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Big Data Oriented Macro-Quality Index Based on Customer Satisfaction Index and PLS-SEM for Manufacturing Industry

机译:基于客户满意度指数和PLS-SEM的制造业大数据宏观质量指数

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The aim of this paper was to develop a novel macro-quality index driven by big quality data regarding the macro-quality management demands of manufacturing enterprises in Industry 4.0. Firstly, the connotation of big data of macro-quality management in manufacturing industry is expounded, which is the collection of the quality data in product lifecycle including the product quality data, process quality data and organizational ability data. Secondly, referring to the customer satisfaction index theory, a new big data oriented macro-quality index computation model based on the partial least square-structural equation modeling(PLS-SEM) theory is proposed, and the partial least square(PLS) is adopted to estimate the path parameters. Finally, a case study of macro-quality situation evaluation for the manufacturing industry of a city in China is presented. The final result shows that the proposed macro-quality index model is applicable and predictable.
机译:本文的目的是开发一种新的宏观质量指数,该指数由大质量数据驱动,涉及工业4.0中制造企业的宏观质量管理需求。首先,阐述了制造业宏观质量管理大数据的内涵,即收集产品生命周期中的质量数据,包括产品质量数据,过程质量数据和组织能力数据。其次,参考顾客满意度指数理论,提出了一种基于偏最小二乘结构方程模型(PLS-SEM)理论的面向大数据的宏观质量指数计算模型,并采用偏最小二乘(PLS)模型。估计路径参数。最后,以中国某城市制造业宏观质量状况评估为例。最终结果表明,所提出的宏观质量指标模型是适用和可预测的。

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