Date of Award


Publication Type

Doctoral Thesis

Degree Name



Industrial and Manufacturing Systems Engineering

First Advisor

Elmaraghy, Hoda (Industrial and Manufacturing Systems Engineering)


Industrial Engineering.




The artificial world experiences continuous changes that result in the evolution of design features of products and the capabilities of the corresponding manufacturing systems similar to the changes of species in the natural world. The idea of simulating the artificial world, based on the analogy between the symbiotic behaviour of products and manufacturing systems and the biological co-evolution of different species in nature, is expressed by a model and novel hypotheses regarding manufacturing co-evolution mechanism, preserving that co-evolution and using it for future planning and prediction. Biological analogy is also employed to drive the mathematical formulation of the model and its algorithms. Cladistics, a biological classification tool, is adapted and used to realize evolution trends of products and systems and their symbiosis was illustrated using another biological tool, tree reconciliation. A new mathematical method was developed to realize the co-development relationships between product features and manufacturing capabilities. It has been used for synthesizing / predicting new species of systems and products. The developed model was validated using machining and assembly case studies. Results have proven the proposed hypotheses, demonstrated the presence of manufacturing symbiosis and made predictions and synthesized new systems and products. The model has been also adapted for use in different applications such as; system layout design, identifying sustainable design features and products family redesign to promote modularity. The co-evolution model is significant as it closes the loop connecting products and systems to learn from their shared past development and predict their intertwined future, unlike available unidirectional design strategies. The economic life of manufacturing systems can be extended by better utilizing their available capabilities, since the co-evolution model directs products - systems development towards reaching a perfect co-evolution state. This research presents original ideas expressed by innovative co-evolution hypotheses in manufacturing, new mathematical model and algorithms, and demonstrates its advantages and benefits in a wide range of applications.