ABSTRACT
Smart manufacturing systems grow based on multiple demands to predict equipment reliability and quality. To this end, many machine learning techniques are examined. Data security and management are other issues that are important for the industry. The integrated blockchain and cyber-physical systems have been used to protect system transactions from hacking the data during transmission to overcome the above problems. In the private blockchain platform, the blockchain system was implemented. The quality control system was evaluated based on non-linear techniques that are complex and demonstrate the truly positive quality control rate of this system. Similarly, the prediction aspect of fault diagnosis was assessed based on hybrid prediction techniques.
