Date of Award


Degree Type


Degree Name



Industrial and Manufacturing Systems Engineering

First Advisor

ElMaraghy, Waguih


Global Supply Chain, Product Architecture, Supply Chain Complexity, Supply Chain Design, Supply Chain Disruptions, Supply Chain Robustness




Supply chains (SCs) play a crucial role in business operations and economies around the globe. They are in constant change and face challenges such as recurrent risks and disruption risks. The disruptive risks tend to cascade and propagate upstream and downstream of the disruption point. Due to the difficulty of calculating probabilities of disruptions, many decision makers prefer to underestimate disruptive risks. Losses of billions of dollars are accounted for each year due to the disruptive risks. These losses highlight the importance and need of having decision support systems and tools that can aid to design, model and analyze SCs that can cope with disruptions and their effects through all the stages. This research aims at developing new methods for designing and analyzing SCs that are prepared for unexpected events. It provides new insights into the methods to estimate the impact of possible disruptions during designing and planning stages. It further proposes complexity, robustness and resilience measures which facilitate the comparison between different SC designs in different scenarios. The significance of this research is to provide more stable production environments and develop the capability to prepare for unexpected events. Particular focus is given to natural disasters due to the magnitude and variety of impacts they could cause. Hence, a mathematical programming model that designs SCs and product architectures is proposed. The objective function is to minimize the disaster risk score of natural disasters (which depends on the geographical location of each SC entity and its associated “World Risk Index”). Also, a goal programming model is derived from the initial model. The goal programming model allows the inclusion of the decision-makers’ risk attitudes and costs to balance the decisions. The results obtained from the model showed that the SC and product architecture designs affect each other. Additionally, it was demonstrated that different risk-attitudes could lead to different SC designs. To achieve harmonious designs between SCs and products while remaining robust and controlling complexity, a novel methodology to assess structural SC complexity and robustness is presented using network analysis. This methodology includes the evaluation of different product architectures. Consequently, managers can choose the SC/product architecture that has a balanced level of complexity and robustness. It is worth noting that complexity and higher costs are needed to protect against disruptions. Moreover, the results demonstrated that the modular architecture is preferable as it has a balanced level of complexity and robustness. To analyze the dynamic behaviour of the SCs, a system dynamics framework is introduced to evaluate the impacts of disruptions in assembly SCs. Consequently, a pragmatic tool that provides organizational support is proposed. This framework enables the examination of full and partial disruptions and the incorporation of expediting orders after a disturbance. The SC performance indicators are the output of the proposed model. These indicators make the comparison between different scenarios easy. The usage of the framework and the findings can serve to define disruption policies, and assist in the decisions relating to the SC design. After running several scenarios, it was determined that the disruptions happening in the downstream levels have more impacts on the SC performance than the disruptions in the upstream levels. Hence, the disruption policies for the downstream levels should have higher priority. Moreover, it was demonstrated that expediting after disruptions could affect more the already damaged SC performance. Finally, to evaluate the SC performance and costs when facing disruptions, an index to assess SC resilience cost is provided. The metric considers the fulfilment rate in each period of each SC entity and its associated cost. This index allows comparison between different scenarios in the SC.

Available for download on Wednesday, April 17, 2019