Product cost evaluation method and system based on industrial big data

Abstract

The invention discloses a product cost evaluation method and system based on industrial big data. The method comprises the following steps: collecting industrial big data, and extracting product characteristic data, product processing process data and product processing cost data from the industrial big data; inputting the product characteristic data and the product processing process data into arandom forest classification model for training to generate a processing scheme recommendation model; inputting the product processing process data and the product processing cost data into a CART decision tree for training to generate a processing cost prediction model; and performing product cost prediction by using the processing scheme recommendation model and the processing cost prediction model. Product machining efficiency can be improved, and machining cost can be reduced.

Description

technical field [0001] The invention belongs to the technical field of intelligent manufacturing, and more specifically relates to a product cost evaluation method and system based on industrial big data. Background technique [0002] With the development of mechanical processing and manufacturing technology, intelligent manufacturing technology has attracted more and more attention from enterprises. For example, in the fields of mold manufacturing and lithium battery equipment, the production and manufacturing of workpieces tends to be automated and intelligent. In current product processing, manufacturing process analysis and decision-making are made by R&D engineers according to different product characteristics. Due to the high dependence on labor, it is impossible to meet the needs of informatization and intelligence in the production process of products. Especially in terms of product processing cost evaluation, these analysis processes that rely heavily on manual wor...

AI Technical Summary

Problems solved by technology

Due to the high dependence on labor, the demand for informatization and intelligentization of the product production process cannot be fulfilled

Especially in the evaluation of product processing costs, these analysis processes that rely heavily on manual work will lead to large errors, which will affect the production plan and capacity allocation of the enterprise, and will also cause waste of human and financial resources, which will increase the processing cost of products

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