform, instructional videos Golface TV, golf tourism, and smart carts The smart cart has been operational since May 2022, currently featuring four units with plans for mass production in the latter half of 2022 Although the cart currently requires manual operation by golfers, remote operation is anticipated early in 2023, with autonomous driving expected in the third phase Via the cart tablet and management system, staff can understand the status of the course through on-screen visual representations, showing each cart's real-time and relative location, departure times, and duration of service per hole, which aids course managers in monitoring on-course consumption effectively, thus reducing traffic jams and customer complaints 'Previously, we relied on staff's mental imagery now, we can employ imagery to visualize real-time situations on the course This makes it possible for those who don't understand golf to work in this field,' emphasized Tsung-Che Liao While course control has traditionally been handled by experienced professional players, the shortage of skilled professionals makes hiring even more challenging Therefore, replacing manpower with digital tools yields twice the result with half the effort The golf cart tablet has entered the Japanese golf market, installed at Fukuoka Century Golf Club Golface's golf cart tablet has been introduced to 14 domestic courses, and has now officially entered the Japanese market, favored by Fukuoka Century Golf Club, where tablets have been installed in carts providing automatic voice announcements for hitting strategies, distance measurements, and visual charts displaying hitting data During the COVID-19 pandemic, with borders closed, Golface utilized OTA technology to provide software updates and troubleshooting, ensuring uninterrupted services, which was highly appreciated by the Japanese golf courses Tsung-Che Liao remarks that Taiwan's software technology is not inferior to other countries like Japan, but more support from golf courses is needed to help transform the industry intelligently 'To assist in the transformation of golf courses, the first step is digitalization,' Liao pointed out By helping courses accumulate data and understand customer service cycles and hitting rhythms, it enables courses to avoid congestion and serve more customers To date, Golface has accumulated data on over 20,000 teams, 35 million scorecards, and over 10 million records This data helps enhance management performance, segment customer layers, reduce complaints, and plan marketing strategies for off-peak periods Golface co-founder and CEO Tsung-Che Liao has spent 9 years deepening intelligent golf services, aiming to build Taiwan's first golf entertainment platform「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」