Design and implementation of drawing number apply system based on machine learning

For the current situation of low efficiency of drawing number apply in enterprises, a drawing number apply system based on machine learning was developed. First, the dataset is obtained by remove serial number and remove duplicates processing of the existing historical drawing number apply records in the enterprise PDM database. Secondly, the K-means++ algorithm is used to divide the dataset and the parts that need to apply for drawing numbers into several clusters, traverse the new parts in each cluster and use the KNN algorithm to get their attribute drawing numbers. For the “same name and different number” parts, the MVCNN-based 3D model retrieval technology is used to obtain the attribute drawing number. Finally, assign the latest serial number to the attribute drawing number to obtain the complete drawing number. Taking a batch of refrigerated trucks in an enterprise as an example, the correct rate of system drawing number apply is over 95%, and the efficiency is increased by 5~6 times.