With the development of central-private enterprises integration,selecting suitable key suppliers are able to provide core components for smart complex equipment.We consider selecting suitable key suppliers from matchi...With the development of central-private enterprises integration,selecting suitable key suppliers are able to provide core components for smart complex equipment.We consider selecting suitable key suppliers from matching perspective,for it not only satisfies natural development of smart complex equipment,it is also a good implementation of equipment project in central-private enterprises integration context.In in this paper,we carry out two parts of research,one is evaluation attributes based on comprehensive analysis,and the other is matching process between key suppliers and core components based on the matching attribute.In practical analysis process,we employ comprehensive evaluated analysis methods to acquire relevant attributes for the matching process that follows.In the analysis process,we adopt entropy-maximum deviation method(MDM)-decision-making trial and evaluation laboratory(DEMATEL)-technique for order preference by similarity to an ideal solution(TOPSIS)to obtain a comprehensive analysis.The entropy-MDM is applied to get weight value,DEMATEL is utilized to obtain internal relations,and TOPSIS is adopted to get ideal evaluated solution.We consider aggregating two types of evaluation information according to similarities of smart complex equipment based on the combination between geometric mean and arithmetic mean.Moreover,based on the aforementioned attributes and generalized power Heronian mean operator,we aggregate preference information to acquire relevant satisfaction degree,then combine the constructed matching model to get suitable key supplier.Through comprehensive analysis of selecting suitable suppliers,we know that two-sided matching and information aggregation can provide more research perspectives for smart complex equipment.Through analysis for relevant factors,we find that leading role and service level are also significant for the smart complex equipment development process.展开更多
The determination of maintenance mode of complex equipment in nuclear power plant is an essential work for reliability analysis and maintenance decision. Currently, the main decision method of maintenance mode is reli...The determination of maintenance mode of complex equipment in nuclear power plant is an essential work for reliability analysis and maintenance decision. Currently, the main decision method of maintenance mode is reliability centered maintenance( RCM) logic decision-making process, but the process is a qualitative analysis process. Based on a comprehensive analysis of factors affecting equipment reliability and maintenance work, it adopts a fuzzy synthesis decision method to establish a maintenance decision model,which uses the maximum subordination principle and expert assessment method to determine the maintenance mode of complex equipment. Combined with a concrete example of generators in nuclear power plant,a description of maintenance decision method was proposed in the application of complex equipment. The research shows that the method is feasible and reliable.展开更多
In the industrial engineering, the maintenance and logistics support process is one of the key factors for the performance of equipment. Bill of materials( BOM) describes all the components in product and internal hie...In the industrial engineering, the maintenance and logistics support process is one of the key factors for the performance of equipment. Bill of materials( BOM) describes all the components in product and internal hierarchal relationships as a structured tree.In order to gain all required maintenance information for complex equipment which is complex,the modeling and the application of maintenance BOM are introduced in this paper. Because of the simple structure and the wide function,IDEF0 is presented to build the model of maintenance BOM. The modeling approach can gather the maintenance information conveniently based on other BOMs,and applications of maintenance BOM are widely,particularly,in maintenance and inventory management.展开更多
An equipment maintenance system is naturally a complex dynamical system. The effective mamanagement must be based on the knowledge of the system＇s intrinsic dynamics. And the strueture of the maintenance system deter...An equipment maintenance system is naturally a complex dynamical system. The effective mamanagement must be based on the knowledge of the system＇s intrinsic dynamics. And the strueture of the maintenance system determines its behavior. This paper analyzes the basic structures and elements of a maintenance system for complex multi-components equipment. The maintenance system is considered as a dynamic system whose behavior is influenced by its structure＇s feedback and interaction, and the system＇s available resources. Building the dynamical model with Simulink, we show some results about the maintenance system＇s nonlinear dynamics, ods. The model can be used for understanding and which operational adjustments of maintenance which are never given by stochastic process methdetermining maintenance system behavior, towards n of maintenance requirements and timely supply of maintenance resources can be made in a more informed way.展开更多
Complex equipment refers to special equipment that differs from general equipment.The collaborative development work of complex equipment in the military-civilian integration context involves numerous suppliers.We con...Complex equipment refers to special equipment that differs from general equipment.The collaborative development work of complex equipment in the military-civilian integration context involves numerous suppliers.We consider a two-tier supply network composed of different suppliers that participate in the development work to assemble complex equipment that cooperate with a main-manufacturer regarding spare parts.However,in terms of spare parts,a substitution relationship exists in assembly work for complex equipment.Hence,selecting a suitable supplier from the matching process between suppliers and spare parts under a military-civilian integration background is essential.This study considers three main analyses to obtain a suitable supplier for the development work of complex equipment.First,we construct a two-stage model to acquire the necessary evaluation dimension for subsequent processes.Second,we examine the evaluated attributes for the matching process based on entropy-group-DEMATEL analysis.Third,we perform information aggregation for the uncertain preference information between spare parts and suppliers using a Bonferroni mean operator.Finally,an illustrative example is presented to demonstrate the whole efficiency.Through the aforementioned analysis,we can select a suitable supplier that could participate in complex equipment military-civilian collaborative development work.展开更多
