:::

【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」

Recommend Cases

這是一張圖片。 This is a picture.
AI Assists the Red Cross for Smarter Emergency Response

More Preparation Less Loss The Taiwan Food Bank Association, a non-profit organization, collects donations daily from wholesalers, retailers, manufacturers, and even kind-hearted individuals across Taiwan They also rescue consumable materials that are about to be discarded, properly allocate and deliver to households in need, aiding local underprivileged populations When natural disasters such as earthquakes, landslides, mudslides, typhoons, floods, and droughts occur in Taiwan, the food bank's resources can be immediately deployed for disaster relief This field verification unit is the Nantou County Red Cross AssociationOne of the food bank locations, hereinafter referred to as the Nantou Red CrossIs responsible for tasks like pre-disaster supplies preparation and disaster relief material distribution, helping the government bear the responsibility of disaster relief and aid In Taiwan, various natural disasters have characteristics of different duration and spatial coverage, wide or narrow With the normalization of extreme weather, the scale and number of disasters are gradually increasing and becoming harder to predict The required amount and type of materials differ by disaster, and they must address the lifestyles of the affected areas, rescue needs, traffic conditions, geographical restrictions, and other factors for varied material allocation, facing numerous challenges Typhoon Kanu severely damaged transportation in Nantou mountain areas Nantou County Red Cross planned the mountainous route Puli gt Fazhi Elementary School gt Qin'ai Village gt Aowanda to deliver supplies Disasters happen repeatedly We need to be prepared at all times Effective disaster preparedness can mitigate the impact, including swift response to material needs in affected areas, aid distribution, and even psychological support, providing added security for life and property of those in disaster zones Lack of Timeliness in Disaster Information To improve the living conditions and address the lack of supplies in remote areas, the Taiwan Food Bank Association has partnered with the Nantou Red Cross and has successively established food bank points in Nantou City, Puli, and Ren'aiLixing, Ruiyan, XinyiWangmei, Tongfu, Shuili, Lugu and Caotun among others9establish food bank locations, providing supplies worth a certain amount per household every month6001000in New Taiwan Dollars However, many challenges still need to be overcome during natural disasters For example, when typhoons, earthquakes, and landslides occur, the information source for disaster relief dispatch systems relies on post-disaster reports The time lag between reporting, response, and execution prevents timely adjustment and distribution of 'disaster relief' supplies based on the needs of affected areas, affecting rescue efficiency due to lack of timely information The 'preparedness' supplies of the Nantou Red Crosssuch as dry food, water, instant noodles, etc,are recorded manually in terms of stock, expiration dates, and distribution,When a disaster occurs, there is a chance that 'preparedness' supplies have expired and cannot become 'disaster relief' supplies It’s also possible that both conditions mentioned above occur simultaneously, leading to a need for more time to reassign 'preparedness' supplies into usable 'disaster relief' materials On the other hand, upon receiving information about shortages in disaster areas, the supplies donated by the public often grossly differ from the actual needs of the disaster zone, leading to an excess of supplies The Process of Material Operations Before and After a Natural Disaster AIAnticipating Natural Disasters Reinforcing the Accuracy of Preparedness Material Dispatch Application API Technology connects to compute the state of the climate, the intensity of disaster rescues, prioritizing the main tasks of the Nantou Red Cross and the needed areas of search and rescue Coordinated with the existing heavy rain and typhoon simulation disaster training of the Nantou Red Cross, a 'Natural Disaster Emergency Preparedness Material Dispatch and Supplement Decision System' is establishedreferred to as the Emergency Preparedness Material System。 In material management, inventory data along with immediate supply data are entered into the Emergency Preparedness Material System for comparison and analysis, helping the Nantou Red Cross quickly recognize materials like cookiesdry food, beverages, frozen food, toilet paper, etc, and determining whether they should be 'preparedness' materials or regularly distributed materials Adding to this, information forecasting understands the potential disaster conditions in remote areas, facilitating food delivery, addressing both front-end food wastage and backend practical needs When a natural disaster occurs, it enables faster response and decision-making, completing material deployment, hence increasing the speed of material operation transition20。 AI Emergency Preparedness Material System Helps Rapidly Adapt Material Distribution Through the field verification of the Nantou Red CrossAIthe system, material management, and related applications are promoted to more emergency response organizations in different areas, while continuously improving the alert functions within the Emergency Preparedness Material System, strengthening the technological foundation for alerts, enhancing prediction accuracySystem immediacy, and optimizing the data collection and analysis process Simultaneously, it can collaborate with government agencies, meteorological departments, or other rescue teams to discuss integrating more data sources, establishing a mechanism to share resources and data promptly, sharing information in real-time, helping more emergency response organizations enhance their disaster response abilities, seizing the golden rescue time 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-12-12」

