Development of a cloud based smart manufacturing system

Abstract

Smart manufacturing considered as a new trend of modern manufacturing helps to satisfy objectives associated with the productivity, quality, cost and competiveness. The smart manufacturing system is characterized by decentralized, distributed, networked compositions of autonomous systems. The model of smart manufacturing is inherited from the organization of the living systems in biology and nature such as ant colony, school of fish, bee's foraging behaviors, and so on. In which, the resources of the manufacturing system are considered as biological organisms, which are autonomous entities so that the manufacturing system has the advanced characteristics inspired from biology such as self-adaptation, self-diagnosis, and self-healing. In this paper, a cloud based smart manufacturing system for machining transmission cases is considered as research object in which the advanced information and communication technology such as cognitive agent, swarm intelligence, and cloud computing are used to integrate, organize and allocate the machining resources.

Literature review on the ‘Smart Factory’ concept using bibliometric tools

“…The resources of a smart manufacturing system can be considered as autonomous organisms and, likewise the living system, the manufacturing system has the characteristics of self-adaptation, self-healing and self-diagnosis. The algorithms inspired to living systems can be applied to smart manufacturing Park et al (2015). considered a cloud based smart manufacturing system for machining transmission cases and they used an advanced information and communication technology such as cognitive agent, swarm intelligence, and cloud computing to integrate, organize and allocate the machining resources.…”

Development of the Architecture and Reconfiguration Methods for the Smart, Self-Reconfigurable Manufacturing System

“…Integration, organization, and allocation for advanced information and communication technologies [5]; • Self-optimizing processes [6], data-driven decision making [7], self-regulation, and self-organization for adaptive and intelligent manufacturing control [8];…”