A framework for credit-driven smart manufacturing service configuration based on complex networks

ABSTRACT

Complex cooperative relationships between manufacturing equipment and services make such manufacturing networks have necessary research significance in network science. Under the prevailing background of mass customizing, the continuous coordination between manufacturing services (MSs) in the cloud platform is pulling the complex cooperative relationship between equipment and even enterprises, which constitutes a complex manufacturing network (CMN) from a macro perspective. In this paper, a credit-driven service configuration method is proposed, which is tactfully modeled on the reputation system of Uber. Under such circumstances, MSs could be evaluated combining theirexecution states and historical manufacturing behaviors and chosen as the most appropriate service under the current processing condition to tackle the manufacturing tasks according to customers’ requests accurately. Results in the proof-of-concept simulation show that credit is well integrated with the manufacturing process, and could be utilized to drive the CMN with a four-tier networked architecture on the whole, in which it is taken as the benchmark for the service-and-task smart matching in cases where customer requirements and manufacturing process stability are paramount. Credit also effectively assists MSs in exception self-organization and restrains the diffusion of the influence range of the deterioration of service credit when faced with service failures.

KEYWORDS:

• Manufacturing network
• mass customizing
• manufacturing services
• credit-driven
• service configuration
• self-organization

Acknowledgments

This work was sponsored by the the Key Project of National Science Foundation of China [U2001201] and the 111 Project Grant of NPU [B13044].

Disclosure statement

There is no potential conflict of interest in this paper.

Additional information

Funding

This work was supported by the Key Project of National Science Foundation of China [U2001201] and the 111 Project of Northwestern Polytechnical University [B13044].