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【2020 Solutions】 Fans and Motors Detect Abnormalities through AI, ASUS AI Solutions Team Exhibits Exceptional Capabilities

"Fans" are small but crucial components found in computers and home appliances. Though simple and comprising only a few parts, these components are key to maintaining 'coolness' and thus ensuring the longevity of machines. But how do fan manufacturers detect the quality of fans? The answer lies in 'listening' to the sound produced during fan operation to judge their quality. Issues such as axle misalignment, bearing anomalies, or blade interference can produce unusual noises, indicating that the fan is of poor assembly quality. Similarly, assembly quality inspection for other 'moving parts' like motors, engines, compressors is often carried out in a similar manner (As depicted below, auscultation testing of Ford RS engine assembly quality).

Auscultation testing of Ford RS engine assembly quality (Image source: kknews.cc)

▲Auscultation testing of Ford RS engine assembly quality (Image source: kknews.cc)

Historically, fan industry inspectors must complete 3-6 months of 'auditory recognition' training before officially starting work, which takes place in soundproof booths similar to phone booths to ensure no background noise interference. However, after about 6 months (varies by individual), human ears become fatigued by specific sounds and require reassignment to other tasks. The ASUS AI Solutions Team leverages the fact that 'human hearing acuity decreases over time, but AI does not,' thus completely solving the pain point of continually having to retrain inspection staff.

AI Identifies Problematic Motors, ASUS Helps Monitor Quality for Businesses

To address the aforementioned pain points, ASUS uses recorded sounds of properly functioning fans to create 'good fan sound waveforms' for AI to learn. The co-general manager of ASUS Smart IoT Business Group, Quan-De Zhang, stated: 'This is not about matching sounds, which would require exact replication. Instead, for fans, AI needs to learn what constitutes a good category and what is considered an anomaly.' Additionally, ASUS's technology facilitates the training and creation of AI models, enabling their own PE engineers (production engineers) to perform model-building tasks, keeping the models within the company as a core competitive strength. For each new fan model introduced into production, only 3 recordings of 30 seconds each of the approved fan sounds are required to complete the AI model, swiftly integrating it into production. Several domestic 3C fan manufacturers are progressively implementing the ASUS Smart Waveform Detection Solution, and during its integration, ASUS supports training and optimizes AI models, reaching an inspection accuracy equivalent to quality control inspectors. They are happy to report that AI inspection can: 1. work continuously without interruption, 2. produce consistent quality, and 3. establish a digital production record for the products, facilitating future product tracking and process analysis—a long-term goal for fan manufacturers.

AI Recognizes Digital Waveforms

In addition to familiar 3C fans, the ASUS AI Smart Waveform Solution's sound anomaly recognition applies to all 'moving parts' and can also assess the assembly quality of motors produced in factories. Once AI 'hears' an abnormal sound from a motor, it can identify defective motors. Apart from sound, the same artificial intelligence solution also has the capability to recognize anomalies in electric current, voltage, and vibration waveforms. In environments with significant background noise or complex sound collection, detection can flexibly switch to monitoring electric current, voltage, or vibration waveforms to ensure quality inspection of assembled products.

AI Recognizes Digital Waveforms, Preventive Maintenance for Equipment

AI can also 'listen' to detect abnormalities in plant equipment motors, determining when motors need maintenance or replacement. Typically, maintenance checks on motors are carried out on a scheduled basis through inspections. For industries like steel or chemicals, where continuous production is crucial, any motor failure can cause significant material losses, massively outweighing the cost of the motor itself. Although larger motors are not readily available and unexpected downtime can extend for days or weeks resulting in substantial losses, many businesses use scheduled maintenance to replace motors earlier than necessary, opting for high costs over wasting entire production lines of materials or experiencing shutdowns. With ASUS's Smart Waveform Anomaly Detection Solution, all operating motors within a plant are monitored for anomalies, setting alerts to facilitate timely maintenance or parts replacement, achieving the goal of preventive diagnosis and maintenance.

AI Detection is Convenient and Rapidly Deployable

The environments for production and quality inspection vary significantly, and AI application development is highly customized. If the ASUS Smart Solutions Team had to customize AI for every single client, dealing with up to 200-300 suppliers and a variety of dispersed products, it would consume vast resources and be inefficient. Thus, 'reducing the customization ratio and increasing standardization' is another goal of the ASUS Smart IoT Team. They aim to reduce the industry-wide AI application customization ratio from 60-70% to 20-30%. In the future, every new project that ASUS Smart IoT Solutions handles will only require a 20% customization adjustment, allowing for replication and scalable deployment of solutions.

