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Welding RobotIndustrial Welding RobotWelding Machine Robot for Metal WorkpieceCollaborative Welding RobotWelding Cobot
Taiyuan Jin Tai Technology Co,.Ltd
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Product Description Collaborative Welding Robots: Empowering Skill Upgrade and Job Transformation in Manufacturing WeldingIn the manufacturing industry, the welding sector is facing a labor crisis of dual dimensions: on one hand, the skills of many manual welders are stuck in traditional processes, unable to keep up with the demands of advanced materials (such as titanium alloys and high-strength steel) and intelligent equipment; on the other hand, the tedious, repetitive, and high-risk nature of traditional welding jobs makes it difficult to attract young talent, leading to an aging workforce. For a long time, enterprises have been caught in a dilemma: if they stick to manual welding, they cannot meet the technical requirements of modern production; if they adopt traditional robotic welding automation, they may face conflicts such as worker layoffs and skill mismatch. However, the collaborative welding robot (or welding cobot) has broken this deadlock, redefining human-robot collaboration welding to turn "replacing humans" into "empowering humans". It not only helps existing welders upgrade their skills but also creates a new generation of high-value welding-related jobs, injecting vitality into the labor ecology of the welding industry.The collaborative welding robot's user-friendly operation mode has become a "skill ladder" for traditional welders to move towards intelligent operation. Unlike traditional industrial robots that require professional programming knowledge (such as mastering code languages like C++), welding cobots adopt intuitive teaching methods-welders can guide the robot to complete the welding path by hand, and the robot will automatically record parameters such as speed and angle. This means that welders with rich manual welding experience can transform into "cobot operators" in a short time without starting from scratch to learn complex professional knowledge. In human-robot collaboration welding scenarios, traditional welders can give full play to their accumulated experience: they can judge whether the welding parameters need to be adjusted according to the material characteristics and part structure, and intervene in real time when the robot encounters abnormal situations (such as unstable arc). For example, a 52-year-old welder with 30 years of experience in a heavy machinery factory used to only master manual arc welding skills and was once worried about being eliminated by the intelligent transformation of the factory. After receiving a one-week training on collaborative welding robots, he successfully mastered the operation of the robot and even summarized a set of parameter adjustment methods for welding thick steel plates based on his own experience, which was promoted in the factory. Today, he has become a "cobot welding technician" with a salary increase of 30%, and his sense of professional achievement has been significantly improved.The Cobot Welding System further promotes the skill upgrading of workers by integrating a variety of intelligent tools and building a "learning-oriented" work environment. A complete Cobot Welding System is not only a production tool but also a "mobile training platform". It is equipped with a built-in skill training module: workers can use the simulation mode of the system to practice the welding operation of complex parts without consuming real materials, and the system will give real-time feedback on the operation (such as whether the welding path is accurate and whether the parameters are appropriate). Compared with the traditional "master-apprentice" training mode, this method not only shortens the training cycle by 60% but also ensures the standardization of skills. In addition, the system's cloud knowledge base stores a large number of welding process documents and case studies (including solutions for welding different materials and handling common defects), and workers can access and learn at any time during work. A small and medium-sized metal processing enterprise in Jiangsu Province has applied this function to train 15 new employees. In just one month, these new employees can independently operate the Cobot Welding System to complete the welding of standard parts, while in the past, it took at least three months to train a qualified manual welder. The system also supports remote expert guidance-when workers encounter technical problems that are difficult to solve, they can invite experts from the system supplier to conduct online guidance through the video call function of the system, breaking the geographical limitation of skill learning.For large-scale manufacturing enterprises, the Industrial welding cobot has spawned a series of new high-value jobs, promoting the overall transformation of the welding post structure. In factories equipped with Industrial welding cobots, the traditional single "manual welder" position has evolved into multiple professional positions such as "cobot operation and maintenance engineer", "welding process optimizer", and "quality data analyst". Among them, "cobot operation and maintenance engineers" are responsible for the daily operation, regular maintenance, and simple fault repair of Industrial welding cobots; "welding process optimizers" use the data collected by the robot to analyze and optimize the welding process (such as adjusting parameters to improve efficiency and reduce defects); "quality data analysts" mine the quality rules hidden in the welding data to provide support for the factory's quality improvement. These new positions not only require higher skills but also offer higher salaries and broader development prospects. For example, an automotive manufacturing plant in Guangdong Province has set up 20 "welding process optimizer" positions after introducing 50 Industrial welding cobots. These positions are mainly held by outstanding manual welders who have been trained. They use the data analysis function of the Industrial welding cobots to optimize the welding process of the car body, reducing the welding time per car by 15 seconds and the defect rate by 40%. These workers have not only realized the transformation from "skilled workers" to "technical talents" but also become the core force of the factory's technological innovation.The Collaborative Welding Cell integrates the welding robotics system with multiple functional units, creating a "multi-skilled" job environment and promoting the comprehensive development of workers' abilities. In a Collaborative Welding Cell, workers are no longer limited to a single task (such as only responsible for welding). Instead, they need to master multiple skills such as part loading and unloading, robot programming, quality inspection, and simple equipment maintenance. This "multi-skilled" requirement not only makes the work content more diverse and interesting (avoiding the boredom caused by long-term repetitive work) but also improves the comprehensive quality of workers. For example, in the Collaborative