Smart Monitoring of Manufacturing Systems for Automated Decision-Making: A Multi-Method Framework

Area of Science:

• Industrial Engineering
• Manufacturing Systems
• Data Analytics

Background:

• Smart monitoring is crucial for intelligent manufacturing automation.
• Real-time data collection via sensors is common, but efficient analysis is lacking.
• Advanced signal processing and visualization offer potential solutions.

Purpose of the Study:

• To propose a multi-method framework for smart monitoring in manufacturing.
• To enable intelligent decision-making through efficient data analysis.
• To utilize machine signals for operational status and anomaly detection.

Main Methods:

• Collecting machine signals using noninvasive sensors.
• Applying signal filtering and classification techniques.
• Developing a framework for intelligent decision support.

Main Results:

• The proposed framework demonstrates practicability through numerical experiments.
• The method shows accuracy in assessing operational status and detecting anomalies.
• The framework effectively advises managerial actions based on detected issues.

Conclusions:

• The developed smart monitoring framework is accurate and practical for manufacturing systems.
• This approach supports intelligent decision-making and anomaly detection.
• Further research into diverse manufacturing environments is recommended.