Product life cycle analysis method and system based on big data and storage medium

A product life cycle and analysis system technology, applied in the Internet field, can solve the problems that life cycle analysis methods cannot be completed efficiently, and achieve the effects of large commercial benefits, improved fault tolerance, and rapid and accurate investment

Inactive Publication Date: 2019-12-03
QI AUTOMOTIVE CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In this context, customer purchasing behavior, demand patterns, and market trends are constantly evolving and changing. Traditional product research and life cycle analysis methods cannot be efficiently completed.

Method used

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  • Product life cycle analysis method and system based on big data and storage medium
  • Product life cycle analysis method and system based on big data and storage medium
  • Product life cycle analysis method and system based on big data and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0066] According to the present invention, refer to the appended Figure 1-4 , taking the air pump assembly as an example, implementing a product life cycle analysis method based on big data, including the following steps:

[0067] S1. Data acquisition step: acquire the data information of the air pump assembly;

[0068] S2. Data processing steps: including data cleaning, data classification, and labeling;

[0069] S3. Model analysis step: including establishing an index system, model learning, and model analysis.

[0070] Data sources can be selected from corporate official websites, customs, 4S stores, and sales order feedback. Such as figure 2 As shown, in the data acquisition step, the company's product data information is entered into the database; the product data information from the customs and 4S stores is extracted into the database using java programs or Sqoop tools; Unstructured data is captured by web spider technology and the acquired page information is sto...

Embodiment 2

[0086] Similar to Embodiment 1, the difference lies in that: after the model is established, the historical data is used to carry out machine learning and verification on the model, and the model is further optimized to improve the prediction accuracy. Historical data information includes sales growth rate, product category, number of competitors and new entrants, as shown in Table 1 below.

[0087] Taking the diverter as an example, diverter 1 represents the first generation product, diverter 2 represents the second generation product, and diverter 3 represents the third generation product. The data matrix of product category and industry data is listed.

[0088] product category sales growth rate number of competitors New entrants steering gear 1 -18% 101 0 steering gear 2 10% 313 68 steering gear 3 8% 72 5

[0089] According to historical data statistics, it can be found that the steering gear 1 is already in a recession, and the ...

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PUM

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Abstract

The invention provides a product life cycle analysis method and system based on big data, and a storage medium. The method comprises the following steps: S1, a data acquisition step: acquiring data information of each product; S2, a data processing step which comprises data cleaning, data classification and label addition; S3, a model analysis step: establishing an index system, constructing a model and analyzing the model; wherein the model adopts an extended Bass-e model. A big data thinking mode is introduced into traditional market research, product life cycle analysis is researched for abig data visual field, and by comprehensively and accurately collecting product data information, data mining and processing are enhanced, and real market requirements are analyzed and predicted. A company can accurately grasp the product period and carry out research and development layout in advance, so that rapid and accurate investment is realized when market requirements exist, continuous andstable supply is ensured, and production cost is greatly reduced.

Description

technical field [0001] The invention belongs to the technical field of the Internet, and in particular relates to a big data-based product life cycle analysis method, system and storage medium. Background technique [0002] As a relatively large means of transportation, automobiles involve tens of thousands of spare parts, and the categories and models are complex. Traditional auto parts include common maintenance parts, wearing parts, non-wearing parts that are rarely replaced, and accident parts that need to be replaced after an accident. Among the four types of accessories mentioned above, although the replacement frequency of non-wearing parts is low, due to the high unit price of accessories, the value of accessories in the aftermarket accounts for the highest proportion, and the circulation is the most difficult. For companies that focus on the non-consumable parts market, the main bottleneck and challenge at present lies in the wide variety of non-consumable parts, t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q30/02G06F16/215G06F16/2458G06F16/35
CPCG06F16/215G06F16/2465G06F16/35G06Q10/0639G06Q30/0201
Inventor 赵彩辉
Owner QI AUTOMOTIVE CO LTD
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