Green energy is the future trend and will surely lead to huge business opportunities in the future Wind power has been one of the green energy sources that have attracted global attention in recent years It will become an important force in my country's renewable energy and help Taiwan's power generation reach the goal of 20 by 2025 to improve Taiwan's energy independence As the number and power of domestic wind turbines wind turbines increases year by year, it is particularly important to ensure that the power storage equipment achieves safe, long-term performance, is not easily attenuated during charging and discharging, and is sustainable, low-carbon and environmentally friendly At the same time, the wind turbine equipment itself Health inspection, maintenance and repair have also become the focus of wind farm operators In order to meet the needs of wind farm customers, the green energy business unit of Hua Mo Industry has launched long-lasting energy storage all-vanadium redox flow battery electrolyte and wind turbine AI predictive operation and maintenance, providing 100 safety, long-term efficiency and reducing customer initial manufacturing costs cost-effective power energy storage equipment, and through AI predictive operation and maintenance services to help customers reduce power generation costs by 10 and save up to 30 in maintenance and warranty costs Hua Molybdenum Industry was established in 1998 The industry started by refining vanadium, molybdenum and rare metal elements and other products, and used them in high-end steel, professional chemicals and specialty chemicals industries, and vanadium is more like a steel-making Vitamins can increase the effectiveness of steelmaking Among them, vanadium and molybdenum related products are one of the company's main projects The company sees that the all-vanadium redox flow battery, which is 100 vanadium-based, will be a very promising mainstream green energy technology in terms of long-term energy storage in the future, and before 2010 The government has actively invited legal entities such as the Industrial Research Institute to conduct research on related component materials in solid-state batteries and all-vanadium batteries In addition, the Ministry of Economic Affairs expects renewable energy to account for 20 of power generation in 2025 and reach 15GW Based on the above Considering this, Hua Molybdenum Industry decided to devote all its efforts to research and invest in the technological development of self-developed all-vanadium redox flow battery electrolyte in 2017, in order to accelerate the compliance rate of renewable energy in 2025 Hua Molybdenum pointed out that "renewable energy power is relatively unstable, and Taiwan itself lacks lithium resources In lithium battery manufacturing, almost 80-90 of battery cells must rely on foreign procurement, and there is a lack of 100 domestic self-sufficient energy storage Resources and technology "Similarly, how does Taiwan overcome the problem of having no natural vanadium resources To this end, Hua Molybdenum Industry uses original technology to use waste catalysts from petrochemical industries such as CNPC refineries or Taishuo petrochemical processes Up to 10 of the vanadium ion content can be used to extract high-value vanadium resources, thereby producing Taiwan's 100 self-made all-vanadium redox flow battery electrolyte without being affected by resources, effectively achieving resource recycling Since 2017, Hua Molybdenum Industrial has successfully created all-vanadium flow electrolyte technology, and has successfully passed product verification by the Industrial Research Institute, the Nuclear Research Institute and many international manufacturers Taiwan’s power storage energy target is to reach 15GW in 2025 Its power distribution includes 500MW in Taipower’s automatic frequency regulation system, 500MW in E-dReg and 500MW in existing or newly built solar power plants For example, electricity consumption is mainly between 4 pm and 10 pm, which is the peak period for people's daily electricity consumption For this reason, the Energy Administration specifically requires Taipower to strengthen the upgrade of energy storage equipment, which has also driven the market's interest in all-vanadium redox flow batteries Energy storage system equipment is in high demand In addition, Taiwan's current total power reserve construction and contribution has not yet reached 100MW, and the gap from the 2025 target of 15GW of power storage is still more than 15 times Using all-vanadium redox flow batteries to successfully create 100 safe, low-carbon, environmentally friendly and long-lasting energy storage system equipment Compared with the short-term power storage of lithium batteries, the biggest advantage of all-vanadium redox flow batteries is that it is globally recognized as a long-term power reserve It can store energy for a long time up to 12 hours, which means that if it is charged for 12 hours, It can release power for 12 hours Compared with the electricity measurement method of general energy storage systems, which is daily electricity consumption power in kilowatts x time in hours, for all-vanadium redox flow batteries, power and hours are different Special design, the power is also called a stack, which is composed of four materials metal, polymer mold, carbon felt and graphite plate, and the power consumption time is calculated based on the amount of electrolyte in cubes Therefore, when the power electric push x the amount of electrolyte the daily electricity consumption of our all-vanadium redox flow battery for energy storage The product features of the all-vanadium redox flow battery energy storage system equipment include four major features safety, long-term performance, not easy to decay during charging and discharging, and sustainable, low-carbon and environmentally friendly The quality of the all-vanadium flow battery is 100 safe Since the electric energy is stored in the vanadium-containing electrolyte, it can avoid any flammable accidents caused by a fully charged energy storage system In terms of battery life, compared to the short battery life of lithium batteries, all-vanadium