Date of Award


Publication Type

Master Thesis

Degree Name



Industrial and Manufacturing Systems Engineering


Applied sciences


Waguih ElMaraghy




Global competition, increased products variety, shorter time-to-market, and higher quality impose an increased complexity to the manufacturing systems. Assembly is a stage in the production system that has a significant portion of the total cost as well as a high impact on the final product quality. Therefore, recognition and management of complexity in assembly will result in cost efficiency in manufacturing systems.

This thesis aims at modeling the assembly complexity in physical and functional domains. A matrix-based model is proposed to capture the effect of product and process-related elements on complexity in the physical domain. A novel notion, i.e. Reduced Combinatorial Complexity (RCC) is introduced, which deploys the entropy theory to measure complexity in the functional domain.

The proposed models have been applied on different case studies. The results show that applying the Design For Assembly (DFA) method on products will result in reduction of the assembly complexity. In addition, RCC confirms that dividing assembly into subassemblies will lead to significant reduction in complexity. Furthermore, it can be used as a tool to compare different subassemblies and their effect on reducing the assembly total complexity.