Data mining analysis method applied to sandwich production control system

By applying technical means such as stream data processing and deep learning in the sandwich production control system, the problem that traditional methods are difficult to meet modern production needs is solved, and the improvement of production efficiency and quality and cost reduction are achieved.

CN119721381APending Publication Date: 2025-03-28GUANGZHOU TIANYI FOOD CO LTD
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Patent Information

Application Number
CN202411875799.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-19
Publication Date
2025-03-28

AI Technical Summary

Technical Problem

Traditional manual operation and empirical judgments are difficult to meet the high requirements for product quality and production speed in modern sandwich production, and existing data mining technology is rarely used in sandwich production control systems.

Method used

A variety of technical means are adopted, including streaming data processing, deep learning, computer vision, optimization algorithms and association analysis algorithms, to collect and analyze historical and real-time data of the sandwich production control system, and to carry out production status prediction, quality prediction, defect detection, fault prediction and production scheduling optimization.

Benefits of technology

It improves the production efficiency and quality of sandwiches, reduces production costs, improves the intelligence level of production management, and realizes optimization of the production process, precise quality control and effective cost management.

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Abstract

The invention discloses a data mining analysis method applied to a sandwich production control system, and relates to the technical field of data mining. The method comprises the following steps: collecting multi-source data of a sandwich production control system; predicting the production state of the production control system by adopting a stream data processing technology; performing quality prediction on the sandwich by adopting a deep learning algorithm; performing defect detection on the sandwich by using a computer vision technology; performing fault prediction by adopting a deep learning algorithm and a correlation analysis algorithm; optimizing the production scheduling of each production link by adopting an optimization algorithm; and product data of the sandwich are collected and product traceability is carried out. On the basis of data mining, various technologies are adopted to process and analyze the mined data, so that the production efficiency and quality are improved, and the production cost is reduced; by predicting the production quality and carrying out defect detection and fault detection, the production management level is improved, and the optimization of the production process, the accurate control of the quality and the effective management of the cost are realized.
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