A Product Life Cycle Information Management System Infrastructure with CAD/CAE/CAM, Task Automation, and Intelligent Support Capabilities

Author(s):  
Harold P. Frisch
2021 ◽  
Vol 4 (1) ◽  
pp. 5-13
Author(s):  
Erliang Huang

Objective: To establish a total life cycle information management system for medical equipment based on our hospital’s actual situation. Methods: Per the definition of the total life cycle for the particular item of medical equipment, the function modules were designed and distributed according to different staff postings and then implemented on the WeChat public account-a series of API and services to develop custom features, a mobile app, and a computer web browser. Results: After implementation, the system can cover a series of management stages of the entire life cycle for medical equipment and the information exchanged among various stages. The relevant staff in different posts can operate the medical equipment management information on any of the three platforms. Conclusion: The improvement and efficiency aid staff in various settings in managing medical equipment and medical behaviors and patient safety is increased.


2022 ◽  
Vol 13 (1) ◽  
pp. 1-21
Author(s):  
Zhihan Lv ◽  
Ranran Lou ◽  
Hailin Feng ◽  
Dongliang Chen ◽  
Haibin Lv

Two-dimensional 1 arrays of bi-component structures made of cobalt and permalloy elliptical dots with thickness of 25 nm, length 1 mm and width of 225 nm, have been prepared by a self-aligned shadow deposition technique. Brillouin light scattering has been exploited to study the frequency dependence of thermally excited magnetic eigenmodes on the intensity of the external magnetic field, applied along the easy axis of the elements. Scientific information technology has been developed rapidly. Here, the purposes are to make people's lives more convenient and ensure information management and classification. The machine learning algorithm is improved to obtain the optimized Light Gradient Boosting Machine (LightGBM) algorithm. Then, an Android-based intelligent support information management system is designed based on LightGBM for the big data analysis and classification management of information in the intelligent support information management system. The system is designed with modules of employee registration and login, company announcement notice, attendance and attendance management, self-service, and daily tools with the company as the subject. Furthermore, the performance of the constructed information management system is analyzed through simulations. Results demonstrate that the training time of the optimized LightGBM algorithm can stabilize at about 100s, and the test time can stabilize at 0.68s. Besides, its accuracy rate can reach 89.24%, which is at least 3.6% higher than other machine learning algorithms. Moreover, the acceleration efficiency analysis of each algorithm suggests that the optimized LightGBM algorithm is suitable for processing large amounts of data; its acceleration effect is more apparent, and its acceleration ratio is higher than other algorithms. Hence, the constructed intelligent support information management system can reach a high accuracy while ensuring the error, with apparent acceleration effect. Therefore, this model can provide an experimental reference for information classification and management in various fields.


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