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Technical Development of Defect Early Warning System

Difficult Technology Development

Firstly, the engineering model should be established, and the engineering model affecting defects and defective products should be established according to the on-site process, products, equipment and automation conditions of the enterprise. Have a deep understanding of the engineering fields of process, product, equipment and automation. It is best to have worked in various fields on site for several years; If this technical level is not reached, the resulting system will have one short board or another. Most of the on-site problems are comprehensive. At first glance, a considerable part of the problems are difficult to be solved directly by basic theory; But in fact, there may be problems in the coordination of various fields, which is difficult for people with only one aspect of professional knowledge to understand.

Based on the existing data of the factory, such as MES data, industrial Internet data or other data collected with SCADA, machine learning can fully bind the established model with the current situation of process, products, equipment and automation of the production line, that is, the accuracy of the model on the production line of the collected data is very high.  

The most difficult is the system architecture of software and field engineering problems. In addition to the design of normal software architecture, such as data structure, database, class, function, module and software interface, it is particularly necessary to collect all relevant scenario use cases, such as compiling the current work of all engineers on site into intelligent software! If these scenario use cases are not collected comprehensively, the system will not react or react improperly when encountering scenario use cases that have not been collected, and the processing instructions obtained by the automation system are incorrect, which will cause accidents! After the scene use cases are fully collected, the system should be able to automatically form an intelligent alarm, and when the operator takes action, the system should be able to respond in time and take follow-up actions. In particular, the system should guide the on-site operator how to deal with relevant problems.


Technical Development Stage of Defect Early Warning System

The technical development of defect early warning system, taking lithium battery as an example, should include three crucial stages:
(1) Early model development, including more than 100 sets of models in various stages of lithium battery manufacturing, see Overview of lithium battery manufacturing technology development;
(2) The development of three contracts for the existing lithium battery production line of a large electric vehicle / lithium battery enterprise, including data acquisition and application of MES data, defect prediction and corresponding machine learning, as well as knife gap prediction, soft measurement and corresponding knife gap machine learning, as well as the research and development of knife gap measurement hardware, see Development case of lithium battery defect early warning system;
(3) Customized development for various enterprises, production lines and various production processes, such as interface development for different MES software packages, see item by item below.

Interface Development of Existing Defect Early Warning System Installed in Each Data System

The focus here is to add the installation interface with each MES system / each industrial Internet platform / each SCADA data system for the defect early warning system, so that it can be fully integrated into the existing data systems. At present, various suppliers have developed a large number of data systems. For example, there are about 20000 manufacturing execution systems MES. About 10 types of input interfaces can be developed, and the interface variables are exposed, so that users can connect with the system through subroutines.

Setting Module of Customized Model of Defect Early Warning System

The defect early warning system sets specific modules for adding customized models during development. Metal Pass company has designed and developed a number of proprietary customized models, which are designed into corresponding modules. Based on the customer's on-site situation, they are combined into the customized module of defect early warning system during installation. The company provides different versions of the system and adds customized models. For common sections, the company gives priority to setting up many versions of defect early warning system, and gives priority to adding the customized model of common sections to the defect early warning system. During installation, you only need to select the corresponding version in the list.

When there is a need for customized models on site, but the company has never encountered similar customized models in previous projects, according to the advantages of experts in the team in model development, we can carry out certain customized model development, and the newly developed model module can be added to the defect early warning system. Our team has developed more than 100 models of emerging industries and more than 100 models of traditional industries, a total of more than 200 sets.

Service Name: customized development, installation and application of defect early warning system

Manufacturing industry, especially manufacturing industry, whose quality needs to be improved

Innovation: Key Technologies of Smart Manufacturing, such as engineering modeling and modeling of vital characteristics in production, such as product quality or defective rate

Defect Warning System Series
Development case of lithium battery defect early warning system
Function and application of defect early warning system products
Customer requirements of defect early warning system
Technical consultation of defect data based on Prediction
Production process optimization based on defect early warning
Introduction to defect early warning system technology


Tech & Products

   Situation, Metauniverse, 4.0 brains, Smart manug, Equipment Softw.
Defect warning, Defect detection, Li-battery, Level 2 platform


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