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Engineering machine part stocking prediction method, management method and system

A technology of forecasting method and management method, which is applied in the field of construction machinery parts stocking management system, can solve problems such as poor adaptability, achieve high accuracy, reduce out-of-stock rate, and improve accuracy

Pending Publication Date: 2022-01-21
中科云谷科技有限公司 +1
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  • Abstract
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Problems solved by technology

[0005] The purpose of the present invention is to provide a forecasting method, management method and system for spare parts of construction machinery, aiming to solve the problem of poor adaptability when the existing single forecasting model is applied to the stocking management of different kinds of spare parts of construction machinery

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  • Engineering machine part stocking prediction method, management method and system
  • Engineering machine part stocking prediction method, management method and system
  • Engineering machine part stocking prediction method, management method and system

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Embodiment Construction

[0041] It should be noted that, in the case of no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0042] The specific implementation manners of the embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation manners described here are only used to illustrate and explain the embodiments of the present invention, and are not intended to limit the embodiments of the present invention.

[0043] figure 1 It is a schematic flowchart of a method for predicting engineering machinery parts in an embodiment of the present invention. Such as figure 1 As shown, the present invention provides a method for forecasting construction machinery parts stocking, the method comprising:

[0044] Construct data features from the historical sales data of the accessories; match the corresponding demand forecast model...

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Abstract

The embodiment of the invention provides an engineering machine part stocking prediction method. The prediction method comprises the following steps: constructing data features from historical sales volume data of parts; matching a corresponding demand prediction model according to the data features; and obtaining a prediction demand of the accessory based on the historical sales data of the accessory and a demand prediction model. Meanwhile, the invention further discloses a corresponding engineering machine part stock management method and system. According to the embodiment of the invention, the method and system solves a problem that a single prediction model is poor in adaptability to different types of engineering machinery parts, and improves the efficiency of stocking management of the engineering machinery parts and the economical efficiency and accuracy of stocking.

Description

technical field [0001] The invention relates to the field of inventory management, in particular to a method for forecasting construction machinery parts stocking, two construction machinery parts stocking management methods, and a construction machinery parts stocking management system. Background technique [0002] The demand for spare parts in the construction machinery industry mainly comes from the maintenance and repair needs of the corresponding main engine. When the main engine shuts down unplanned, it will greatly affect the customer's construction period and bring additional economic losses. The demand for accessories has the characteristics of urgent time, many varieties, and small demand for individual materials. Most materials cannot form a stable logistics. [0003] At present, the industry mainly uses the weighted average or moving average of the historical demand for accessories in the recent period as its future demand, supplemented by a certain multiple as ...

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Application Information

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IPC IPC(8): G06Q10/04G06Q10/08G06K9/62G06N20/00
CPCG06Q10/04G06Q10/06315G06Q10/087G06N20/00G06F18/23213G06F18/24
Inventor 林丹珠童兴陈轶泽龚勇周志忠罗昌明
Owner 中科云谷科技有限公司
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