复杂数据驱动下的质量检测、监测与运维技术研究综述

doi:10.16381/j.cnki.issn1003-207x.2024.1767

Abstract

Abstract:

In the field of manufacturing， quality management plays a critical role in enhancing companies' core competitiveness. Traditional approaches to quality management have rapidly evolved， transitioning from an emphasis on quality inspection to quality monitoring， and ultimately to full life-cycle quality management. However， with the rapid development of the global Internet in the 21st century， "smart+" technologies， characterized by intelligence and automation， have ushered in a new era of quality management techniques. Consequently， data has emerged as the cornerstone of modern quality management across every stage of the product life cycle. Data manifests in diverse forms， including text， numeric， images， video， and other formats. This diversity not only promotes the continuous innovation and data collection methods， but also imposes higher demands on the theoretical depth of data analysis and the applicability of analytical models. Complex data characteristics， such as data imbalance and multi-source heterogeneity， pose significant challenges to the quality management technologies. In this context， it focuses on the process of manufacturing， with a focus on quality inspection， monitoring， and operations and maintenance （O&M）. It summarizes the cutting-edge technologies that address complex data in quality management and provides insights into prospective research directions in this field.

Key words: complex data, quality management, quality inspection, quality monitoring, operation and maintenance management

CLC Number:

F253.3

Yuanyuan Gao,Xiandong Hong,Baoping Tao, et al. Review of Quality Detection, Monitoring, Operation and Maintenance Technology Driven by Complex Data[J]. Chinese Journal of Management Science, 2026, 34(2): 41-55.

Figures/Tables 1

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Review of Quality Detection, Monitoring, Operation and Maintenance Technology Driven by Complex Data

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