This paper examines and analyzes an approach to identify and create artificial disruptions in the supply chain for sourcing parts and assemblies for manufacturing products with indigenous and specific technology and knowledge that are usually disrupted by competitors and political issues. This approach is carried out by designing and modeling in three stages, which in the first stage begins with the optimal selection of the supplier with the criteria of cost, reliability and delivery time in the absence of disruption. Then, using the results of the first stage model and adding assumptions and constraints of the attacker to disrupt the supply sources, a goal-oriented programming model is developed and finally, with the help of the quality decision support tool of the Quality House, the decision maker will try to reduce its undesirable effects by providing solutions to deal with this disruption based on the user's mission objectives and available data and ranking strategies. The following is a case study to explain these steps. The results show that by using optimization models, the supplier that has the most impact from the attacker's perspective can be selected and the impact of disruptions can be minimized.