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

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【解決方案】7毫秒內分離人聲 洞見未來科技協助聽損者「聽說更簡單」
Voice Separation in 7 Milliseconds: RelaJet's Future Technology Makes 'Hearing and Speaking Easier' for the Hearing Impaired

One rainy Thursday afternoon near Taipei Arena, the Taipei Experience Center of RelaJet was fully booked with appointments from people with hearing loss eager to try hearing aids made with a voice separation engine For the hearing impaired, having affordable, lightweight, and effective noise-reducing hearing aids is truly a blessing 'We hope to help users in need to hear the world's wonders again' This empathetic expectation by RelaJet's founder and CEO Po-Ju Chen, who is also hearing impaired, illustrates his understanding of the needs of the hearing impaired He hopes that RelaJet's unique voice amplification hearing aid technology will benefit many more people Affordable hearing aids benefit many with hearing loss Founded in 2018 by Po-Ju Chen and his brother Yu-Ren Chen, RelaJet developed a multi-voice separation engine paired with Qualcomm's Bluetooth audio platform, drastically reducing the price of imported hearing aids, typically costing 80,000-100,000 NT dollars, to just under 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anticipated to be exported to international markets in the latter half of this year Additionally, a hearing aid product combining Bluetooth functionality, set to launch in June this year, is sized like typical Bluetooth earphones, targeting visually conscious consumers with hearing loss Its small size and attractive wireless earphone design allow for phone calls, and if approved by the Ministry of Health and Welfare, eligible users can apply for government subsidies RelaJet to expand into overseas markets, using the USA as a beachhead An interesting question arises due to the pandemic everyone must wear masks which impedes lip-reading How does this affect those with hearing loss Yu-Ren Chen indicates that this situation highlights RelaJet's advantages As each person with hearing loss has different levels of hearing ability, hearing aids can only augment to an appropriate volume, assisting users to hear about 60-70 content, with the remainder relying on lip reading and gestures During the pandemic, as everyone wears masks, masks also muffle sounds, but RelaJet's voice separation engine can correct and strengthen the separation, making it easier for those with hearing loss to recognize voices Besides the Taiwan market, RelaJet's next stage will be expanding into overseas markets, expecting to obtain ISO 13485 medical device quality management system certification and US medical device approval in 2022 They plan to enter the US market, either under their own brand or through OEM arrangements Apart from the Taiwan market, RelaJet will also enter the US market in the next phase for hearing aids「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【解決方案】光禾感知科技智慧球場體驗 AR互動讓看球變得更加有趣
OSENSE Technology Qubby AI customer service helps enterprises comprehensively upgrade from customer service to knowledge management

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increase channels for contact with consumers However, this has created a greater workload for customer service personnel, who need to monitor even more channels to provide timely services OSENSE Technology's Qubby AI customer service helps enterprises integrate and manage multiple platforms, such as websites, LINE, Facebook Messenger, WhatsApp, and multimedia interactive machines, with a single account The service supports 29 languages and serves domestic and overseas customers 247, building good relationships by meeting customer needs and creating an endless stream of important and valuable customers Qubby AI customer service features Saves training time, standardized AI response, supports IMSNS, improves customer service efficiency, optimizes the service experience, and the web page is applicable everywhere Efficiently create enterprise-specific AI customer service in 3 steps, eliminating the need for design QA OSENSE Technology has condensed the establishment of Qubby AI customer 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【解決方案】瑕疵辨識率達百分百 耐銳利科技獲面板大廠青睞
Defect identification rate reaches 100%, Nairi Technology is favored by major panel manufacturers

