The Exploration of AI-Empowered Industrial Product Quality and Safety Supervision Pathways in the Context of Big Data

Abstract

The widespread application of artificial intelligence (AI) technology has brought new solutions to the field of industrial product quality and safety supervision. This paper aims to delve into the effective pathways of AI-empowered industrial product quality and safety supervision in the context of big data, with the goal of enhancing supervisory efficiency. By comprehensively analyzing the existing problems and challenges in current industrial product quality and safety supervision work, this paper elaborates on the development status of big data and AI technologies and their potential application value in the supervisory field. It systematically investigates how to deeply integrate big data and AI technologies into every aspect of industrial product quality and safety supervision. By constructing a four-layer technical architecture for the supervision system - comprising perception, data, interaction, and application layers - this research promotes cross-departmental, multi-level governance system innovation. Building upon optimized resource allocation, it enhances the precision and foresight of industrial product quality and safety supervision work, facilitating overall improvement in regulatory practices.