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In the era of the fourth industrial revolution, dubbed as Industry 4.0, manufacturing resources will be digitized and integrated into a digital ecosystem of manufacturing network. Data has changed from by-product in manufacturing process to strategic resource which attracts much attention of enterprises. However, research which have been carried out on how to mine and utilize these data are very limited.
In this research, an integrated system for shop floor process planning by reusing and evaluating the manufacturing big data is proposed aiming to reuse the shop floor manufacturing knowledge. First, a digital library of shop floor manufacturing process commands which is extracted from STEP-NC code is introduced to set up the command code source foundation for the system. Second, an advanced machine learning algorithm is developed to seek for effective commands for different manufacturing operations. Moreover, the system takes a combination of the outcome from the algorithm in order to summarize a set of overall process plan synthetically. Finally, a whole process of a specific part is tested by using the integrated system which provides a performance boost to the manufacturing process of the part.
Mr Hanyu Wang is a postgraduate research student within Mechanical Engineering at the Kingston University.
Hanyu Wang has joined the University of Southampton in 2014 commencing his undergraduate studies in BEng Aeronautical and Aerospace Engineering in Southampton university.