Improved product quality abnormal data FP-Growth correlation analysis method

A correlation analysis and product quality technology, applied in data processing applications, electronic digital data processing, digital data information retrieval, etc., can solve the problem of lack of in-depth data analysis and data mining for data and quality inspection data, and insufficient production data Use and other issues

Pending Publication Date: 2019-10-08
FUDAN UNIV
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  • Description
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Problems solved by technology

[0003] Most large-scale manufacturing enterprises have successively realized the automation and informatization of production, and accumulated a large amount of production data in the production and manufac

Method used

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  • Improved product quality abnormal data FP-Growth correlation analysis method
  • Improved product quality abnormal data FP-Growth correlation analysis method
  • Improved product quality abnormal data FP-Growth correlation analysis method

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Experimental program
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Embodiment Construction

[0046] The present invention will be described in further detail below in conjunction with the implementation examples.

[0047] 1. Improvement of the FP-Tree data structure in the FP-Growth algorithm: When executing the FP-Tree construction algorithm, the optimized item header table is used to avoid cumbersome loop traversal operations, and the specific execution is performed according to the code in Appendix 2.

[0048] 2. Improvement of FP-Growth algorithm parallelization strategy:

[0049] In the second step, first, through flatMap conversion, each transaction in the transaction set is converted into the form of , where key represents the transaction, and the value of value is set to 1. On this basis, use the reduceByKey operation to make the key value the same The values ​​of all elements are summed to obtain a data set stored in the format of , named Trans; again use flatMap to split the key of Trans into Shard the data, and then use the reduceByKey conversion to sum t...

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Abstract

The invention belongs to the technical field of industrial big data, and particularly relates to an improved product quality abnormal data FP-Growth correlation analysis method. The main content of the method of the invention comprises the product quality abnormal data association analysis characterized in that the multi-factor association analysis is carried out on the product production qualityand the production process data, a series of association rules are mined based on a multi-factor association analysis algorithm, the potential problems of some indexes in the quality data are found, and the factors causing product quality abnormal influences are conveniently positioned; the FP-Tree data structure improvement characterized in that a field tail _ Link is newly added on the basis ofan FP-Tree frequent item header table, and the current last node of each data item is recorded, so that the repeated traversal linked list operation when a new node is inserted is avoided, and the FP-Tree tree building efficiency is improved; the improvement of the parallelization strategy of the FP-Growth association algorithm characterized in that an FP-Growth algorithm mining frequent mode is executed parallelly on each transaction set group to break through the original mode of firstly building a tree and then parallelizing, so that the calculation efficiency of each node in the parallelization execution is improved.

Description

technical field [0001] The invention belongs to the technical field of industrial big data, and in particular relates to an FP-Growth correlation analysis method for abnormal product quality data. Background technique [0002] The "big data era" we live in is an intelligent era that has been upgraded and evolved from the information age. The "big data era" is no longer limited to information sharing, but more focused on the intelligent application of information. In this era, data is no longer a worthless "by-product" of social production; on the contrary, data has become a renewable and valuable means of production. Massive data contains massive amounts of information and hides huge value. Through the analysis and mining of data, not only can the existing phenomena be described and explained in depth, but even the future can be predicted. Big data has penetrated into all aspects of people's lives, endowing people's lives with more intelligence and convenience. [0003] M...

Claims

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Application Information

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IPC IPC(8): G06F16/2458G06Q10/06G06Q50/04
CPCG06F16/2465G06Q10/06395G06Q50/04Y02P90/30
Inventor 李敏波丁铎
Owner FUDAN UNIV
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