Cyber-physical Systems Architecture for Self-Aware Machines in Industry 4.0 Environment

TLDR

Cyber‑physical systems are emerging methodologies that monitor and synchronize information between physical and cyber spaces, and in manufacturing, advanced analytics over CPS can make machines more efficient, collaborative, and resilient, driving the Industry 4.0 transformation. The paper proposes a unified framework for integrating CPS into manufacturing and introduces an adaptive clustering method for interconnected systems, illustrated with a case study of self‑aware machines. The framework employs an adaptive clustering analytical method to integrate CPS, and the paper demonstrates its application through a case study of self‑aware machines.

Abstract

The recently emerged methodologies for interconnected systems such as cyber-physical systems are focused to closely monitor the information and synchronize it between the physical connected systems and cyber computational space. Depending on the physical system being monitored, the approach for designing and implementing the framework for interconnect systems might differ. In manufacturing industry, utilizing advanced analytics over a systematic deployment of cyber-physical system provides network of machines with ability to perform more efficiently, collaboratively and resiliently. Such transformation can takes the manufacturing industry into the next level of evolution namely called Industry 4.0. In this paper, a unified framework for integrating CPS in manufacturing is presented. Then an adaptive clustering method as an advanced analytical method for interconnected systems will be described and at the end of the paper a case study of self-aware machines by CPS integration is presented.