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【2020 Application Example】 AI Smart Customer Service Maintenance Response System, solving customer machinery fault issues instantly through chatting!

A tool machine manufacturer that markets successfully both domestically and internationally, but also faces challenges?

A domestic tool machine manufacturer specializing in CNC wire cut machines, CNC EDM machines, and CNC fine hole EDM machines, uses its strong core capability in electromechanical development to deliver high-precision, high-quality products. It has successfully developed an aviation engine turbine ring wire cutting machine and specializes in designing and manufacturing super-large custom models, successfully marketing its products to over 30 countries worldwide.

Though capable of marketing high-quality products, the lack of standardized processes and methodologies for machine maintenance means that it often requires significant manpower and time to address machine failures, increasing maintenance costs...

No fast repair solutions, difficult personnel training, high maintenance time costs

While the tool machine manufacturer can sell high-precision machinery globally, encountering maintenance situations always consumes a lot of manpower and money. This is due to the lack of standardized troubleshooting processes for machine maintenance, mainly relying on the experience of maintenance technicians and the machine error codes. Not all faults can be diagnosed through codes. Technicians can only initially judge based on the error codes, then hypothesize the likely fault causes for further inspection and maintenance. There is also no standard way to record the repair methods, making it difficult to quickly troubleshoot similar issues in the future.

In addition to 'lack of standardized fault troubleshooting process', there are also issues of 'difficult personnel training' and 'high maintenance time costs'. Technicians need years of repair experience and must be familiar with mechanics, electronics, and mechanical engineering. If error codes are not available during repair, it requires considerable time to identify the problem with the machine, causing significant time and cost losses.

▲Traditional way of addressing issues through email

Implementing the 'AI Smart Customer Service Maintenance Response System' reduces costs for maintenance visits, shortens the duration of repairs, and simultaneously enhances the product's value.

Considering the pain points mentioned, the needs of the tool machine manufacturer are threefold: firstly, establishing a 'fault troubleshooting AI image recognition maintenance knowledge base system'. Then, collecting data on machine failures to establish a 'machine fault condition database'. Lastly, integrating AI image recognition and deep learning functions to analyze photos taken at the time of the machine's failure in order to identify the most closely related fault issues and troubleshooting methods.

This 'AI Smart Customer Service Maintenance Response System' predominantly uses 'supervised learning' as its primary AI technique. The 'AI model' part involves 'CNN' (Convolutional Neural Networks), which is used for image recognition and obtaining extensive training data on machine malfunctions and recommended maintenance methods for effective AI predictions. The 'data analysis' part uses 'DNN' (Deep Neural Networks) to acquire reference data related to fault conditions after training, providing answers that maintenance staff and clients desire for repairs, reducing the rate of maintenance visits and enhancing the product's added value. Additionally, 'AlexNet' is used as a preliminary development tool; its parameters can be set independently and executed automatically, ensuring that the AI model trained aligns closely with expected outcomes.

Currently, the tool machine manufacturer has around 10,000 graphic and text entries, predominantly 'image data'. The system uses images for fault identification and text to assist in the diagnosis of abnormalities. It employs '360-degree panoramic modeling' to archive graphic data and stores numerous image files internally. Additionally, it gathers relevant data such as electrical currents, voltages, water pressures, and flow rates via sensors, utilizing them for associated decision-making processes. The following pictorial representation shows the system service process:

AI Smart Response Customer Service System Service Process Chart

▲AI Smart Response Customer Service System Service Process Chart

This system gathers experiences from technical maintenance staff and information on machine faults to establish databases containing: machine fault conditions, machine fault images, maintenance actions, and completions of machines. It logs the comprehensive repair records, and leveraging AI image recognition and data analysis, it determines the most likely fault conditions. Through accumulated maintenance experience, the machine is enabled to autonomously learn and decide, offering the most suitable solutions to technicians or clients, thus shortening the training and repair time for technicians, reducing clients' downtime and costs, and increasing the machine's additional product value.

Promoting the 'AI Smart Customer Service Maintenance Response System' across various industries for greater economic impact!

This 'AI Smart Customer Service Maintenance Response System' initially sets up a maintenance knowledge base, then employs Chatbot technology to integrate smart customer service, allowing clients to interact directly via chat to quickly resolve basic machine faults. In the training of maintenance technicians, AI can also swiftly classify and inform of the likely fault causes and troubleshooting steps, thus lessening training and repair duration. By effectively solving issues like the lack of quick repair solutions, difficulty in training personnel, and high maintenance time costs, it is poised to expand its applications to other industries for more significant economic outcomes in the future.

AI Intelligent Reply Customer Service System - Smart Image Recognition Customer Service Illustration

▲AI Intelligent Reply Customer Service System - Smart Image Recognition Customer Service Illustration

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

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這是一張圖片。 This is a picture.
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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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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