Vertical data continuity with lean edge analytics for industry 4.0 production

Industry 4.0 is characterized by the digitization and networking of machines and systems in production. The amount of data in production is increasing, providing information about processes and thus enables the autonomous monitoring, control and optimization of value creation processes. However, there have been several open challenges and current research questions identified. In particular, new solutions need to be scalable and high-performing to deal with the growing volumes of data close to real-time. The work at hand tackles these research gaps by presenting an approach to realize vertical data continuity by combining signal acquisition and simultaneous data evaluation in a decentralized system without the use of time-consuming external cloud solutions. The approach has been evaluated in laboratory as well as in industrial settings. (C) 2020 Elsevier B.V. All rights reserved.

Automated summary

Industry 4.0 is characterized by the digitization and networking of machines and systems in production, allowing for autonomous monitoring, control, and optimization of value creation processes. However, challenges remain in developing scalable and high-performing solutions to handle the increasing volumes of real-time data. This study presents an approach to address these challenges by achieving vertical data continuity through decentralized signal acquisition and simultaneous data evaluation, without reliance on time-consuming external cloud solutions.