Welding Cell of a construction machinery manufacturer, each worker is proficient in three skills: first, operating the collaborative welding robot to complete the welding task; second, using the laser detector in the cell to conduct preliminary quality inspection of the weld; third, replacing the wearing parts of the robot (such as welding tips and nozzles). This multi-skilled training not only makes the workers more competitive in the job market but also improves the flexibility of the factory's labor allocation-when a worker is absent, other workers can quickly take over his work, ensuring the smooth progress of production.Advances in welding automation technology have provided a solid technical foundation for the skill upgrading and job transformation brought by collaborative welding robots. The application of artificial intelligence technology enables the robot to automatically identify the skill level of workers and push targeted learning content-for example, for workers who are not proficient in programming, the robot will recommend basic programming courses; for workers who have mastered the basic operation, it will push advanced content such as process optimization. The development of digital twin technology allows workers to conduct virtual debugging and process simulation of the welding robotics system in a virtual environment, which not only reduces the risk of equipment damage caused by misoperation but also helps workers deeply understand the working principle of the system. These technological advancements have made the skill upgrading of workers more efficient and targeted, and also made the new jobs spawned by collaborative welding robots more technically connotative.As a core component of automated welding solutions, collaborative welding robots are not only changing the way of welding production but also reshaping the labor value system of the welding industry. They have turned the "labor substitution" brought by traditional automation into "labor upgrading", making workers an important part of the intelligent production system rather than being excluded by it. For enterprises, this means having a more skilled and stable workforce; for workers, it means getting rid of low-value repetitive labor and moving towards a more respected and promising career path; for the entire welding industry, it means solving the problems of talent shortage and skill aging and achieving sustainable development.In conclusion, collaborative welding robots are the key force driving the skill upgrading and job transformation of the manufacturing welding industry. Through human-robot collaboration welding, they help traditional welders realize the leap from "manual operation" to "intelligent collaboration"; via the Cobot Welding System, they build a convenient and efficient skill learning platform for workers; with the Industrial welding cobot, they create a batch of high-value technical positions; in the Collaborative Welding Cell, they promote the development of workers' multi-skills; and relying on welding automation technology, they provide continuous power for workers' skill growth. In the wave of intelligent manufacturing, collaborative welding robots are not only tools for improving production efficiency but also partners for workers' career development. The future of the welding industry will be a win-win situation where humans and robots work together to create value, and collaborative welding robots are leading this beautiful future.The manufacture of this series of welding machines complies with the standard GB15579.1-2004 "Arc welding equipment part 1: welding power supply". The MIG-P series inverter pulse MIG/MAG arc welding machine has two welding modes: P-MIG and conventional MIG.The P-MIG welding mode can achieve carbon steel and stainless steel.For the welding of non-ferrous metals, the MIG welding mode can achieve low spatter welding of carbon steel and CO2 gas shielded welding.The performance characteristics are as follows:Fully digital control system to achieve precise control of the welding process and stable arc length.Fully digital wire feeding control system, accurate and stable wire feeding.The system has a built-in welding expert database and automatic intelligent parameter combination.Friendly operation interface, unified adjustment method, easy to master.Minimal welding spatter and beautiful weld formation.100 sets of welding programs can be stored to save operation time.The special four-step function is suitable for welding metals with good thermal conductivity, and the welding quality is perfect when starting and ending the arc.It has various interfaces for connecting with welding robots and welding machines (optional). PWM inverter technology can improve the reliability of the whole machine, high precision, energy saving and power saving.Precautions for use(1) The equipment number plate should be riveted at the specified position on the upper cover of the casing, otherwise the internal components will be damaged.(2) The connection between the welding cable and the welding machine output socket must be tight and reliable. Otherwise, the socket will burn out and cause instability during welding.(3) Avoid contact between the welding cable and metal objects on the ground to prevent short circuit of the welding machine output.(4) Avoid damage and disconnection of the welding cable and control cable.(5) Avoid deformation of the welding machine by impact and do not pile heavy objects on the welding machine.(6) Ensure smooth ventilation.(7) When used outdoors, the welding machine should be covered in rainy and snowy weather, but ventilation should not be hindered.(8) The maximum cooling water temperature should not exceed 30oC, and the minimum should not be frozen. The cooling water must be clean and free of impurities, otherwise it will block the cooling water circuit and burn the welding gun.2. Regular inspection and maintenance of the welding machine(1) Professional maintenance personnel should use compressed air to remove dust from the welding power supply once every 3 to 6 months, and pay attention to check whether there are loose fasteners in the machine.(2) Check the cable for damage, the adjustment knob for looseness, and the components on the panel for damage.(3) The conductive nozzle and wire feed wheel should be replaced in time, and the wire feed hose should be cleaned frequently.3. Welding machine faults and troubleshootingBefore repairing the welding machine, the following checks should be performed:(1) Whether the status and welding specification display on the front panel of the welding machine are correct, and whether the buttons and knobs are working properly.(2) Whether the line voltage of the three-phase power supply is within the range of 340V~420V; whether there is a phase loss.(3) Whether the connection of the welding machine power input cable is correct and reliable.(4) Whether the grounding wire connection of the welding machine is correct and reliable.(5) Whether the welding cable connection is correct and the contact is good.(6) Whether the gas circuit is good, and whether the gas regulator or proportioner is normal.
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