Sanjay Tyagi - Academia.edu (original) (raw)

Papers by Sanjay Tyagi

This paper describes a novel approach, based on intuitionistic fuzzy set theory for reliability a... more This paper describes a novel approach, based on intuitionistic fuzzy set theory for reliability analysis of series and parallel network. The triangular intuitionistic fuzzy sets are used to represent the failure possibility of each basic (terminal) event to get more comprehensive results for the failure possibility of the top event. The proposed technique is demonstrated on a web server LOG data used to illustrate HTTP (Hyper Text Transfer Protocol) failure.

Applied Mathematics, 2011

Being one of the most expensive components of an electrical power plant, the failures of a power ... more Being one of the most expensive components of an electrical power plant, the failures of a power transformer can result in serious power system issues. So fault diagnosis for power transformer is highly important to ensure an uninterrupted power supply. Due to information transmission mistakes as well as arisen errors while processing data in surveying and monitoring state information of transformer, uncertain and incomplete information may be produced. Based on these points, this paper presents an intelligent fault diagnosis method of power transformer using fuzzy fault tree analysis (FTA) and beta distribution for failure possibility estimation. By using the technique we proposed herein, the continuous attribute values are transformed into the fuzzy numbers to give a realistic estimate of failure possibility of a basic event in FTA. Further, it explains a new approach based on Euclidean distance between fuzzy numbers, to rank the basic events in accordance with their Fuzzy Importance Index.

The fuzzy sets possess natural capability to capture measurement uncertainty as a part of experim... more The fuzzy sets possess natural capability to capture measurement uncertainty as a part of experimental data. Therefore the uncertainties of various kinds involved in system failure analysis may be adequately addressed using the concept of fuzzy sets. Fonseca et al developed and implemented fuzzy reasoning algorithm via an expert system to assess the likelihood of equipment failure mode. The algorithm developed by them is a fuzzy mathematical formulation which linearly relates the presence of different failure causing factors (FCFs) categorized as critical, important and related. It has been observed that the failure data may not be collected accurately and ignorance of uncertainty of any sort may lead to substantial errors. Unlike Fonseca et al, we propose that the FCFs should be measured by a fuzzy technique with desired accuracy. Also, it is quite obvious that the weights of FCFs are vital in failure mode screening. Thus the weights of FCFs should be linguistic and to be assigned appropriate fuzzy numbers in place of crisp numbers. The proposed technique is implemented to the same example taken by Fonseca et al.

International Journal of Engineering, Science and Technology, 2010

Research in conventional fault tree analysis (FTA) is based mainly on failure probability of basi... more Research in conventional fault tree analysis (FTA) is based mainly on failure probability of basic events, which uses classical probability distributions for the failure probability of basic events. In the present paper the probabilistic consideration of basic events is replaced by possibilities, thereby leading to fuzzy fault tree analysis. Triangular and trapezoidal fuzzy numbers are used to represent the failure possibility of basic events. Since a system may have to go through different operating conditions during the design or testing phase. Thus the failure possibility of a basic event will be assigned more than one fuzzy numbers by different experts under various operating conditions. It is also well established that the selection of a fuzzy number to represent a basic event is vital in fault tree analysis. Here we developed an algorithm to find a single fuzzy number for a basic event, wherein more than one fuzzy number is assigned to that particular event. Using this algorithm, we obtain a single fuzzy number, having least variance from all fuzzy numbers assigned to the concerned event. The adequate and appropriate means and procedure for the detection of basic events having key role in the occurrence of top event in system analysis become essential. Here we have put forward an approach to rank the basic events in accordance with their importance in the occurrence of top event. This approach can be widely used to improve the reliability and to reduce the operating cost of a system. The proposed techniques are discussed and illustrated by taking an example of a nuclear power plant.

Applied Mathematics, 2014

In this paper, we investigate the reliability analysis of a powerloom plant by using interval val... more In this paper, we investigate the reliability analysis of a powerloom plant by using interval valued intuitionistic fuzzy sets (IVIFS). Herein, we modeled a powerloom plant as a gracefully degradable system having two units A(n) and B(m) connected in series. The reliability of n components of unit A and m components of unit B is assumed to be an IVIFS defined over the universe of discourse [0, 1]. Thus, the reliability of the system obtained is an IVIFS that covers the inherited uncertainty in data collection and reliability evaluation of a powerloom plant.

