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

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.

I Introduction

In recent years, with the increasing competition in the market, governments in the world have realized that quality is more important than the velocity for the economic development. And macro-quality evaluation is needed for the government to understand the macro-quality situation, which can provide an effective and quantitative decision making tool for macro-quality management. Especially in the big data and Industry 4.0 era, lots of quality data from the product lifecycle can be collected and used to improve the accuracy and validity of the macro-quality cvaluation^{[1] [2]}.