Open AccessData analytics framework for Industry 4.0: enabling collaboration for added benefits
Author(s) -
LazarovaMolnar Sanja,
Mohamed Nader,
AlJaroodi Jameela
Publication year - 2019
Publication title -
iet collaborative intelligent manufacturing
Language(s) - English
Resource type - Journals
ISSN - 2516-8398
DOI - 10.1049/iet-cim.2019.0012
Subject(s) - profitability index , analytics , computer science , manufacturing , data analysis , process management , key (lock) , quality (philosophy) , business , knowledge management , data science , data mining , marketing , philosophy , computer security , finance , epistemology
Industry 4.0 is a promising vision for advancing the manufacturing sector through the recent innovations in information and Communication Technologies that enable collecting, storing, and processing detailed and accurate data about industry processes. This data enables manufacturers for data‐driven decision making to significantly improve their operations and profitability. Most of the large manufacturing enterprises can benefit from this as they can collect more data that can be utilised to enhance their decision‐making processes. Small and medium enterprises (SMEs) have limited data and resources, thus reducing the possible gains. However, if SMEs and small manufacturing facilities collaborate and share data, which is then jointly analysed, feasibility and quality of their data analytics and decision‐making processes could be significantly enhanced. This study discusses collaborative data analytics (CDAs) in Industry 4.0, summarising findings into a novel CDA framework that can be used by manufacturing enterprises of any size and scale to enable and enhance the mutual benefits of CDAs and decision‐making processes. The CDA framework can enhance the key factors and performance metrics of manufacturing facilities such as reliability, availability, and efficiency. The study also provides a preliminary benefit analysis of utilising the proposed CDA framework for manufacturing SMEs.