Risk-Oriented Product Assembly System Health Modeling and Predictive Maintenance Strategy

Area of Science:

• Manufacturing Engineering
• Quality Control
• Reliability Engineering

Background:

• Assembly system health is critical for reliable product manufacturing.
• Operational data analysis is essential for managing assembly system health states.
• Current methods may not adequately address health risks in assembly systems.

Purpose of the Study:

• To propose a risk-oriented health assessment method for assembly systems.
• To develop a predictive maintenance strategy based on assembly system health risk.
• To enhance product reliability through improved assembly system management.

Main Methods:

• Introduced the concept of assembly system health risk and its formation mechanism.
• Utilized process variation data of key reliability characteristics (KRCs) for health risk assessment.
• Developed a predictive maintenance decision model using health risk as the maintenance threshold.
• Employed stepwise optimization to determine the optimal maintenance strategy.

Main Results:

• The proposed risk-oriented method effectively assesses assembly system health.
• The predictive maintenance strategy optimizes maintenance decisions.
• A case study demonstrated the method's effectiveness and superiority over traditional approaches.
• The method achieved a 37.40% cost saving compared to traditional methods.

Conclusions:

• The developed risk-based health assessment and predictive maintenance strategy significantly improve assembly system management.
• This approach ensures higher product reliability and offers substantial cost benefits.
• The findings provide a robust framework for proactive health management in assembly systems.