Service Innovation and Smart Analytics for Industry 4.0 and Big Data Environment | Zendy

Jay Lee | Zendy; Hung-An Kao | Zendy; Shanhu Yang | Zendy

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Service Innovation and Smart Analytics for Industry 4.0 and Big Data Environment

Author(s) -

Jay Lee,

Hung-An Kao,

Shanhu Yang

Publication year - 2014

Publication title -

procedia cirp

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.683

H-Index - 65

ISSN - 2212-8271

DOI - 10.1016/j.procir.2014.02.001

Subject(s) - big data , industry 4.0 , analytics , service (business) , productivity , factory (object oriented programming) , manufacturing , data science , transparency (behavior) , smart manufacturing , computer science , manufacturing engineering , process management , knowledge management , business , engineering , marketing , computer security , data mining , macroeconomics , economics , programming language

Today, in an Industry 4.0 factory, machines are connected as a collaborative community. Such evolution requires the utilization of advance- prediction tools, so that data can be systematically processed into information to explain uncertainties, and thereby make more “informed” decisions. Cyber-Physical System-based manufacturing and service innovations are two inevitable trends and challenges for manufacturing industries. This paper addresses the trends of manufacturing service transformation in big data environment, as well as the readiness of smart predictive informatics tools to manage big data, thereby achieving transparency and productivity

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