Implementation strategy of data management in the

2022-08-17
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The implementation strategy of experimental data management

background overview

the product development process of modern industrial departments is usually composed of three aspects: design, simulation and experiment, and each aspect of the work produces a large amount of data. How to manage these three aspects of data is the key to ensure the success of product development, improve work efficiency and form lean manufacturing

for test engineers and managers, a key problem is that automated test sites produce a large number of test data, which is difficult to manage and process. In order to deal with test 3, choose trouser shaped samples: using trouser shaped samples is insensitive to the length of the incision. The test data requires special technicians and takes a lot of time to analyze and sort out reports useful to users. At the same time, a large number of test data are shelved and cannot be processed in time. Over time, they are simply discarded

therefore, data management technology, especially test data management technology, has become one of the most critical technologies in the process of product development. Because every work of product design, simulation and experiment will produce massive data, and the data has its own characteristics and diversity, so every aspect of data needs special software tools to manage. More importantly, the three major data management technologies need to manage not only data, but also processes, as well as pre-processing and post-processing of data. Their professionalism and uniqueness determine that the three aspects of data management need different software tools to achieve. At the same time, in the process, how to achieve secure system data access control is also one of the key technologies

over the years, various mainstream CAD software manufacturers have developed their own management tool software for product design data to manage product design data and processes, which is known as PDM. Some manufacturers also provide simulation data management software (SDM) to manage simulation data and processes

however, there is a lack of unified and effective management tools for the management of test data. A large number of test and test data are basically stored, sorted, exchanged and released in the form of various electronic documents. This "documented" data management method has serious shortcomings

low efficiency: experimenters often spend a lot of time looking for required test data from massive data files. Because the file type and data format of the test data are inconsistent, the test personnel need to filter and sort out the data manually, which is a very time-consuming and labor-intensive process

easy to make mistakes: due to the existence of a large number of manual operations, it is inevitable that errors will occur in a certain link. At least, the welding adopts carbon dioxide made in the air and inert gas to protect the weld, which will reduce the effectiveness of the test, and at least damage the accuracy of the test, causing greater adverse consequences

low data utilization: due to the low efficiency and easy error detection caused by manual operation, the test data are often shelved after the completion of a test, which is difficult to provide reference for similar tests in the future

unable to carry out data mining: the massive experimental data obtained by spending a lot of manpower, material resources, financial resources and time to complete the experiment contains rich information, and simple file management cannot reveal those valuable information through data mining

poor security and confidentiality: the test data stored in the form of files are vulnerable to unauthorized access and modification, and lead to the disclosure of important data

there have always been two differences on the scheme of experimental data management: choose general software or develop by yourself. Due to different specific conditions of enterprises, different sources of experimental data and different management requirements, many enterprises choose the path of customized development

system features

our test data management system, as the basic framework of test data management, is an in-house software product developed based on the accumulation of more than ten years of experience. According to the needs of customers, we can quickly customize a test data management platform with strong functions, flexibility and stable performance. In view of the challenges faced by test data management, the design of the test data management system platform has the following unique technical features: metadata driven software architecture; Object oriented data model; Virtual XML database

benefits for customers

the benefits that the test data management scheme can bring to users' business mainly include:

various test and measurement data are stored in a massive database in the form of records, eliminating the trouble of managing a large number of data files; Data can be expanded according to different user sizes and can be expanded smoothly

by classifying the test and measurement data, we can quickly and accurately find the required data from the massive data

based on database operation, it can fully and effectively carry out various post-processing of test and measurement data, avoiding the previous manual operation links based on files, thus greatly improving work efficiency and reducing errors

the system administrator can set a thorough and multi-level authority control strategy for the data in the system, as well as the data backup and recovery mechanism, ensuring the security and disaster resistance of the data

I'll show you the following information in detail. After a period of trial operation and operation, users believe that the test data management system has the following characteristics:

practicality: the system can really flexibly deal with various complex problems encountered in actual use, and there are no unnecessary restrictions to restrict the application scope of the system. The operation is simple and easy to learn. Engineers and technicians can complete all kinds of work in the shortest time and the simplest steps, which reduces the manual operation components to the greatest extent and greatly improves their work efficiency

Maintainability: the system based on metadata driven software architecture provides strong flexibility and adaptability with a total project investment of about 57.05 million yuan. By using graphical tools, engineers and technicians can define and modify the business needs of their related majors, and the system can automatically adjust and adapt without the help of computer software engineers. This feature greatly enhances the maintainability and vitality of the system

security: the system can meet the extremely high requirements for data security and confidentiality. Its careful and meticulous data authority control mechanism can ensure the security of data without affecting the sharing of data. The data backup and recovery mechanism of the system can backup and recover the data of various disciplines independently without mutual influence. (end)

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