redox flow batteries can have a battery life of more than 20-25 years through changes in price Regarding the charge and discharge performance of energy storage, unlike lithium batteries which have a certain number of charge and discharge times 5000-600 times, there is no limit to the number of charge and discharge times of all-vanadium redox flow batteries Regarding zero carbon emissions, which is highly valued globally, unlike lithium batteries which have recycling issues, the electrolyte of the all-vanadium redox flow battery can be used permanently The material components of the stack are environmentally friendly and fully recyclable to create a truly sustainable and low-cost Carbon-friendly energy storage system Onshore wind turbine AI prediction smart operation and maintenance allows customers to reduce power generation costs by 10 and save maintenance and warranty costs by up to 30 Hua Molybdenum Industry not only improves the long-term power storage efficiency of renewable energy customers through all-vanadium redox flow battery energy storage system equipment and helps customers reduce initial purchase costs, but also uses AI smart operation and maintenance empirical calculations for offshore and onshore wind turbines Field demonstrations were drawn on Taipower's onshore wind farm, and we actively accumulated our own technical experience and energy in AI predictive operation and maintenance With the support of the AI HUB project of the Industrial Bureau of the Ministry of Economic Affairs, the cooperation site will focus on the Phase I wind farm of Taipower Corporation and provide smart operation data of wind turbines for more than 6 months for analysis The AI predictive operation and maintenance system for onshore wind turbines uses machine learning The main technology provider comes from ONYX Insight, a subsidiary of British Petroleum BP The company uses AI Hub analysis software technology to analyze the wind turbines faced by Taipower Pain point analysis, including power generation loss of road-based wind turbines and damage prediction of key components of land-based wind turbines such as gearboxes, pitch bearings under abnormal vibration three-dimensional vibration frequency or abnormal temperature, etc output Through this implementation, it can effectively help Taipower reduce power generation costs by 10, increase asset value by 12, and save up to 30 in maintenance and warranty costs In the past three years, ONYX Insight has successfully predicted and operated more than 20,000 offshore or onshore wind turbines around the world, accumulating extremely high AI model accuracy It is believed that the international partnership established with ONYX Insight will effectively guide and accelerate the green energy division of Hua Molybdenum Industry in its goal and layout to become an independent technology service provider for wind turbine AI predictive operation and maintenance Works with partner ONYX insight to provide customers with an AI predictive operation and maintenance system, including wind turbine power generation loss and damage prediction of key wind turbine components Building a solid foundation for domestic wind turbine operation and maintenance, using Taiwan as a base to expand to Southeast Asian wind farms The market output value of offshore wind turbine AI predictive operation and maintenance in Taiwan will exceed NT30 billion in the future, and the energy storage market has an output value of more than 100 billion US dollars globally In the future company vision, Hua Molybdenum Industrial hopes to become An independent technical service provider for vanadium flow battery electrolyte and wind turbine AI predictive operation and maintenance The long-term goal is to establish a local supply chain of vanadium flow battery electrolytes around the world by accumulating abundant technology and performance capital to supply industry needs nearby 「Translated content is generated by ChatGPT and is for reference only Translation date：2024-05-19」

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 - Implementation in golf courses solves the problem of labor aging and shortage Chao-Cheng Chen further explained that the National Land Surveying and Mapping Center is a RTK service provider RTK provides the error reference map of the positioning point USRROBOT can access the positioning error value of a specific position through 4G Internet access The AI algorithm of USRROBOT reduces the general 10-20 m error of GPS to 2 cm After positioning, USRROBOT then uses six-axis accelerator positioning, gyroscopes, and wheel differential sensing devices for software and hardware integration Only by matching the wheel's movement pattern and the terrain can accurate mowing path planning be achieved The AI lawn mowing robot, which is 62 cm wide, 84 cm long, 46 cm high, and weighs only 25 kg, can set the mowing boundaries in the cloud It can avoid pools and sand pits through settings, using AI algorithms to automatically calculate the optimal path It is able to mow approximately 150 ping of grass in one hour The battery can be used continuously for more than 6 hours The battery life is currently the highest in the world In addition to general gardening companies, with the assistance of the AI project team of the Industrial Development Bureau, Ministry of Economic Affairs, USRROBOT's AI lawn mowing robot has been applied to golf course lawn mowing A well-known golf course located in Taiping District, Taichung City currently has a staff of 5 people who are responsible for the lawn, planting maintenance, and other landscape maintenance of the entire 30-hectare course However, the average age of staff is as high as 55 years old, and the golf course has been unable to recruit new staff members for a long time In view of the aging staff and the shortage of manpower, the golf course hopes to mitigate the impact with AI technology, and is therefore using AI multi-device collaborative mowing sensor technology, in hopes of reducing the burden of staff maintaining the golf course New challenges - 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

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」