MULTI-AGENT-BASED SELF-ORGANIZING MANUFACTURING NETWORK TOWARDS MASS PERSONALIZATION

摘要

Mass personalization is arriving. It requires smart manufacturing capabilities to responsively produce personalized products with dynamic batch sizes in a cost-effective way. However, current manufacturing system automation technologies are rigid and inflexible in response to ever-changing production demands and unforeseen internal system status. A manufacturing system is required to address these challenges with adaptive self-organization capabilities to achieve flexible, autonomous, and error-tolerant production. Within the context, the concept of Self-Organizing Manufacturing Network has been proposed to achieve mass personalization production. In this paper, we propose a four-layer system-level control architecture for Self-Organizing Manufacturing Network. This architecture has additional two layers (namely, Semantic Layer and Decision-Making Layer) on Physical Layer and Cyber Layer to improve communication, interaction, and distributed collaborative system automation. In this architecture, manufacturing resources are encapsulated as Semantic Twins to make interoperable peer communication in the manufacturing network. The interaction of Semantic Twins consolidates system status and manufacturing environment that enables multi-agent control technologies to optimize manufacturing operations and system performance.