Abstract
Information and communication technologies are permeating all aspects of industrial and manufacturing systems, expediting the generation of large volumes of industrial data. This article surveys the recent literature on data management as it applies to networked industrial environments and identifies several open research challenges for the future. As a first step, we extract important data properties (volume, variety, traffic, criticality) and identify the corresponding data enabling technologies of diverse fundamental industrial use cases, based on practical applications. Secondly, we provide a detailed outline of recent industrial architectural designs with respect to their data management philosophy (data presence, data coordination, data computation) and the extent of their distributiveness. Then, we conduct a holistic survey of the recent literature from which we derive a taxonomy of the latest advances on industrial data enabling technologies and data centric services, spanning all the way from the field level deep in the physical deployments, up to the cloud and applications level. Finally, motivated by the rich conclusions of this critical analysis, we identify interesting open challenges for future research. The concepts presented in this article thematically cover the largest part of the industrial automation pyramid layers. Our approach is multidisciplinary, as the selected publications were drawn from two fields; the communications, networking and computation field as well as the industrial, manufacturing and automation field. The article can help the readers to deeply understand how data management is currently applied in networked industrial environments, and select interesting open research opportunities to pursue.
Highlights
The manufacturing industry needs to lead innovations to face the global competitive pressures in the advent of intelligent manufacturing across the broad range of manufacturing sectors [1]
The fourth industrial revolution, or Industry 4.0 (I4.0), which is being realized in the recent and years, is expected to deeply change the future manufacturing and production processes, and to lead to smart factories and networked industrial environments that will benefit from its main design principles: interoperability, virtualization, decentralization, distributed control and communication, real-time capability, service orientation, quick and easy maintenance, low cost, and modularity [2]
Reference [35] reviews the scheduling mechanisms for 802.15.4-Time Slotted Channel Hopping (TSCH) and slow channel hopping MAC in low power industrial wireless networks. It categorizes the numerous existing solutions according to their objectives and approaches and identifies some open challenges, expected to attract much attention over the few years. All those studies provide an interesting glimpse into the standardization domain for industrial networked environments, but, naturally, their focus is highly specific and is very different from the holistic approach focusing on data management which is presented in our survey
Summary
The manufacturing industry needs to lead innovations to face the global competitive pressures in the advent of intelligent manufacturing across the broad range of manufacturing sectors [1]. In the bottom of the pyramid are the production process and field network (sensing and actuation) layers (green and purple), which typically consist of assembly lines, robots, IIoT devices, sensors and actuators At those two layers, the main requirements on data communication is real-time behavior, low latency and low jitter for control applications. On top of the presented technological enablers, in order to implement higher layers than the control layer of the industrial automation pyramid, groundbreaking services will further boost the I4.0 vision Those services correspond to layers from supervision and manufacturing execution to enterprise resource planning and are marked with blue and black colors, at the right side of Fig. 2.
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