A reliable framework for supply chain management using cluster based blockchain for intelligent industrial automation

Area of Science:

• Industrial Automation
• Supply Chain Management
• Blockchain Technology
• Intelligent Computing

Background:

• Industry 4.0 necessitates intelligent mechanisms for enhanced production levels.
• Effective supply chain management is crucial for tracking system performance and improving product quality in manufacturing.
• Modern industrial automation relies heavily on intelligent computing algorithms.

Purpose of the Study:

• To propose a reliable framework for supply chain management using cluster-based blockchain technology.
• To organize information using Blockchain Technology and analyze it for intelligent industrial automation systems.
• To enhance product quality and system performance through intelligent supply chain solutions.

Main Methods:

• A framework integrating cluster-based blockchain technology for supply chain management.
• Information organization and analysis using Blockchain Technology.
• Performance evaluation using execution time cost, accuracy, and mean error value analysis.
• Utilizing 26 software metrics for performance evaluation in Software Development applications.

Main Results:

• The proposed framework achieves 93% accuracy in software development project clustering.
• Analysis of blockchain performance based on execution time, accuracy, and mean error.
• Demonstrated the impact of optimum cluster size selection on blockchain accuracy for new projects.

Conclusions:

• Cluster-based blockchain technology offers a reliable framework for intelligent industrial automation.
• Optimizing cluster selection is key to achieving high accuracy and suitable blockchain implementation.
• The framework provides a valuable approach for enhancing supply chain management and product quality.