In order to meet the demand of testability analysis and evaluation for complex equipment under a small sample test in the equipment life cycle, the hierarchical hybrid testability model- ing and evaluation method （HH...In order to meet the demand of testability analysis and evaluation for complex equipment under a small sample test in the equipment life cycle, the hierarchical hybrid testability model- ing and evaluation method （HHTME）, which combines the testabi- lity structure model （TSM） with the testability Bayesian networks model （TBNM）, is presented. Firstly, the testability network topo- logy of complex equipment is built by using the hierarchical hybrid testability modeling method. Secondly, the prior conditional prob- ability distribution between network nodes is determined through expert experience. Then the Bayesian method is used to update the conditional probability distribution, according to history test information, virtual simulation information and similar product in- formation. Finally, the learned hierarchical hybrid testability model （HHTM） is used to estimate the testability of equipment. Compared with the results of other modeling methods, the relative deviation of the HHTM is only 0.52%, and the evaluation result is the most accu rate.展开更多
An effective prognostic program is crucial to the predictive maintenance of complex equipment since it can improve productivity, prolong equipment life, and enhance system safety. This paper proposes a novel technique...An effective prognostic program is crucial to the predictive maintenance of complex equipment since it can improve productivity, prolong equipment life, and enhance system safety. This paper proposes a novel technique for accurate failure prognosis based on back propagation neural network and quantum multi-agent algorithm. Inspired by the extensive research of quantum computing theory and multi-agent systems, the technique employs a quantum multi-agent strategy, with the main characteristics of quantum agent representation and several operations including fitness evaluation, cooperation, crossover and mutation, for parameters optimization of neural network to avoid the deficiencies such as slow convergence and liability of getting stuck to local minima. To validate the feasibility of the proposed approach, several numerical approximation experiments were firstly designed, after which real vibrational data of bearings from the Laboratory of Cincinnati University were analyzed and used to assess the health condition for a given future point. The results were rather encouraging and indicated that the presented forecasting method has the potential to be utilized as an estimation tool for failure prediction in industrial machinery.展开更多
文摘With the development of central-private enterprises integration,selecting suitable key suppliers are able to provide core components for smart complex equipment.We consider selecting suitable key suppliers from matching perspective,for it not only satisfies natural development of smart complex equipment,it is also a good implementation of equipment project in central-private enterprises integration context.In in this paper,we carry out two parts of research,one is evaluation attributes based on comprehensive analysis,and the other is matching process between key suppliers and core components based on the matching attribute.In practical analysis process,we employ comprehensive evaluated analysis methods to acquire relevant attributes for the matching process that follows.In the analysis process,we adopt entropy-maximum deviation method(MDM)-decision-making trial and evaluation laboratory(DEMATEL)-technique for order preference by similarity to an ideal solution(TOPSIS)to obtain a comprehensive analysis.The entropy-MDM is applied to get weight value,DEMATEL is utilized to obtain internal relations,and TOPSIS is adopted to get ideal evaluated solution.We consider aggregating two types of evaluation information according to similarities of smart complex equipment based on the combination between geometric mean and arithmetic mean.Moreover,based on the aforementioned attributes and generalized power Heronian mean operator,we aggregate preference information to acquire relevant satisfaction degree,then combine the constructed matching model to get suitable key supplier.Through comprehensive analysis of selecting suitable suppliers,we know that two-sided matching and information aggregation can provide more research perspectives for smart complex equipment.Through analysis for relevant factors,we find that leading role and service level are also significant for the smart complex equipment development process.
文摘The determination of maintenance mode of complex equipment in nuclear power plant is an essential work for reliability analysis and maintenance decision. Currently, the main decision method of maintenance mode is reliability centered maintenance( RCM) logic decision-making process, but the process is a qualitative analysis process. Based on a comprehensive analysis of factors affecting equipment reliability and maintenance work, it adopts a fuzzy synthesis decision method to establish a maintenance decision model,which uses the maximum subordination principle and expert assessment method to determine the maintenance mode of complex equipment. Combined with a concrete example of generators in nuclear power plant,a description of maintenance decision method was proposed in the application of complex equipment. The research shows that the method is feasible and reliable.
