The scientist’s investigation covers issues in Big data, Competitive advantage, Product lifecycle, Process management and Manufacturing engineering. He undertakes interdisciplinary study in the fields of Big data and Cleaner production through his research. His Cleaner production investigation overlaps with other disciplines such as Key, Sustainable development, Process development execution system, Analytics and Process.
His research in Competitive advantage intersects with topics in Sense and respond, Order and Knowledge management. His Product lifecycle research incorporates themes from Configuration management, Product management and Innovation management. Yang Liu has researched Product management in several fields, including System lifecycle, Application lifecycle management, Product design specification and Systems engineering.
Yang Liu mostly deals with Artificial intelligence, Competitive advantage, Process management, Pattern recognition and Energy consumption. The Artificial intelligence study combines topics in areas such as Iterative method, Machine learning and Filter, Computer vision. His work deals with themes such as Sense and respond, Resource allocation, Knowledge management, Industrial organization and Flexibility, which intersect with Competitive advantage.
The concepts of his Industrial organization study are interwoven with issues in Supply chain, Benchmarking and Quality, Operations management. Yang Liu has included themes like Product lifecycle and Process in his Process management study. His Product lifecycle study frequently intersects with other fields, such as Product management.
Yang Liu mainly focuses on Artificial intelligence, Cleaner production, Product-service system, Industrial engineering and Energy consumption. His work on Discriminative model and Deep learning is typically connected to Ideal and AKA as part of general Artificial intelligence study, connecting several disciplines of science. Among his Cleaner production studies, you can observe a synthesis of other disciplines of science such as Efficient energy use, Big data, Cloud computing, Ecotourism and Evolutionarily stable strategy.
His study in Big data is interdisciplinary in nature, drawing from both Product lifecycle and Engineering management. His study focuses on the intersection of Product-service system and fields such as Preventive maintenance with connections in the field of Risk analysis, Identification and Key. In Industrial engineering, Yang Liu works on issues like Scheduling, which are connected to Dynamic priority scheduling.
Control, Circular economy, Cleaner production, Cloud computing and Big data are his primary areas of study. His Control research integrates issues from State and Operating system. His study in Circular economy intersects with areas of studies such as Key, Fault, Risk analysis, Product-service system and Identification.
His study on Cleaner production is intertwined with other disciplines of science such as Manufacturing engineering, Efficient energy use, Factory, Demand response and Editorial team. The various areas that Yang Liu examines in his Cloud computing study include Product lifecycle, Smart manufacturing and Engineering management.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
A big data analytics architecture for cleaner manufacturing and maintenance processes of complex products
Yingfeng Zhang;Shan Ren;Yang Liu;Yang Liu;Shubin Si.
Journal of Cleaner Production (2017)
A comprehensive review of big data analytics throughout product lifecycle to support sustainable smart manufacturing: A framework, challenges and future research directions
Shan Ren;Yingfeng Zhang;Yang Liu;Yang Liu;Tomohiko Sakao.
A framework for Big Data driven product lifecycle management
Yingfeng Zhang;Shan Ren;Yang Liu;Yang Liu;Tomohiko Sakao.
Barriers to smart waste management for a circular economy in China
Abraham Zhang;Abraham Zhang;V.G. Venkatesh;Yang Liu;Yang Liu;Yang Liu;Ming Wan.
Sustainable competitive advantage in turbulent business environments
International Journal of Production Research (2013)
A novel multi-objective programming model of relief distribution for sustainable disaster supply chain in large-scale natural disasters
Cejun Cao;Cejun Cao;Congdong Li;Congdong Li;Qin Yang;Yang Liu;Yang Liu;Yang Liu.
Journal of Cleaner Production (2018)
Sustainability Assessment of Intelligent Manufacturing Supported by Digital Twin
Lianhui Li;Ting Qu;Yang Liu;Ray Y. Zhong.
A big data driven analytical framework for energy-intensive manufacturing industries
Yingfeng Zhang;Shuaiyin Ma;Haidong Yang;Jingxiang Lv.
Journal of Cleaner Production (2018)
Research on services encapsulation and virtualization access model of machine for cloud manufacturing
Yingfeng Zhang;Geng Zhang;Yang Liu;Di Hu.
Journal of Intelligent Manufacturing (2017)
SVM based multi-label learning with missing labels for image annotation
Yang Liu;Kaiwen Wen;Quanxue Gao;Xinbo Gao.
Pattern Recognition (2018)
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