Failure mode and effects analysis （FMEA） offers a quick and easy way for identifying ranking-order for all failure modes in a system or a product. In FMEA the ranking methods is so called risk priority number （RPN...Failure mode and effects analysis （FMEA） offers a quick and easy way for identifying ranking-order for all failure modes in a system or a product. In FMEA the ranking methods is so called risk priority number （RPN）, which is a mathematical product of severity （S）, occurrence （0）, and detection （D）. One of major disadvantages of this ranking-order is that the failure mode with different combination of SODs may generate same RPN resulting in difficult decision-making. Another shortfall of FMEA is lacking of discerning contribution factors, which lead to insufficient information about scaling of improving effort. Through data envelopment analysis （DEA） technique and its extension, the proposed approach evolves the current rankings for failure modes by exclusively investigating SOD in lieu of RPN and to furnish with improving sca.les for SOD. The purpose of present study is to propose a state-of-the-art new approach to enhance assessment capabilities of failure mode and effects analysis （FMEA）. The paper proposes a state-of-the-art new approach, robust, structured and useful in practice, for failure analysis.展开更多
To evaluate the relative effectiveness of the input and output of the high-tech industry in China＇s 31 provinces （including municipalities and autonomous regions）, DEA evaluation model was constructed using data en...To evaluate the relative effectiveness of the input and output of the high-tech industry in China＇s 31 provinces （including municipalities and autonomous regions）, DEA evaluation model was constructed using data envelopment analysis （DEA）, and DEA evaluation model was solved using Deap2.1 software, for the purpose of obtaining the DEA efficiency and the non-DEA efficiency in all the provinces （including municipalities and autonomous regions）. Then, the comprehensive efficiency, technical efficiency, scale efficiency, scale return, and projection analysis were analyzed. Finally, the provinces of the non-DEA efficiency are sorted according to three efficiencies, and also a goal of improvement is proposed for the purpose of expanding technology investment in the provinces of the DEA efficiency.展开更多
To investigate the long-term operating efficiencies of container ports, we extend the work of previous researches to present a new systemic and improved method of data envelopment analysis （DEA）-based Malmquist prod...To investigate the long-term operating efficiencies of container ports, we extend the work of previous researches to present a new systemic and improved method of data envelopment analysis （DEA）-based Malmquist productivity index （MPI） in this paper. An approach based on both panel data and multi-inputs/outputs is considered comprehensively, and aims at measuring the operating efficiencies of 10 leading container ports in China from 2001 to 2006 by applying this new systematic influence factor of total factor productivity change is the calculation method. The results illustrate that the main technology change, and the container transportation of these 10 ports is on the healthy development status and will recover and grow reposefully in the following years展开更多
This paper considers the problem of evaluating efficiency of Decision Making Units （DMUs） with network structures of divisions by the Data Envelopment Analysis （DEA） model. All divisions in the network are under a...This paper considers the problem of evaluating efficiency of Decision Making Units （DMUs） with network structures of divisions by the Data Envelopment Analysis （DEA） model. All divisions in the network are under a decentralized authority organiza- tion. That is, each division in a decision making unit has its own authority to adjust its input and output. By incorporating the division operations in the DEA model, we discuss the sufficient and necessary conditions for a DMU to be network efficient in series structure and general structure respectively.展开更多
In standard data envelopment analysis （DEA） models, inefficient decision-making units （DMUs） should change their inputs and outputs arbitrarily to meet the efficient frontier. However, in many real applications of...In standard data envelopment analysis （DEA） models, inefficient decision-making units （DMUs） should change their inputs and outputs arbitrarily to meet the efficient frontier. However, in many real applications of DEA, because of some limitations in resources and DMU＇s ability, these variations cannot be made arbitrarily. Moreover, in some situations, undesirable factors with different disposability, strong or weak disposability, are found. In this paper, a DEA-based model is proposed to determine the relative efficiency of DMUs in such a restricted environment and in presence of undesirable factors. Indeed, variation levels of inputs and outputs are pre-defined and are considered to evaluate the performance of DMUs. Numerical examples are utilized to demonstrate the approach.展开更多
文摘Failure mode and effects analysis （FMEA） offers a quick and easy way for identifying ranking-order for all failure modes in a system or a product. In FMEA the ranking methods is so called risk priority number （RPN）, which is a mathematical product of severity （S）, occurrence （0）, and detection （D）. One of major disadvantages of this ranking-order is that the failure mode with different combination of SODs may generate same RPN resulting in difficult decision-making. Another shortfall of FMEA is lacking of discerning contribution factors, which lead to insufficient information about scaling of improving effort. Through data envelopment analysis （DEA） technique and its extension, the proposed approach evolves the current rankings for failure modes by exclusively investigating SOD in lieu of RPN and to furnish with improving sca.les for SOD. The purpose of present study is to propose a state-of-the-art new approach to enhance assessment capabilities of failure mode and effects analysis （FMEA）. The paper proposes a state-of-the-art new approach, robust, structured and useful in practice, for failure analysis.
文摘To evaluate the relative effectiveness of the input and output of the high-tech industry in China＇s 31 provinces （including municipalities and autonomous regions）, DEA evaluation model was constructed using data envelopment analysis （DEA）, and DEA evaluation model was solved using Deap2.1 software, for the purpose of obtaining the DEA efficiency and the non-DEA efficiency in all the provinces （including municipalities and autonomous regions）. Then, the comprehensive efficiency, technical efficiency, scale efficiency, scale return, and projection analysis were analyzed. Finally, the provinces of the non-DEA efficiency are sorted according to three efficiencies, and also a goal of improvement is proposed for the purpose of expanding technology investment in the provinces of the DEA efficiency.
基金the National Natural Science Foundation of China (No. 50578030)
文摘To investigate the long-term operating efficiencies of container ports, we extend the work of previous researches to present a new systemic and improved method of data envelopment analysis （DEA）-based Malmquist productivity index （MPI） in this paper. An approach based on both panel data and multi-inputs/outputs is considered comprehensively, and aims at measuring the operating efficiencies of 10 leading container ports in China from 2001 to 2006 by applying this new systematic influence factor of total factor productivity change is the calculation method. The results illustrate that the main technology change, and the container transportation of these 10 ports is on the healthy development status and will recover and grow reposefully in the following years
基金The project is supported by National Natural Science Foundation of China（70531040, 70871114）, the 985 Research Grant of Renmin University of China, and The Hong Kong CERG Research Fund PolyU 5485/09H.
文摘This paper considers the problem of evaluating efficiency of Decision Making Units （DMUs） with network structures of divisions by the Data Envelopment Analysis （DEA） model. All divisions in the network are under a decentralized authority organiza- tion. That is, each division in a decision making unit has its own authority to adjust its input and output. By incorporating the division operations in the DEA model, we discuss the sufficient and necessary conditions for a DMU to be network efficient in series structure and general structure respectively.
文摘In standard data envelopment analysis （DEA） models, inefficient decision-making units （DMUs） should change their inputs and outputs arbitrarily to meet the efficient frontier. However, in many real applications of DEA, because of some limitations in resources and DMU＇s ability, these variations cannot be made arbitrarily. Moreover, in some situations, undesirable factors with different disposability, strong or weak disposability, are found. In this paper, a DEA-based model is proposed to determine the relative efficiency of DMUs in such a restricted environment and in presence of undesirable factors. Indeed, variation levels of inputs and outputs are pre-defined and are considered to evaluate the performance of DMUs. Numerical examples are utilized to demonstrate the approach.