基金National Natural Science Foundation of China(No.71471147)the Basic Research Project of Natural Science in Shaanxi Province of China(No.2015JQ7273)the 111 Project of China(No.B13044)
文摘In the industrial engineering, the maintenance and logistics support process is one of the key factors for the performance of equipment. Bill of materials( BOM) describes all the components in product and internal hierarchal relationships as a structured tree.In order to gain all required maintenance information for complex equipment which is complex,the modeling and the application of maintenance BOM are introduced in this paper. Because of the simple structure and the wide function,IDEF0 is presented to build the model of maintenance BOM. The modeling approach can gather the maintenance information conveniently based on other BOMs,and applications of maintenance BOM are widely,particularly,in maintenance and inventory management.
文摘An equipment maintenance system is naturally a complex dynamical system. The effective mamanagement must be based on the knowledge of the system＇s intrinsic dynamics. And the strueture of the maintenance system determines its behavior. This paper analyzes the basic structures and elements of a maintenance system for complex multi-components equipment. The maintenance system is considered as a dynamic system whose behavior is influenced by its structure＇s feedback and interaction, and the system＇s available resources. Building the dynamical model with Simulink, we show some results about the maintenance system＇s nonlinear dynamics, ods. The model can be used for understanding and which operational adjustments of maintenance which are never given by stochastic process methdetermining maintenance system behavior, towards n of maintenance requirements and timely supply of maintenance resources can be made in a more informed way.
基金supported by the Philosophy in Colleges and Universities of Anhui Provincial Department of Education(No.2022AH050635,No.2023AH050041).
文摘Complex equipment refers to special equipment that differs from general equipment.The collaborative development work of complex equipment in the military-civilian integration context involves numerous suppliers.We consider a two-tier supply network composed of different suppliers that participate in the development work to assemble complex equipment that cooperate with a main-manufacturer regarding spare parts.However,in terms of spare parts,a substitution relationship exists in assembly work for complex equipment.Hence,selecting a suitable supplier from the matching process between suppliers and spare parts under a military-civilian integration background is essential.This study considers three main analyses to obtain a suitable supplier for the development work of complex equipment.First,we construct a two-stage model to acquire the necessary evaluation dimension for subsequent processes.Second,we examine the evaluated attributes for the matching process based on entropy-group-DEMATEL analysis.Third,we perform information aggregation for the uncertain preference information between spare parts and suppliers using a Bonferroni mean operator.Finally,an illustrative example is presented to demonstrate the whole efficiency.Through the aforementioned analysis,we can select a suitable supplier that could participate in complex equipment military-civilian collaborative development work.
基金supported by the National Defense Pre-research Foundation of China(51327030104)
文摘In order to meet the demand of testability analysis and evaluation for complex equipment under a small sample test in the equipment life cycle, the hierarchical hybrid testability model- ing and evaluation method （HHTME）, which combines the testabi- lity structure model （TSM） with the testability Bayesian networks model （TBNM）, is presented. Firstly, the testability network topo- logy of complex equipment is built by using the hierarchical hybrid testability modeling method. Secondly, the prior conditional prob- ability distribution between network nodes is determined through expert experience. Then the Bayesian method is used to update the conditional probability distribution, according to history test information, virtual simulation information and similar product in- formation. Finally, the learned hierarchical hybrid testability model （HHTM） is used to estimate the testability of equipment. Compared with the results of other modeling methods, the relative deviation of the HHTM is only 0.52%, and the evaluation result is the most accu rate.
基金Acknowledgments The research work presented in this paper was partialy supported by the National Natural Science Foundation of China （Grant No. 61173015 ＆ 61573257）.
文摘An effective prognostic program is crucial to the predictive maintenance of complex equipment since it can improve productivity, prolong equipment life, and enhance system safety. This paper proposes a novel technique for accurate failure prognosis based on back propagation neural network and quantum multi-agent algorithm. Inspired by the extensive research of quantum computing theory and multi-agent systems, the technique employs a quantum multi-agent strategy, with the main characteristics of quantum agent representation and several operations including fitness evaluation, cooperation, crossover and mutation, for parameters optimization of neural network to avoid the deficiencies such as slow convergence and liability of getting stuck to local minima. To validate the feasibility of the proposed approach, several numerical approximation experiments were firstly designed, after which real vibrational data of bearings from the Laboratory of Cincinnati University were analyzed and used to assess the health condition for a given future point. The results were rather encouraging and indicated that the presented forecasting method has the potential to be utilized as an estimation tool for failure prediction in industrial machinery.
