Method for mining data of clothing standard working hours on basis of clustering analysis

Abstract

The invention discloses a method for mining data of clothing standard working hours on the basis of clustering analysis. The method comprises the following steps: (1) data acquisition: recording the procedure working hours of each staff in real time by utilizing an RFID (radio frequency identification device) production system and establishing a data warehouse; (2) data preprocessing: removing abnormal data objects from a data set by a triple standard deviation method; (3) clustering by a density-based K-means algorithm, comprising: 1, determining the value of a clustering number K and the convergence precision of a criterion function; 2, initiating a clustering center; 3, appointing a sample object; 4, updating the clustering center; and 5, checking whether to meet the convergence precision or not, if so, finishing clustering, otherwise, repeating the steps 3 to 5 until the convergence precision is met; and (4) dividing all the working hour data into K classes according to the clustering result, and evaluating the average value, namely the standard working hours of the class, on the basis of each class. By the method, the standard working hours can be generated automatically. The method is convenient to implement and low in cost.

Description

technical field [0001] The invention belongs to the field of information technology application, and relates to a method for analyzing man-hour standards using data mining technology in the process of formulating clothing standard man-hours, in particular to a data mining method based on cluster analysis. Background technique [0002] For a long time, the garment industry has been one of the most competitive industries in the world in my country. However, its leading position is largely due to the extremely low domestic labor cost advantage. With the continuous deepening of the process of manufacturing informatization, the garment industry It is also gradually transforming from traditional labor-intensive to technology-intensive and intelligence-intensive. At present, many clothing companies have realized informatization in many aspects, such as procurement, production, sales, etc., which has greatly improved production efficiency, reduced production costs, and shortened prod...

AI Technical Summary

Problems solved by technology

However, the current system standard adopts the international standard, which is not very suitable for our country, and each company has its own specific situation, which requires the GSD system to meet the requirements of customization, but this is difficult to achieve

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