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 latency-sensitive 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 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">things</i> 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.
Highlights
With the development of tiny sensors towards smaller-size, lower-cost, lower power consumption and higher-precision, efforts have been made in developing and applying a large variety of smart sensors, devices and facilities in the manufacturing industry to build what is termed as smart factories
Those smart objects or assets with embedded identification (ID), sensing, and actuation capabilities are usually connected using the Internet of Things (IoT) [1] and 5G technologies [2], and seamlessly integrated into smart manufacturing platforms, like Cloud Manufacturing (CMfg) systems [3] and
Manufacturing resources including assets and materials are converted into smart cloud assets and objects following a Human-Cyber-Physical System approach
Summary
With the development of tiny sensors towards smaller-size, lower-cost, lower power consumption and higher-precision, efforts have been made in developing and applying a large variety of smart sensors, devices and facilities in the manufacturing industry to build what is termed as smart factories. Manufacturing resources can be added or removed for different orders at hierarchical levels of workcell, workshop and enterprise without affecting each other; (2) Coordination mechanisms and protocols converters can be designed and developed to coordinate, synchronize, and control smart assets and objects; and (3) A Data Analytics Service with suitable models to make full use of the vast sensor data should support real-time synchronization and management Those models and coordination mechanisms can be reconfigured or upgraded for better performance in iCMfg. For example, a manufacturing cell, an efficient grouping of the resources required to manufacture a product, must be ‘‘smart’’ enough to produce a wide variety of orders of fluctuating volumes, with the UOS support. AR/VR models can be fully integrated into iCMfg platform for uses in smart manufacturing services
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