Abstract:

To meet the spare parts collaborative needs of manufacturing industry chain collaborative platform, we propose a cross-enterprise inventory control solution and establish a near-term demand forecasting model. In order to ensure the effectiveness of the inventory control program, we dynamically extract historical transaction data of each node and real-time inventory data, and obtain the optimal solution based on the genetic algorithm. We use the MapReduce framework to calculate model parameters and improve the processing speed. By pushing the results to downstream service providers, the feedback information can control the dynamically generated orders. The application in the automotive industry chain cloud services platform demonstrates that the response time of the industry chain is compressed.

Key words: spare parts, industrial chain, inventory cooperative, genetic algorithms