基于计算机和大数据技术的制造企业质量控制

Yu Du
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引用次数: 0

摘要

传统制造业正面临着大数据的冲击,产品研发、工艺设计、质量管理、生产经营等各个环节都迫切期待着工业背景下应对大数据挑战的创新方法的诞生。虽然传统制造企业已经初步建立了质量管理信息系统,但现有的质量管理系统仍存在诸多问题和局限性,无法满足制造企业的运营需求。本文选择制造企业的质量管理为研究对象,利用计算机、互联网、大数据、云计算等先进技术,构建了制造企业质量控制的数据系统模型。本文通过建立质量监控模型,优化质量数据处理流程,构建智能质量监管平台,建立制造企业质量报警规则。如果质量监测指标的实际值与预测值之间的偏差映射在[0,1]之间,质量监测系统就能生成异常值概率分值。本研究将传统的人工质量管理转变为 "互联网+质量数据 "的管理模式,以实现制造企业质量管理的信息化、数字化和智能化。这种综合研究方法将现代数字技术与质量管理的相关理论相结合,探索出了制造企业质量管理的优化方案,也为其他同类企业的信息化建设提供了可借鉴的经验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quality control of manufacturing enterprises based on computer and big data technology

The traditional manufacturing industry is facing the impact of Big Data, and all aspects of product research and development, process design, quality management, production and operation are urgently looking forward to the birth of innovative methods to cope with the challenges of big data in the industrial background. Although traditional manufacturing enterprises have initially established quality control information system, there are still many problems and limitations in the existing quality control system, which cannot meet the operation needs of manufacturing enterprises. This paper chooses the quality management of manufacturing enterprises as the research object, and uses advanced technologies such as computer, internet, big data and cloud computing to build a data system model of quality control of manufacturing enterprises. this paper optimizes the quality data processing process by establishing the quality monitoring model, and builds an intelligent quality supervision platform, and sets up the quality alarm rules for manufacturing enterprises. If the deviation between the actual value and the predicted value of the quality monitoring index is mapped between [0,1], the quality monitoring system can generate an outlier probability score. In this study, the traditional manual quality management is transformed into the management mode of the “internet + quality data” in order to realize the information, digital and intelligent quality management of manufacturing enterprises. This comprehensive research method combines modern digital technology and relevant theories of quality management to explore the optimization scheme of quality management of manufacturing enterprises, and also provides reference experience for the information construction of other similar enterprises.

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