Abstract
With the development of Industry 4.0 and cloud computing technology, personalized customization as a new production mode is showing a trend of rapid development. Personalized customization has the characteristics of order-driven production, strict processing times, high dynamic external conditions, and large flexibility in the production process, all of which bring more uncertainty to the production system and great challenges to the edge computing processing of related tasks in personalized customization production. Aiming at the above problems, a thing-edge-cloud collaborative computing decision-making (TCCD) method in customized production is proposed. First, the architecture of a personalized customized production system used for implementing the TCCD method is presented. Then, according to the number and type of products in the customer order received from the private cloud platform, the customer’s personalized customized order is dynamically divided. Subsequently, a task priority sorting algorithm is proposed to optimize the waiting time of all tasks involved in the order. Furthermore, a discrete particle swarm algorithm is proposed to optimize the average execution time of all tasks and equipment utilization decision-making options (thing-edge collaborative computing, edge-edge collaborative computing, or edge-cloud collaborative computing). Finally, the effectiveness of the proposed TCCD method is verified by using the prototype platform of personalized product packaging intelligent production line with the same process flow.
Highlights
New information technologies, such as artificial intelligence [1]–[3], cloud computing [4]–[6] and Internet of Things (IoT) [7]–[9], have emerged one after another, which have enlightened upgrades to the manufacturing industry
Edge computing provides a mechanism for interconnection and intercommunication between devices, operational technology (OT) systems, and information technology (IT) systems as well as real-time data collection, aggregation, storage, and analysis mechanisms deployed in the manufacturing site, which can quickly and achieve integration of OT and IT [16]–[20]
A thing-edge-cloud collaborative computing decision-making (TCCD) method based on discrete particle swarm algorithm was proposed to optimize the average execution time of all the order tasks and equipment utilization
Summary
New information technologies, such as artificial intelligence [1]–[3], cloud computing [4]–[6] and Internet of Things (IoT) [7]–[9], have emerged one after another, which have enlightened upgrades to the manufacturing industry. Liang et al [28] designed a multi-user collaborative offloading scheduling algorithm based on a decomposition method to solve the coordination problem of wireless resources and computing resources allocation in a multi-user mobile edge computing system under I/O interference, which can made the offloading controllable and has better results. Faced with the challenges of stricter task execution time and full utilization of edge device computing resources in personalized customized production, the traditional centralized cloud computing models cannot meet the demand. To build and implement a flexible and reliable edge collaborative computing system, we propose an edge collaborative computing system architecture for personalized customized production and a thing-edge-cloud collaborative computing decision (TCCD) method to achieve efficient computing of customized production tasks and optimal utilization of equipment computing resources.
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