This company, based in Shenzhen, Guangdong, focuses primarily on optoelectronics, specializing in the research and production of advanced fingerprint modules and CNC modules. It stands as one of China’s leading manufacturers of optoelectronic equipment. With its business expanding, the company faces challenges in enhancing production efficiency and optimizing internal logistics.
Previously, the factory relied on manual labor for handling, resulting in low efficiency and potential damage to delicate materials. To address this issue, the company decided to introduce delivery robots to optimize its logistics processes. They chose the Reeman Big Dog delivery Robot, which automatically delivery raw materials and finished products between the production line and the warehouse, as well as performs internal material sorting and distribution tasks.
The applications of delivery robots in this factory are diverse:
1. Raw Material Handling: The robots are configured to automatically delivery raw materials from the warehouse to the production line, reducing manual handling costs and time.
2. Finished Product delivery: After production, the robots move finished products from the production line to the inspection area, achieving automated logistics management.
3. Internal Material Distribution: Within the factory, robots are programmed to distribute components and finished products to different production floors as needed, increasing production efficiency and flexibility.
After adopting the Reeman Big Dog delivery Robot for over half a year, the factory’s efficiency has significantly improved by approximately 10%. Employee workload has decreased, and quality assurance has improved, all of which are evident successes. The relevant personnel have expressed plans to continue introducing more robots to expand the production line.
A technician at the factory also commented, “Since using the delivery robots, our work has become much easier. We now have more time to learn and engage in more complex tasks, such as troubleshooting machine faults and controlling the robots.”
