Analyzing Smart Inventory Management System Performance Over Time with State-Based Markov Model and Reliability Approach, Enhanced by Blockchain Security and Transparency
Nabil Chbaik, Azeddine Khiat, Ayoub Bahnasse, Hassan Ouajji · Statistics Optimization & Information Computing · 2024
In response to the evolving demands of modern inventory management, this paper introduces a quantitative mathematical model aimed at assessing the performance of a smart inventory management system, emphasizing the integration of blockchain technology to enhance security and transparency. By considering essential hardware components, including ESP32 module, HC-SR04 ultrasonic sensor, battery, and jumper wires, the model utilizes Markov modeling and a reliability-based approach. Its primary objective is to enable timely repair and maintenance activities, ensuring sustained system availability by identifying and addressing weak components. Efficient operation of all system parts is critical for the timely transmission of inventory data. Through the incorporation of blockchain technology, the study addresses security and transparency concerns, alongside evaluating key reliability metrics such as reliability, unreliability, and Mean Time to Failure (MTTF). Sensitivity analysis identifies critical components, highlighting the importance of maintenance for components like the switch and servo motor. The research underscores the role of blockchain technology in fortifying security and transparency in smart inventory management systems, alongside emphasizing the significance of reliability metrics in system performance optimization.