(M1430-06-38) Smart Compound Library Based on Machine Learning, Sensing Technology, and Programmable Logic Control

Purpose: Traditional compound storage systems face challenges such as risks of manual operation, insufficient space utilization, and material inventory issues. By implementing a smart compound library based on automation, these problems can be solved, improving the safety and accuracy of laboratory compound management.

Methods: In smart compound library, several major functional modules are typically involved, including compound storage and retrieval port, internal transfer and storage modules. Infrared sensing and intelligent scanning technologies are used for rapid identification, providing accurate information basis for subsequent processes. Image recognition and machine learning are employed to achieve precise positioning and adaptive grasping, while pressure sensing technology ensures the safety of grasped compounds. Three-axis gantries and movable double-sided storage cabinets are utilized for efficient compound transportation. Finally, scheduling algorithms optimize the overall workflow, and a management system enables human-machine interaction.

Results: By integrating machine learning, sensing technologies, programmable logic control, and intelligent scheduling technologies, fully automated warehousing operations and round-the-clock inventory checking have been achieved. The storage capacity in the same space has increased by 3 times, and it can handle 9 types of containers and 5 types of pallets, with a positioning accuracy within 0.03mm.

Conclusion: In this study, the efficient integration of business modules and automation technologies enhances the intelligent level of compound storage operations, significantly improving compound management.