Technological Innovations and Intelligent Laboratory Development in Refining and Chemical Enterprises: A Systematic Review and Future Directions

Abstract

Amid the accelerating wave of digital transformation sweeping the global energy sector, laboratories in refining and chemical enterprises are undergoing a paradigm shift—from conventional manual operations toward intelligent, automated management systems. This study systematically investigates the construction pathways and technical architectures underlying intelligent laboratory systems within the petrochemical industry, with particular emphasis on how frontier technologies—including large-scale AI models, robotics, and the Internet of Things—are reshaping operational modalities. By integrating real-time data acquisition, mobile applications, intelligent analytics, and automated instrumentation, the proposed intelligent laboratory framework yields substantial operational improvements: a 40% increase in detection efficiency, 99.8% data accuracy, and an 80% acceleration in decision response time. Through in-depth analysis of benchmark implementations at Tianjin Petrochemical, Guangdong Petrochemical, and Fushun Petrochemical, this paper identifies key technological breakthroughs—namely the cloud-edge-end collaborative architecture, multimodal data fusion, and domain-specific knowledge graphs for quality control. It further addresses organizational challenges encountered during implementation and outlines prospective development trajectories. The findings offer a systematic and replicable reference framework for the intelligent transformation of laboratories in the refining and chemical sector.