With the introduction of the Internet of Things (IoT) and cyberphysical system (CPS) concepts in industrial application scenarios, industrial automation is undergoing a tremendous change. This is made possible in part by recent advances in technology that allow interconnection on a wider and more fine-grained scale. The purpose of this article is to review technological trends and the impact they may have on industrial communication. We will review the impact of IoT and CPSs on industrial automation from an industry 4.0 perspective, give a survey of the current state of work on Ethernet time-sensitive networking (TSN), and shed light on the role of fifth-generation (5G) telecom networks in automation. Moreover, we will point out the need for harmonization beyond networking.

The Future of Industrial Communication: Automation Networks in the Era of the Internet of Things and Industry 4.0

Industry 4.0 and the current status as well as future prospects on logistics

A review of Internet of Things (IoT) embedded sustainable supply chain for industry 4.0 requirements

A comprehensive review of big data analytics throughout product lifecycle to support sustainable smart manufacturing: A framework, challenges and future research directions

As the next-generation manufacturing system, intelligent manufacturing enables better quality, higher productivity, lower cost, and increased manufacturing flexibility. The concept of sustainability is receiving increasing attention, and sustainable manufacturing is evolving. The digital twin is an emerging technology used in intelligent manufacturing that can grasp the state of intelligent manufacturing systems in real-time and predict system failures. Sustainable intelligent manufacturing based on a digital twin has advantages in practical applications. To fully understand the intelligent manufacturing that provides the digital twin, this study reviews both technologies and discusses the sustainability of intelligent manufacturing. Firstly, the relevant content of intelligent manufacturing, including intelligent manufacturing equipment, systems, and services, is analyzed. In addition, the sustainability of intelligent manufacturing is discussed. Subsequently, a digital twin and its application are introduced along with the development of intelligent manufacturing based on the digital twin technology. Finally, combined with the current status, the future development direction of intelligent manufacturing is presented.

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Digital twin-based sustainable intelligent manufacturing: a review

The increasing demand of customized production results in huge challenges to the traditional manufacturing systems. In order to allocate resources timely according to the production requirements and to reduce disturbances, a framework for the future intelligent shopfloor is proposed in this paper. The framework consists of three primary models, namely the model of smart machine agent, the self-organizing model, and the self-adaptive model. A cyber-physical system for manufacturing shopfloor based on the multiagent technology is developed to realize the above-mentioned function models. Gray relational analysis and the hierarchy conflict resolution methods were applied to achieve the self-organizing and self-adaptive capabilities, thereby improving the reconfigurability and responsiveness of the shopfloor. A prototype system is developed, which has the adequate flexibility and robustness to configure resources and to deal with disturbances effectively. This research provides a feasible method for designing an autonomous factory with exception-handling capabilities.

Agent and Cyber-Physical System Based Self-Organizing and Self-Adaptive Intelligent Shopfloor

Digital Twin (DT) bridges the physical and virtual worlds and provides technical support to the virtualization of the real production scene. However, with the ubiquitous upgrading of the industrial infrastructure, DT systems present an independent and self-contained pattern that causes repeated constructions, stove-piped projects, and cumbersome communication. Based on the Quality of Service (QoS) considerations, this paper proposes an enabling technology framework combining semantic resource modeling with real-time industrial object transmission to improve the performance of DT and overcome these challenges. Firstly, an enhanced modeling methodology including the industrial object meta-model and the industrial object model is designed. Heterogeneous devices are modeled comprehensively, ranging from states, functions, events, interoperability, and flexibility. By formulating the unified specification to achieve standardization and generalization, workers can customize and reuse the models flexibly according to the volatile working environment. Secondly, a real-time industrial object transmission mechanism ensures high fidelity to the physical world and provides unified interfaces for value-added services. While realizing these primary communication functions in real-time, QoS factors and other advanced performances (i.e., reliability, adaptability, robustness) are fulfilled by introducing a decoupling model, a dual-channel network, and a backup strategy. Under the orchestration of all these works, a robust DT system could be developed readily. Finally, a case study is presented to verify the effectiveness of the proposed framework. The results show that interoperability, scalability, microsecond latency, and other strict requirements are realized. 

The enhanced resource modeling and real-time transmission technologies for Digital Twin based on QoS considerations

An exploratory architecture using data and knowledge to close the loop between design and Maintenance from a product quality perspective

The rapidly changing market has stimulated the emergence of self-organizing mechanisms in intelligent manufacturing systems, where resources are generally capable of making decisions through intercommunications and interoperations to maximize system adaptivity. With the increasing number of exceptional events during manufacturing, those mechanisms might eventually fail to react timely to situations of multiple resource conflicts. In this work, we discussed the social networks consisting of various manufacturing resources and provided the relevant modeling techniques including the Resource Description Framework and the Finite State Machine. The function and behavior models can support the autonomous interactions and collaborations among resources, while the communication hub connected the resources and formed a peer-to-peer network. On this basis, the dynamic features of manufacturing networks including the exception propagation phenomenon can be analyzed. A case was studied to identify the bottleneck resources using the complex network theory. This work has provided an analytical platform to optimize manufacturing resources using complex network and graph theory.

Cheng Qian

Papers

Agent and Cyber-Physical System Based Self-Organizing and Self-Adaptive Intelligent Shopfloor

The enhanced resource modeling and real-time transmission technologies for Digital Twin based on QoS considerations

An exploratory architecture using data and knowledge to close the loop between design and Maintenance from a product quality perspective

Modeling of manufacturing resources towards an interactive Resource Social Network