The intensive shortage of natural resources and the inchoate phase of automobile remanufacturing in a closed-loop supply chain (CLSC) are driving people to take cyclic manufacturing seriously. Aiming at maximizing resource utilization and produce profits, we apply an optimizing mathematical analysis to the modeling of automobile engine remanufacturing in a joint manufacturing system, in which the quantity and quality of procurement, and the demand of the market, are both uncertain. The manufacturer can either produce new products with raw materials or remanufacture the returned product taken back from customers; the raw materials are bought from two suppliers with certain probabilities of disruption in the supply. The returned products are classified into different quality levels according to the testing results after sorting, by considering the remanufacture-up-to strategy we obtained the optimal remanufacturing ratio, then the manufacturing quantity and corresponding maximized total profit of this joint system are determined. We also investigated a real-life case of auto engine remanufacturing, comparing it with the theory of optimal remanufacturing policy, and the results indicate that a material savings of more than 45% and a cost improvement of more than 40% could be achieved when the optimal remanufacturing policy of our model is implemented.