Service-Oriented Real-Time Smart Job Shop Symmetric CPS Based on Edge Computing

Chuang Wang,Dongyu Yang,Yi Lv,Qiang Wang,Guanghui Zhou

doi:10.3390/sym13101839

Abstract

Symmetry is one of the most important notions in the digital twins-driven manufacturing cyber–physical system (CPS). Real-time acquisition of production data and rapid response to changes in the external environment are the keys to ensuring the symmetry of the CPS. In the service-oriented production process, in order to solve the problem of the service response delay of the production nodes in a smart job shop, a CPS based on mobile edge computing (MEC) middleware is proposed. First, the CPS and MEC for a service-oriented production process are analyzed. Secondly, based on MEC middleware, a CPS architecture model of a smart job shop is established. Then, the implementation of MEC middleware and application layer function modules are introduced in detail. By designing an MEC middleware model and embedding function modules such as data cache management, redundant data filtering, and data preprocessing, the ability of data processing is sunk from the data center to the data source. Based on that, the network performances, such as network bandwidth, packet loss rate, and delay, are improved. Finally, an experiment platform of the smart job shop is used to verify different data processing modes by comparing the network performance data such as bandwidth, packet loss rate, and response delay.

Highlights

IntroductionInternational competition is becoming increasingly fierce. Improving the intelligence level and rapid response capability of the job shop is a key task to maintain the competitive advantage of manufacturing enterprises
Gong et al designed three types of nonlinear RF chain structures, which reduce the power consumption of massive MIMO systems, and massive multiple-input multiple-output (MIMO) wireless communication technology is an ideal channel to connect the industrial Internet of Things (IIoT) and the cyber–physical system (CPS) [24]
In order to solve the response lag problem of a service-oriented production process, this article proposes a job shop CPS model based on mobile edge computing (MEC) middleware

Summary

Introduction

International competition is becoming increasingly fierce. Improving the intelligence level and rapid response capability of the job shop is a key task to maintain the competitive advantage of manufacturing enterprises. The cyber–physical system (CPS) is an important carrier in the intelligent manufacturing of a smart job shop. It is a multidimensional and complex production system that integrates perception, calculation, and control [1]. The implementation of CPS will lead to significant changes in the working environment, especially in manufacturing and production control systems [22]. It can realize the job shop environment monitoring, production process optimization, product quality inspection, and other aspects of independent decision making and control, and it can improve production efficiency [23]. Rathore et al proposed Deep-Block-IoT Net, and a secure deep learning approach with blockchain for the IoT network is carried out among the edge nodes

Results

Discussion

Conclusion