The Experts below are selected from a list of 114 Experts worldwide ranked by ideXlab platform
Rong Pang - One of the best experts on this subject based on the ideXlab platform.
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Research on equipment Maintenance decision system based on health management
2009 8th International Conference on Reliability Maintainability and Safety, 2009Co-Authors: Mei Zhao, Liqing Rong, Rong PangAbstract:This paper addresses the importance of equipment health management integrated into the activities of equipment Maintenance and management. Firstly, the equipment health management is defined and its main activities are analyzed, including analyzing equipment health factors, processing health data, evaluating and predicting health condition, and solving health problems. Then, a flexible software frame for the equipment health management is constructed with a proper consideration of the requirements of high integration in technologies for complex equipments. A variety of data necessary to support equipment Maintenance decision optimization is described, such as fundamental data, condition data, Maintenance Record data and decision model data. Furthermore, the relationship of important functional modules is depicted. Finally, with the case of equipment Maintenance decision system for spaceflight launch site based on the health management activities and the flexible software framework, this paper indicates differences and improvements of the system contrasting with other existing systems.
Zhong Shanshan - One of the best experts on this subject based on the ideXlab platform.
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digitization management of medical equipment Maintenance Record
Chinese Medical Equipment Journal, 2012Co-Authors: Zhong ShanshanAbstract:Objective To realize the digitization management of medical equipment Maintenance Record.Methods The "Maintenance Record" module was added to the primary equipment management software.The user purview was set up,and the Maintenance engineer was encouraged to fill in the Record timely,correctly and comprehensively.Results The digitization management of medical equipment Maintenance Record was realized,using which the Maintenance Records could be timely,accurately collected.Conclusion It's possible to achieve medical equipment Maintenance Records digital management in a digital hospital with the appropriate incentive system,which possess important promotive function to the Maintenance management,equipment evaluation and decision-making of the hospital.
Jun Wu - One of the best experts on this subject based on the ideXlab platform.
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The design of heavy machine's fault diagnosis prototype system based on mixed expert system
2010 International Conference on Mechanic Automation and Control Engineering, 2010Co-Authors: Chao Deng, Yuan-hang Wang, Jun Wu, Yao XiongAbstract:Beginning with the simple introduction of method and current situation about heavy machine and its fault diagnosis, this paper puts forward the method of fault diagnosis based on mixed expert system, which uses the rules and cases. The architecture and diagnosis flow of the system are both constructed. Then the knowledge base of heavy machine's fault diagnosis and inference engine are mainly set up, including the rule base and case base which are respectively grounded on the “Structure Fault Tree” and breakdown Maintenance Record. Finally, the prototype system is designed.
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A mixed expert system for fault diagnosis
2010 IEEE 17Th International Conference on Industrial Engineering and Engineering Management, 2010Co-Authors: Yuan-hang Wang, Chao Deng, Yao Xiong, Jun WuAbstract:Because of the high structure complexity and variety of working condition, it is greatly difficult to fault diagnosis for heavy machines. This paper puts forward a method of fault diagnosis based on mixed expert system, which uses the rules and cases. The architecture and diagnosis flow of the system are both proposed. The knowledge database of fault diagnosis of heavy machine are mainly set up, including the rule database and case database which are respectively based on the “Structure Fault Tree” and breakdown Maintenance Record. Finally, the prototype system is designed.
Yao Xiong - One of the best experts on this subject based on the ideXlab platform.
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The design of heavy machine's fault diagnosis prototype system based on mixed expert system
2010 International Conference on Mechanic Automation and Control Engineering, 2010Co-Authors: Chao Deng, Yuan-hang Wang, Jun Wu, Yao XiongAbstract:Beginning with the simple introduction of method and current situation about heavy machine and its fault diagnosis, this paper puts forward the method of fault diagnosis based on mixed expert system, which uses the rules and cases. The architecture and diagnosis flow of the system are both constructed. Then the knowledge base of heavy machine's fault diagnosis and inference engine are mainly set up, including the rule base and case base which are respectively grounded on the “Structure Fault Tree” and breakdown Maintenance Record. Finally, the prototype system is designed.
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A mixed expert system for fault diagnosis
2010 IEEE 17Th International Conference on Industrial Engineering and Engineering Management, 2010Co-Authors: Yuan-hang Wang, Chao Deng, Yao Xiong, Jun WuAbstract:Because of the high structure complexity and variety of working condition, it is greatly difficult to fault diagnosis for heavy machines. This paper puts forward a method of fault diagnosis based on mixed expert system, which uses the rules and cases. The architecture and diagnosis flow of the system are both proposed. The knowledge database of fault diagnosis of heavy machine are mainly set up, including the rule database and case database which are respectively based on the “Structure Fault Tree” and breakdown Maintenance Record. Finally, the prototype system is designed.
Mei Zhao - One of the best experts on this subject based on the ideXlab platform.
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Research on equipment Maintenance decision system based on health management
2009 8th International Conference on Reliability Maintainability and Safety, 2009Co-Authors: Mei Zhao, Liqing Rong, Rong PangAbstract:This paper addresses the importance of equipment health management integrated into the activities of equipment Maintenance and management. Firstly, the equipment health management is defined and its main activities are analyzed, including analyzing equipment health factors, processing health data, evaluating and predicting health condition, and solving health problems. Then, a flexible software frame for the equipment health management is constructed with a proper consideration of the requirements of high integration in technologies for complex equipments. A variety of data necessary to support equipment Maintenance decision optimization is described, such as fundamental data, condition data, Maintenance Record data and decision model data. Furthermore, the relationship of important functional modules is depicted. Finally, with the case of equipment Maintenance decision system for spaceflight launch site based on the health management activities and the flexible software framework, this paper indicates differences and improvements of the system contrasting with other existing systems.
