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【2020 Solutions】 How does Synnex make energy saving more efficient? The secret lies in the Smart Factory Cloud AI Manager

Synnex Technology, established just two years ago, self-positions as a Smart Factory Cloud AI Manager, focusing on the management of 'water, gas, oil, and electricity' to assist factories in becoming more energy-efficient and effective.

Founded at the end of 2017 from a division of the Institute for Information Industry, Synnex received substantial investments from major entities like Lite-On Technology, Yeong Yang Technology, Polaris Ventures, and the National Development Fund during its first funding round, showcasing strong market confidence in its future development.

Given that all factories and buildings utilize energy, there is a significant demand for energy conservation, revealing endless business opportunities. Energy includes four major manageable components: 'water, gas, oil, and electricity'. Synnex begins with these components, focusing on their respective equipment such as air compressors for 'gas' and distribution panels, transformers, and generators for 'electricity', before advancing to process equipment like motor operation.

'Water, gas, oil, and electricity' four types of energy management.

▲ 'Water, gas, oil, and electricity' four types of energy management.

At the present stage, Synnex offers two major solutions (products), one targeted at factories and the other at science parks or industrial parks. Thus, by the end of 2018, Synnex positioned itself as a '24-hour Factory and Park Cloud AI Manager', emphasizing its expertise in energy and equipment domains.

AI Manager targets the rigid needs of factory buildings

In major domestic factory areas, variable frequency motors are commonly used as facility equipment. Usually, for stability, regular maintenance is required to avoid production line disruptions due to a single piece of facility equipment, clearly a 'rigid demand'. Yet, current solution prices from equipment providers are high, while the effectiveness is poor, failing to truly meet the maintenance needs of the manufacturing industry.

For example, in lens grinding which uses motors, if a motor functions abnormally causing high vibrations, continued operation would shift the focus of the lenses, likely resulting in defective products. Through Synnex's motor diagnostic technology, effects caused by external equipment can be detected and yield rates improved, allowing production lines or facilities to operate more smoothly.

Setting for abnormal condition warnings is possible

▲ Setting for abnormal condition warnings is possible

In traditional factory settings, when motors malfunction causing the production line to report insufficient compressed air pressure, equipment replacement is initially prioritized, awaiting factory confirmation on the issue later. However, often the problem is minor yet incurs substantial replacement costs. With the introduction of AI models, real-time monitoring of critical parameters such as temperature and current is possible. Through parameter analysis, diagnostics are categorized into health assessment and operational analysis. Maintenance can address health issues, but if operations are not smooth, replacement becomes necessary. Once issues are clarified, appropriate decisions can be made accordingly.

Immediate or scheduled automatic diagnostics can determine motor health and potential issues

▲ Immediate or scheduled automatic diagnostics can determine motor health and potential issues

Hence, Synnex's core technology overcomes numerous barriers from communication modules, networking devices, cloud platforms to application services, and with an integrated software-hardware capability, allows traditional equipment to be commercialized as networked products within ten days. This immediate integration into In-Factory and In-Park cloud AI application services assists businesses in keeping up with the IoT era, achieving an integration of software and hardware, and developing more industry-appropriate application services.

「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

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【解決方案】2秒鐘完成結帳動作 Viscovery AI影像辨識助攻智慧零售
Complete checkout in 1 second, Viscovery AI image recognition assists smart retail

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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 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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 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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」