Data-driven smart manufacturing

By Fei Tao, Qinglin Qi, Ang Liu, Andrew Kusiak. Journal of manufacturing systems, 2018

1,511 citations recorded by the source corpus.

Abstract The advances in the internet technology, internet of things, cloud computing, big data, and artificial intelligence have profoundly impacted manufacturing. The volume of data collected in manufacturing is growing. Big data offers a tremendous opportunity in the transformation of today’s manufacturing paradigm to smart manufacturing. Big data empowers companies to adopt data-driven strategies to become more competitive. In this paper, the role of big data in supporting smart manufacturing is discussed. A historical perspective to data lifecycle in manufacturing is overviewed. The big data perspective is supported by a conceptual framework proposed in the paper. Typical application scenarios of the proposed framework are outlined.

View Paper: https://www.semanticscholar.org/paper/624cd8b4dac3b11e0ed97729582c1324c302b0be

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Citations in the corpus

Industry 4.0: a supply chain innovation perspective (2020, background): “Consequently, these solutions aim at avoiding or quickly resolving process defects and equipment failure (see Tao et al. 2018) or at fine-tuning operating parameters to improve process performance.”
The internet of things for smart manufacturing: A review (2019, background): “However, the manufacturing industry is not well prepared for changes in the quest for data-driven knowledge (Kusiak, 2017; Tao et al. , 2018) Big data analytics provide efficient and effective methods and tools to handle large-scale IoT data for information processing and manufacturing process…”
The Internet of Things, Fog and Cloud Continuum: Integration and Challenges (2018, background): “In relation to speciﬁc issues of increasing research interest one can highlight the body of work on security [160, 161], networking and communication [162], as well as data management [163, 164, 165, 166, 167].”
Machine learning applied in production planning and control: a state-of-the-art in the era of industry 4.0 (2020, methodology): “(Kusiak 2017; Tao et al. 2018; Wang et al. 2018a) provided a literature analysis of data-driven smart manufacturing, citing representative references.”
A state-of-the-art survey of Digital Twin: techniques, engineering product lifecycle management and business innovation perspectives (2019, background): “…physical entity in the real world and can simulate its physical counterpart’s characteristics, behavior, life and performance in a timely fashion” Qi and Tao (2018) “Virtual models of physical objects are created in a digital way to simulate their behaviors in real-world environments” Xu et…”
Digital Twins and Cyber–Physical Systems toward Smart Manufacturing and Industry 4.0: Correlation and Comparison (2019, background): “The term smart manufacturing refers to a future state of manufacturing, in which real-time transmission and analysis of data from across the product life-cycle, along with model-based simulation and optimization, create intelligence to yield positive impacts on all aspects of manufacturing [7,8].”