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A look at the world production and consumption indicates that production systems resiliency and sustainability is highly regarded by businessmen and the general users for long surviving of human being race and ecological endurance. By conducting theoretical studies and reviewing the literature, and searching previous studies to identify the resilience factors important to manufacturing industries, a list of effective strategies was determined. The most important strategies of resilience considered in this study are: capacity management, multi sourcing, demand management, information sharing, additional inventory holding, contracting with backups, risk management and disaster recovery, dropping market feeding strategy, enlightenment of business flow complexity, and suppliers/facilities reinforcement. In this article, DEMATEL approach is used to demonstrate how production resilience factors can impacts on each other and what the interrelationships among these factors are. After that, a questionnaire was designed for pairwise comparisons of resilience strategies of capacity scaling, multi sourcing, contracts, inventory management, risk management, and production level. Then, a system dynamics approach is used to model the interrelations among the resilience factors by taking feedback loops into consideration managing to trace their impacts on production and inventory levels. A production system with its main processes of: production order rate, planned work, work in process (WIP), production rate, inventory level, desired shipment rate, backlogs, rejected rate, rework rate, required capacity, and capacity scaling are designed for this study. This model presents a production system with circular resilience’s strategies impacts on production scaling and hence their impacts on sustainability indicators of job creation, and salary (social pillar), profit and investment (economic pillar), and ecosystem destruction (environment pillar). System dynamics approach helped us in presenting the long trends of sustainability indicators as shown by a number of figures in the body of this article. Five scenarios are developed and the results were presented to the team of our experts presenting them by wi=0, wp=0 (case 1), wi=0, wp=0.5 (case 2), wi=1, wp=0 (case 3), wi=0, wp=1 (case 4), and wi=0.36, wp=0.47 (case 5). Experts’ opinions were gathered and then use TOPSIS approach for determining the best case the among cases discussed above. The results indicates that the data generated by Vensim computer software for five cases, case 5 with wi=0.36 and wp=0.47 is the best case among all cases.