Cost Estimation of Manufacturing Enterprises based on BP Neural Network and Big Data Analysis

Abstract

The manufacturing industry is the pillar industry of modern industry, and the cost estimation of manufacturing enterprises is an important management means of the manufacturing industry. Aiming at the cost estimation problem of manufacturing enterprises, this research proposes a cost estimation method based on Back Propagation (Back Propagation) neural network and big data analysis. In the process, the Lambda architecture was used to construct the big data analysis architecture of manufacturing enterprises, the K-means clustering algorithm was introduced for data clustering, and then the genetic algorithm was combined with the Back Propagation neural network to estimate the cost. In the estimation accuracy test, the accuracy of the research method can reach 94.7% after 240 iterations; in the calculation time test, the calculation time of the research method is 403 Ks when the data size is 500 Gb in a large-scale data set; in the call data volume test, the call data volume of the research method is 164 Kb when the research method is carried out to the seventh step in the small-scale data set; when the application analysis is carried out, the research method completes accurate cost estimation for 9 target parts. This research method has good model performance and calculation accuracy, and can effectively estimate manufacturing enterprises’ costs.