Big Data Driven Edge-Cloud Collaboration Architecture for Cloud Manufacturing: A Software Defined Perspective

Abstract

In the practice of cloud manufacturing, there still exist some major challenges, including: 1) cloud based big data analytics and decision-making cannot meet the requirements of many latencysensitive applications on shop floors; 2) existing manufacturing systems lack enough reconfigurability, openness and evolvability to deal with shop-floor disturbances and market changes; and 3) big data from shop-floors and the Internet has not been effectively utilized to guide the optimization and upgrade of manufacturing systems. This paper proposes an open evolutionary architecture of the intelligent cloud manufacturing system with collaborative edge and cloud processing. Hierarchical gateways connecting and managing shop-floor things at the ''edge'' side are introduced to support latency-sensitive applications for real-time responses. Big data processed both at the gateways and in the cloud will be used to guide continuous improvement and evolution of edge-cloud systems for better performance. As software tools are becoming dominant as the ''brain'' of manufacturing control and decision-making, this paper also proposes a new mode-''AI-Mfg-Ops'' (AI enabled Manufacturing Operations) with a supporting software defined framework, which can promote fast operation and upgrading of cloud manufacturing systems with smart monitoring-analysis-planning-execution in a closed loop. This research can contribute to the rapid response and efficient operation of cloud manufacturing systems.

Big Data and Its V’s with IoT to Develop Sustainability

“…As software is dominating manufactory control and decision making like "brain," it also proposes an AI-enabled Manufacturing Operations (AI-Mfg-Ops) mode with software-defined framing that can help 6 Scientific Programming rapid operation and upgrade of cloud manufacturing systems in an in-line loop with intelligent monitoring, analysis, planning, and implementation. Research may lead to the rapid response of cloud production systems and their efficient functioning [33]. e study of data mining has aroused the interest of both academia and industry.…”

Address business crisis caused by COVID‐19 with collaborative intelligent manufacturing technologies

“…it can be replaced by another shop floor if there is a failure. With the CIM technologies, other shop floors can be quickly reconfigured to adapt to different production requirements and to ensure the overall production capacity [8, 15]. The cloud platform can support to plan the production resources of multiple shop floors in a unified manner and arrange multiple shifts.…”

“…A cloud‐edge‐device computing structure [15] can be used to achieve information sharing and collaborative production between shop floors. Edge computing collects shop floor data and uploads them to the edge nodes for fast processing.…”

“…With the help of smart sensors and plug‐and‐play cyber‐physical systems, the workstations in the assembly lines can change the operation processing and setting sequence according to the actual order inbound traffic and capacity utilisation [23, 24]. The software‐defined cloud manufacturing system can quickly configure the production system accordingly [8, 15]. When disruptions occur, the reconfigured system implements product variants, replacing the original products to some extent, thus reducing the loss of the enterprise.…”

Intelligent Machine Tool Based on Edge-Cloud Collaboration

“…Shao et al [19] used edge-cloud collaboration to process dataintensive IoT workflows. Based on the edge-cloud collaboration, Yang et al [20] proposed an evolutionary architecture of the intelligent cloud manufacturing system, using layered gateways for real-time response. The "Industrial Internet Platform White Paper (2017)" pointed out that high-frequency data acquisition in industrial production brought huge pressure.…”