Big Data Analytics for Physical Internet-based intelligent manufacturing shop floors

By Ray Y. Zhong, Chen Xu, Chao Chen, George Q. Huang. International Journal of Production Research, 2017

388 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Industrial and Manufacturing Engineering, Media Technology

View Paper: https://www.semanticscholar.org/paper/6d97dca6deb258c30381956e9af93b12bd5c6d03

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Citations in the corpus

Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic (2020, background): “The studies by Dubey et al. (2018), Gunasekaran et al. (2018), Ivanov and Dolgui (2019), and Zhong et al. (2017) elaborate on interrelations between lean, agile, and digital for increasingly data-driven market responsiveness.”
A critical investigation of Industry 4.0 in manufacturing: theoretical operationalisation framework (2018, background): “This can, consequently, provide novel opportunities in terms of efficiency improvements, cost savings and revenue growth (Bechtold et al. 2014; Zhong et al. 2015).”
Researchers' perspectives on Industry 4.0: multi-disciplinary analysis and opportunities for operations management (2020, background): “0 context have been shown for shop floor control (Zhong et al. 2017; Yang et al. 2019), scheduling (Ivanov et al.”
The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics (2018, background): “…seen in procurement processes, manufacturing shop ﬂ oors, promotion actions in the omnichannel model, routing optimisation, real-time traf ﬁ c operation monitoring and proactive safety management (Addo-Tenkorang and Helo 2016; Gunasekaran et al. 2016, 2017; Nguyen et al. 2017; Zhong et al. 2017).”
A comprehensive review of big data analytics throughout product lifecycle to support sustainable smart manufacturing: A framework, challenges and future research directions (2019, background): “Manufacturers are being flooded by huge amounts of data, since various sensors, electronic devices, and digital machines are used in production lines and shop-floors (Zhong et al., 2017).”
The Role of Big Data Analytics in Industrial Internet of Things (2019, methodology): “Performance analysis and exception diagnosis model have been proposed and tested using Petri nets and decision tree algorithms [47].”
Big Data for supply chain management in the service and manufacturing sectors: Challenges, opportunities, and future perspectives (2016, background): “Manufacturing sector is being flooded by a huge amount of data since various sensors, electronic devices, and digital machines are used in production lines, shop floors, and factories (Zhong et al., 2015).”
Defining a Digital Twin-based Cyber-Physical Production System for autonomous manufacturing in smart shop floors (2019, methodology): “…shop ﬂoor modelling for transparency, manufacturing data integration for sharing and Big Data analysis for production control (Kumar et al. 2016, Zhong et al. 2017, Yin et al. 2018), there are still some limitations or disadvantages to be dealt with: (1) Machine-oriented virtualisation and…”
Big data analytics in supply chain management between 2010 and 2016: Insights to industries (2018, background): “Therefore BDA can support manufacturer building intelligent shop floor logistics system (Zhong et al., 2015, 2017).”