On the machine tool production line, there are some slight differences in the first step of assembly Accumulated tolerances will cause the assembly work to be repeated, which is time-consuming and labor-intensive, resulting in shipment delays that will impact the company's reputation Narili Technology Company focuses on the field of smart manufacturing and provides various AI solutions It uses machine learning models to inherit the experience of old masters In the CNC processing machine assembly and casting process, it uses AI to analyze production line data, accurately adjust various data, and improve Production accuracy is 25 This AI production line data analysis system is called "Master 40" by Huang Changding, chairman of Naruili Technology It is the most evolved version of the master plus artificial intelligence It has been used in machine tool processing factories with remarkable results In addition, Nairi Technology used AI defect detection technology to participate in the 2021 AI Rookie Selection Competition of the Industrial Bureau of the Ministry of Economic Affairs, assisting AUO in advanced panel image defect detection, with an accuracy rate of 100, and won the award Assisted panel manufacturer AUO to solve problems with 100 accuracy in defect detectionHuang Changding further explained that during the production of general panels, edges and corners are There may be defects in the corners Although the defects are visible to the naked eye, AOI is often difficult to identify, causing the detection error rate to often exceed 30 Therefore, re-inspection must be carried out with manpower to improve the accuracy rate However, in response to the demand for a small number of diverse products and insufficient manpower, using AI detection is indeed a good method Nairui Technology, founded in 2018, has been able to win the favor of major panel manufacturers with its AI technology in just three years In fact, it has been honed in the field of CNC machine tools for a long time Tang Guowei, general manager of Narili Technology, pointed out that the top three CNC machine tool factories in Taiwan hope to introduce AI into the two production lines of assembly and casting Among them, on the assembly line, in order to maintain the accuracy of assembly, every part of the component is designed Tolerances are designed During assembly, each component is within the tolerance However, the cumulative tolerance still fails the final quality inspection and must be dismantled and reassembled This is not only time-consuming and labor-intensive, but also causes waste "After entering the production line, I realized that some masters have accumulated a lot of experience and are good at adjustment After his adjustment, the accuracy rate has improved a lot and the speed is faster" On the contrary, the new engineers did not Based on experience, it takes a long time to adjust and may not pass the quality inspection The yield rate of Master 40 system has increased significantly from 70 to 95Tang Guowei then said that the original size data set by Master during assembly All were recorded on paper After the information was written, it was stored in the warehouse and sealed No one studied the relationship between the dimensions Narili assists customers in designing the Fu 40 system Through the human-machine panel, the master can directly input the measured dimensions and related data during assembly After collecting data from different masters, AI algorithms are used to analyze the relationship between the data and create an AI model The AI model automatically notifies the operator what size to adjust to, and the quality inspection will definitely pass In this way, the yield rate will be improved It has increased significantly from 70 to more than 95 Narili Technology Company focuses on the field of smart manufacturing and provides various AI solutionsTang Guowei added, assembling the spindle of a CNC processing machine It took four hours In the first step, the machine made measurement errors, including vibration, temperature, speed, etc that were out of range It had to be dismantled and reinstalled, which took another four hours How to adjust after disassembly depends on the experience of the master At first, the master may have done the best assembly method based on experience, but the error rate was also 30, and the assembly took several days With the assistance of AI masters, the assembly time only takes half a day, and the yield rate reaches over 95, saving a lot of time and manpower "Use the AI model of machine learning to collect the experience of all the masters and provide it for AI learning The first step is digitalization, and the second step is knowledgeization This is the transformation of the enterprise "An important key", Huang Changding believes that Narili Technology is an important partner in the transformation of traditional manufacturing from automated production to digital transformation In addition, another industry that Naili Technology focuses on is the smart car dispatching system of the leading brand of elevator manufacturers The so-called car dispatch referring to the elevator car means that if there are more than two elevators, group management is required In the past, car dispatching was based on fixed rules If the elevator was closer to the requested car, that elevator would be automatically dispatched On the one hand, it did not take into account that dispatching a car if the elevator was called too many times might make other people wait longer The previous vehicle dispatching model did not take into account the usage characteristics of the building, resulting in a lot of waste For example, in an office building, there are peak hours in the morning, lunch break, and afternoon after work AI smart car dispatch can be flexibly adjusted according to off-peak and peak hours, increasing the efficiency of car dispatch, reducing waiting time, and reducing wasted electricity Introducing elevator smart dispatch to improve transportation efficiency and have environmental protection functionsHuang Changding added that just like the previous traffic lights at intersections, the system has already The number of seconds to stop and pass on highways, sub-trunks and small streets is programmed Smart traffic lights are now used to flexibly adjust waiting times to make road sections prone to congestion smoother Using AI to learn usage scenarios and introducing a smart dispatch system into elevators will improve transportation efficiency and make it more environmentally friendly In addition to introducing smart elevator dispatching, Nairili also introduced AI into the smart production and shipment scheduling system of elevator factories Elevator factories often cannot accurately estimate the customer's elevator delivery date For example, office buildings or stores must be completed to a certain extent before the elevator can be installed on the construction site If affected by unexpected factors such as delays in the customer's construction period, the elevator factory will often be idle or the schedule will be difficult to arrange Tang Guowei pointed out that generally those who understand the progress of client projects may be from business or engineering, but overall, the accuracy rate of shipments is only about 60, which means that 40 of them will not be shipped as scheduled Therefore, if the shipping schedule can be accurately estimated, the production line can be freed up for emergency orders or other product production needs The AI smart scheduling system will analyze past shipment data, about 20-30 parameters such as climate, distance between the factory and the construction site, and customer credit, and put them into the AI algorithm to accurately predict whether shipments can be made as scheduled goods Huang Changding also specifically stated that the machine learning of Naili Technology is not ordinary machine learning, but also incorporates various calculation methods such as traditional image processing technology and statistics Only by being very familiar with the domain knowledge can we make good products AI models are also where the company’s competitiveness lies He emphasized that the data that general SaaS platforms can process is very limited, and the accuracy rate has increased from 70 to 75 at most Naili’s strength lies in AI algorithms and machine learning, and it must be coupled with in-depth industry knowledge to produce output Good AI model Narili Technology started with the AI project, gradually deepened the technology, chose to start with the more difficult tasks, and accumulated rules of thumb It is expected to develop SaaS services this year 2022, based on customer needs starting point, gradually gaining a foothold and becoming an important partner in smart manufacturing The picture left shows the general manager of Naruili Technology Tang Guowei and Chairman Huang Changding right「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」