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.
Highlights
The fourth Industrial Revolution or Industry 4.0 is the widely adopted term to refer to the phenomenon of instilling the latest information and communication technologies (ICTs) and corresponding infrastructures into automation and manufacturing processes [1]
Based on our findings related to the four Industry 4.0 data analytics areas where collaborative data analytics (CDAs) can be performed, as well as the different types and models for their implementations, presented in the previous sections, we developed a CDA framework
In the case of dynamic CDAs which will require more technology to be implemented such as cloud computing, fog computing and middleware [42], a local fog node can be used by each enterprise to function as a firewall that has the filtering and aggregation capabilities to control what to share as the data is streamed in real time
Summary
The fourth Industrial Revolution or Industry 4.0 is the widely adopted term to refer to the phenomenon of instilling the latest information and communication technologies (ICTs) and corresponding infrastructures into automation and manufacturing processes [1]. Through the emergence of Industry 4.0, future manufacturing systems are expected to become highly flexible, modular and much more efficient, producing intelligent products that control their own production processes [2] This anticipation will be facilitated by the availability of data and advancements in data analytics processes, which are considered to be vital to the development of the Industry 4.0. Predictive manufacturing implies that manufacturing systems possess technologies and intelligence to proactively implement mitigating solutions to prevent efficiency loss in manufacturing operations This includes predicting equipment performance, as well as faults and anomalies, and inferring future fault events and even diagnosing potential root causes of problems.
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