Exploration of the optimal modularity in assembly line design

Area of Science:

• Industrial Engineering
• Manufacturing Systems
• Operations Research

Background:

• Structural modularity in assembly processes positively impacts efficiency, manufacturing flexibility, and productivity for mass customization.
• Current methods for determining optimal modularity often rely on intuition or analytical reasoning, lacking scientific rigor for complex tasks.

Purpose of the Study:

• To develop a scientific methodology for selecting the optimal modular assembly model from predefined alternatives.
• To explore the relationships between modularity measures, complexity, and symmetry in assembly processes.

Main Methods:

• Investigated the linkage between modularity and complexity to understand how modularization affects structural complexity distribution.
• Proposed and compared three methods for optimal modular assembly model selection, including two novel approaches and one adapted network analysis technique.
• Evaluated methods through numerical tests to assess their precision and effectiveness.

Main Results:

• The study identified a prioritized method among the three tested for its superior results and precision in selecting optimal modular assembly models.
• Demonstrated how modularization strategies can influence the distribution of structural complexity across assembly lines.

Conclusions:

• The developed methodology provides a scientific foundation for selecting optimal modular assembly models, moving beyond intuitive approaches.
• The findings offer a more precise and effective way to enhance manufacturing flexibility and productivity in mass customization settings.