【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」

【導入案例】化身大型AIOT科技遊樂場 海科館華麗轉身好吸睛
Transforming into a Large-Scale AIoT Technology Playground: The Spectacular Makeover of the National Museum of Marine Science & Technology

Taiwan is a maritime nation When you visit the Badozi Fishing Port or Tidal Park in Keelung, do you also explore the mysteries of the ocean world at the 48-hectare National Museum of Marine Science amp Technology To get more people closer to marine technology, Keelung's Marine Museum has introduced technological services, transforming the venue into a large technology playground that delights both children and adults, fully utilizing the 'learning through play' approach After a lengthy planning process, Northern Taiwan's largest marine science museum in Keelung opened in January 2014 The museum focuses on marine education and technology, boasting Taiwan's largest IMAX 3D ocean theater The unique themes and modern viewing facilities should make it a well-known landmark in Keelung However, the original exhibition planning was static and highly specialized, lacking sufficient interaction with the public Visitors who have attended the museum also reported that the exhibits were limited and quite boring, leading to poor overall consumer experience ratings The top three dissatisfactions with the museum were weak connections to surrounding attractions, unengaging display content, and lack of exhibit material According to statistics from the Marine Museum, the ratio of local to visiting guests is approximately 64, with most foreign visitors coming from the north transportation is primarily by car and bus common types of visits include family, parent-child, and friends and the stay duration is generally 1 to 2 hours Upon deeper investigation, the top three visitor complaints were weak linkages to surrounding attractions, unengaging display content, and insufficient number of exhibits The museum analyzed potential reasons, including some displays being too specialized, making it difficult for the public to understand, and a lack of interactive elements, making the exhibition boring and the visit hurriedly brief Analysis of visitor profiles revealed that since half of the museum's visitors are locals, and accessing the museum is not so easy for out-of-towners who must travel by car or public transport, the design of the venue and exhibitions must incorporate more interactivity and intrigue to encourage locals to return and extend the duration of visitors' stays while using technological services to highlight the museum's unique features Through a recommendation from the Information Software Association, part of the Ministry of Economic Affairs' Industrial Bureau AI team, the Marine Museum commissioned Jugu Technology to resolve the issue of uninspiring venue attractions Preliminary interviews by Jugu Technology revealed that many visitors were attracted by the architectural design of the museum, notices posted on nearby walls, flags, or events being held the most interesting feature for visitors was the 3D ocean theater, indicating that content presented through audio-video and physical scenic methods was more engaging Seven major AI technologies lead to a boost in regional tourism at the Marine Museum Through the introduction of technology services, Jugu Technology designed the 48-hectare site with seven major services AI voice tours, treasure hunt puzzle games, AI exhibit interactive revitalization, AI space exhibition interactive experience, AI crowd control, Face AI interactive experience, and AI voice customer service system By utilizing AIoT and cloud technology, they made the exhibition more interesting, not only solving the issue of boring static viewings for children but also doubling the learning efficiency and dramatically improving public perception of the Marine Museum, thus increasing visitor intent and boosting regional tourism The National Museum of Marine Science and Technology introduced seven major technological application services including AI voice guide Jugu Technology aimed to improve the space optimization of the Marine Museum, using the special exhibition of coastal birds in northern Taiwan as a prototype, integrating 'face', 'limb', 'crowd' as three main axes to enhance functionality and assist in improving the museum's application of AI Practically, the Marine Museum and Jugu Technology selected the on-site special exhibits to avoid any installation of water and electricity works or pipelines in active exhibits, thereby maintaining the quality of the viewing experience Instead, they selected exhibits that were not yet open to introduce a series of technological services tailored to the unique characteristics of the exhibits In the coastal bird special exhibition inside the Marine Museum, initial construction discussions with the curators utilized Bella X1 for a welcoming interactive introduction at the exhibition entrance This was followed by an AI-powered smart guide in both Chinese and English using X1 for narration, coupled with a fun treasure hunting stamp-collecting activity - APP X1, allowing visitors to participate in challenges Subsequently, bird species within the bird exhibition were brought to life interactively using X1, and AR scenarios X1 were introduced into the exhibition space to add elements of fun and entertainment Finally, Face AI was used to interactively test facial expressions and score smiles The gorgeously transformed Marine Museum will become the best travel destination for families with children ImageMarine Museum FB Page The AIoT services introduced by the Marine Museum could be extended to various exhibition-type museums and even static art galleries in the future, tailored to the unique characteristics of different venues They could also be promoted through government projects and related plans, aiding in rural revitalization, making visits more than just sightseeing in rural areas, and breaking free from stereotypes associated with different venues The applications of these services are broad「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」