Integrated Bar Stacking and Testing System for High-Volume Edge-Emitting Laser Manufacturing

Abstract

This article presents the development and validation of an AI-enhanced multi-functional workcell system designed to address critical challenges in semiconductor laser diode pre-assembly manufacturing operations. The proposed system integrates precision bar handling, electrical characterization, optical testing, and real-time database connectivity within a single modular platform to overcome limitations of conventional sequential processing approaches. The workcell employs a hierarchical modular architecture featuring six-degree-of-freedom robotic manipulation, reconfigurable test stations, adaptive tooling mechanisms, and distributed control systems that enable simultaneous processing operations across multiple laser bar configurations. Advanced Manufacturing Execution System integration utilizes OPC-UA communication protocols and machine learning algorithms for process optimization and predictive quality management. Comprehensive experimental validation demonstrates significant improvements in positioning accuracy, cycle time reduction, measurement precision, and operational flexibility compared to existing bar handling systems. The integrated approach incorporates auto-calibration algorithms, adaptive control mechanisms, and artificial intelligence techniques that enable autonomous decision-making while maintaining strict quality control standards, representing a substantial advancement in semiconductor manufacturing automation technology.