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Abstract The invention of new technologies has enabled the development of the manufacturing industry, from mechanical systems to highly automated assembly lines. The Industry 4.0 Concept requires self-sufficient factories, self-prediction, self-comparison, self-reconfiguration, and self-maintenance. Service innovation and industrial big data are receiving more attention from academia and industry. This article discusses managing manufacturing transformation services in the era of the Industrial Revolution 4.0 in the big data environment and the readiness of intelligent predictive informatics tools. This paper focuses on the basic concepts of Industry 4.0 and the current state of the manufacturing system. It also identifies research gaps between existing systems and Industry 4.0 requirements. The main contribution is the Industry 4.0 implementation structure, which consists of a multi-layered framework that can help people understand and achieve the requirements of Industry 4.0. The most cited members in this cluster are ten life cycles, eight construction industries, and eight learning systems. This study found that the number of publications on Big Data and Industry has increased overall in the last six years, with China being the most powerful country. It also found several other sub-topics related to Big Data and Industry, such as big data Analytics, Risk Management, and Industrial Revolution.
Younus et al. (Mon,) studied this question.