Estimation of the remanufacturing cost of engineering machinery hydraulic cylinder

摘要

The remanufacturing cost of estimation, the accuracy of the estimates and the time it takes to produce cost estimates are important factors to remanufacturing organizations. This paper constructed and trained a back-propagation (BP) neural network to forecast the remanufacturing cost of engineering machinery hydraulic cylinder. According to hydraulic cylinder remanufacturing process, 11 cost-related features have been identified and quantified. Neural networks prediction model was set up with features as input and the cost as the output. The network was trained and validated using 15 samples. The testing results on another 1 sample are promising, which the prediction errors were in the acceptable range. The research provided a feasible method for remanufacturing cost forecast of the engineering machinery hydraulic cylinder, which can be used in setting the remanufactured parts prices in many situations.