Journal
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
Volume 67, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.rcim.2020.102043
Keywords
Fog computing; Collaborative design; Manufacturing platform; Machine learning; Data integration; Blockchain technology
Funding
- National Natural Science Foundation of China [51405089]
- Science and Technology Planning Project of Guangdong Province [2015B010131008, 2015B090921007]
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Successful global manufacturing enterprises require great collaboration among designers, manufacturers, and customers, while achieving trustable collaboration and efficiently utilizing customer views remains a challenge.
Overview of current manufacturing enterprises show that successful global manufacturing enterprise has great collaboration among designer, manufacturer, and customer, which effect on reducing production life cycle and improving customer satisfaction. Recently, several past and ongoing research projects have conducted to enable the collaborative platform to develop effective collaboration with the manufacturing section, design section, and customer views. However, trustable collaboration and how to utilize customer views efficiently is still a challenge. Therefore, this research proposed a blockchain-enabled fog computing-based collaborative design and manufacturing platform to develop triple communication and cooperation among the manufacturing section, design section, and customers in a trustable environment. In the proposed platform, the machine-learning method is used for clustering and categorizing customer-views, and fog computing-based integration between subsystems via blockchain technology is proposed to improve the data integrity and security problem. The proposed platform explained based on key technology, data integrity, key requirement, and illustrative case study. In this respect, we presented the design and manufacturing of bicycles based on customer requests.
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