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Data analytics framework for Industry 4.0: enabling collaboration for added benefits
- Source :
- Lazarova-Molnar, S, Mohamed, N & Al-Jaroodi, J 2019, ' Data analytics framework for Industry 4.0: enabling collaboration for added benefits ', IET Collaborative Intelligent Manufacturing, vol. 1, no. 4, pp. 117-125 . https://doi.org/10.1049/iet-cim.2019.0012
- Publication Year :
- 2019
-
Abstract
- 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.
- Subjects :
- added benefits
Process management
data analytics framework
Industry 4.0
Computer science
media_common.quotation_subject
detailed data
data analysis
ComputerApplications_COMPUTERSINOTHERSYSTEMS
SMEs
production engineering computing
groupware
Industrial and Manufacturing Engineering
decision making
manufacturing enterprises
Artificial Intelligence
Manufacturing
industry processes
data-driven decision
Quality (business)
media_common
Collaborative software
manufacturing industries
business.industry
manufacturing sector
mutual benefits
decision-making processes
Computer Science Applications
small-to-medium enterprises
CDA framework
Hardware and Architecture
Information and Communications Technology
manufacturing facilities collaborate
Data analysis
Profitability index
collaborative data analytics
Small and medium-sized enterprises
business
enable collecting storing
share data
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Lazarova-Molnar, S, Mohamed, N & Al-Jaroodi, J 2019, ' Data analytics framework for Industry 4.0: enabling collaboration for added benefits ', IET Collaborative Intelligent Manufacturing, vol. 1, no. 4, pp. 117-125 . https://doi.org/10.1049/iet-cim.2019.0012
- Accession number :
- edsair.doi.dedup.....b661dc1c0ed24564bed507e0ff57c139
- Full Text :
- https://doi.org/10.1049/iet-cim.2019.0012