D-UG660 Digital practice

D-UG660 Referring to the construction experience of Lenovo’s intelligent factory, Torch Technology has adopted a series of innovative practices in intelligent transformation. After successfully running through the operation mode of intelligent manufacturing plant inside the company, it has transformed its accumulated rich experience into a set of external service capabilities.

Using the production method of the station, the AMR robot realizes the automatic flow of materials. Each CELL production unit focuses on a single task, and material flow between cells does not rely on traditional assembly lines or fixed-path automated guided vehicles (AGVs). This flow is completed by Torch’s self-developed robotic system, thus achieving a fully automated process from physical movement to loading and unloading. In the production process, the robot decides when to trigger the flow of materials based on the results of the calculation of the system, for example, processing a certain number of products after a single shipment. In addition, the robotic system is equipped with automatic rollers and racks for automatic loading and unloading of materials. These robots not only play a role in the production process, but also provide support during the component testing phase. During testing, any nonconforming material is identified by the system and prevented from entering the subsequent process, instead being sent directly to the exception processing site.

Through the PMC (Planning Material Control) system, the production planning and mD-UG660 aterial supply of the factory are accurately controlled. After receiving an order, the PMC system automatically plans the parts needed, generates the purchase order, estimates the arrival time, and feeds the information back to the backend system. Actions’ robot control system operates according to the material flow plan provided by the PMC system to ensure that raw materials, middleware, and semi-finished products are transferred to the corresponding stations according to the established plan, and the final assembly is completed. This transformational practice not only improves production efficiency, but also reduces material backlog, ensuring production flexibility and response speed.

Digital effectiveness

With its rich experience in the construction of intelligent production lines, Actions Technology has developed the ability to provide customers with intelligent transformation services, which can effectively help customers reduce costs and improve efficiency. The specific results are: first, human resources optimization. In a traditional production line, 30 to 40 employees are required for material transfer, station transfer, and loading and unloading. Through the implementation of fully automated processes, these links can realize the complete replacement of human resources and achieve automated production with zero personnel input. Second, production and management standardization. The introduction of robotics has facilitated the standardization of production processes and management, significantly reducing the professional reD-UG660 quirements for senior management positions, thereby reducing management costs and reducing the reliance on the professional skills of managers. Third, improve production quality and efficiency. Through detailed records of work results, factories can perform more accurate quality control, improve product quality, and lay a solid data foundation for continuous iteration and optimization of quality control. Fourth, reduce operating costs. In terms of cost savings, Actions’ intelligent transformation solutions can save more than 30% of customers’ costs. For example, in the logistics and warehousing industry in Japan, the cost of building and operating a 10,000 square meter warehouse with traditional methods is about 50 million yen, and the cost can be significantly reduced to 30 million yen after the adoption of Actions Technology AMR automation solutions, reducing the cost by about half, significantly reducing the construction and operating costs.

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