A personalized method of cloud manufacturing service customization

Evolutionary Analysis of Cloud Manufacturing Platform Service Innovation Based on a Multiagent Game Perspective

“…Ehsan et al [61] introduced service quality level into cloud manufacturing service composition model based on game theory. For the choice of users variables, Huo et al [9] provided personalized manufacturing services for users according to consumer preferences based on the Evolutionary Game Algorithm. Wang et al [62]compared multi-user oriented and multi-task oriented cloud manufacturing service scheduling model, considered the influence of user preference and scheduled time on the model, and described user preference by comparison of preference criteria and fuzzy terms.…”

“…In the cloud manufacturing mode, through the Internet of Things (IoT) and virtualization technology, manufacturing enterprises can package highly heterogeneous manufacturing resources (software, data) and manufacturing capabilities (computing capabilities, design capabilities) into manufacturing cloud services and publish them to cloud manufacturing platforms, form a shared resource pool, and implement unified and centralized intelligent management. Then, cloud manufacturing platforms can provide users with all stages of product life cycle services through the internet, such as demonstration services, design services, production and processing services, experimental services, simulation services and integration services [7]- [9]. Through the cloud manufacturing platform, enterprises realize the supply and demand matching and collaboration of manufacturing services, which not only improves the utilization rate of resources but also meets the personalized needs of users.…”

Evolution dynamic of intelligent construction strategy of coal mine enterprises in China

“…Aiming at the characteristics of mutual learning and adaptive adjustment of strategies among participants in groups, evolutionary game theory provides a reasonable analysis framework, which is widely used in environmental governance ( da Silva Rocha and Salomão, 2019 ), low-carbon supply chain ( Kang et al., 2019 ), energy security ( Liu et al., 2015 ; Wang et al., 2020 ). Among them, for the construction of enterprise intelligence, research scholars use the classic evolutionary game model, which mostly focuses on cloud manufacturing services ( Huo et al., 2021 ; Wang et al., 2020 ) supply chain collaborative innovation ( Lu et al., 2021 ; Litos et al., 2017 ), value co-creation ( Li et al., 2021 ), etc. However, there are still two practical characteristics in the behavior decision of intelligent construction in coal mining enterprises: on the one hand, the number of coal mining enterprises are limited, and the classical evolutionary game theory is based on the overall infinite adaptive strategy adjustment; On the other hand, the changeable geological environment such as rock burst, gas outburst and water permeability brings uncertainty to the intelligent construction of coal mine enterprises, while the classical evolutionary game theory does not consider the influence of uncertain environment on equilibrium.…”

Case Retrieval Strategy of Turning Process Based on Grey Relational Analysis

“…However, with the development of the network-based public service manufacturing model [14][15][16], the above methods are not applicable anymore because too much time is consumed. It is unacceptable for users if the response time is too long when they access the Internet to obtain service.…”