Microelectronics Reliability, 1995

Applied Mathematical Modelling, 2014

ABSTRACT A dual hesitant fuzzy set (DHFS) consists of two parts, that is, the membership hesitanc... more ABSTRACT A dual hesitant fuzzy set (DHFS) consists of two parts, that is, the membership hesitancy function and the nonmembership hesitancy function, supporting a more exemplary and flexible access to assign values for each element in the domain, and can handle two kinds of hesitancy in this situation. It can be considered as a powerful tool to express uncertain information in the process of group decision making. Therefore, we propose a correlation coefficient between DHFSs as a new extension of existing correlation coefficients for hesitant fuzzy sets and intuitionistic fuzzy sets and apply it to multiple attribute decision making under dual hesitant fuzzy environments. Through the weighted correlation coefficient between each alternative and the ideal alternative, the ranking order of all alternatives can be determined and the best alternative can be easily identified as well. Finally, a practical example of investment alternatives is given to demonstrate the practicality and effectiveness of the developed approach.

This paper describes a novel approach, based on intuitionistic fuzzy set theory for reliability a... more This paper describes a novel approach, based on intuitionistic fuzzy set theory for reliability analysis of series and parallel network. The triangular intuitionistic fuzzy sets are used to represent the failure possibility of each basic (terminal) event to get more comprehensive results for the failure possibility of the top event. The proposed technique is demonstrated on a web server LOG data used to illustrate HTTP (Hyper Text Transfer Protocol) failure.

Applied Mathematics, 2011

Being one of the most expensive components of an electrical power plant, the failures of a power ... more Being one of the most expensive components of an electrical power plant, the failures of a power transformer can result in serious power system issues. So fault diagnosis for power transformer is highly important to ensure an uninterrupted power supply. Due to information transmission mistakes as well as arisen errors while processing data in surveying and monitoring state information of transformer, uncertain and incomplete information may be produced. Based on these points, this paper presents an intelligent fault diagnosis method of power transformer using fuzzy fault tree analysis (FTA) and beta distribution for failure possibility estimation. By using the technique we proposed herein, the continuous attribute values are transformed into the fuzzy numbers to give a realistic estimate of failure possibility of a basic event in FTA. Further, it explains a new approach based on Euclidean distance between fuzzy numbers, to rank the basic events in accordance with their Fuzzy Importance Index.

The fuzzy sets possess natural capability to capture measurement uncertainty as a part of experim... more The fuzzy sets possess natural capability to capture measurement uncertainty as a part of experimental data. Therefore the uncertainties of various kinds involved in system failure analysis may be adequately addressed using the concept of fuzzy sets. Fonseca et al developed and implemented fuzzy reasoning algorithm via an expert system to assess the likelihood of equipment failure mode. The algorithm developed by them is a fuzzy mathematical formulation which linearly relates the presence of different failure causing factors (FCFs) categorized as critical, important and related. It has been observed that the failure data may not be collected accurately and ignorance of uncertainty of any sort may lead to substantial errors. Unlike Fonseca et al, we propose that the FCFs should be measured by a fuzzy technique with desired accuracy. Also, it is quite obvious that the weights of FCFs are vital in failure mode screening. Thus the weights of FCFs should be linguistic and to be assigned appropriate fuzzy numbers in place of crisp numbers. The proposed technique is implemented to the same example taken by Fonseca et al.

International Journal of Engineering, Science and Technology, 2010

Research in conventional fault tree analysis (FTA) is based mainly on failure probability of basi... more Research in conventional fault tree analysis (FTA) is based mainly on failure probability of basic events, which uses classical probability distributions for the failure probability of basic events. In the present paper the probabilistic consideration of basic events is replaced by possibilities, thereby leading to fuzzy fault tree analysis. Triangular and trapezoidal fuzzy numbers are used to represent the failure possibility of basic events. Since a system may have to go through different operating conditions during the design or testing phase. Thus the failure possibility of a basic event will be assigned more than one fuzzy numbers by different experts under various operating conditions. It is also well established that the selection of a fuzzy number to represent a basic event is vital in fault tree analysis. Here we developed an algorithm to find a single fuzzy number for a basic event, wherein more than one fuzzy number is assigned to that particular event. Using this algorithm, we obtain a single fuzzy number, having least variance from all fuzzy numbers assigned to the concerned event. The adequate and appropriate means and procedure for the detection of basic events having key role in the occurrence of top event in system analysis become essential. Here we have put forward an approach to rank the basic events in accordance with their importance in the occurrence of top event. This approach can be widely used to improve the reliability and to reduce the operating cost of a system. The proposed techniques are discussed and illustrated by taking an example of a nuclear power plant.

Applied Mathematics, 2014

In this paper, we investigate the reliability analysis of a powerloom plant by using interval val... more In this paper, we investigate the reliability analysis of a powerloom plant by using interval valued intuitionistic fuzzy sets (IVIFS). Herein, we modeled a powerloom plant as a gracefully degradable system having two units A(n) and B(m) connected in series. The reliability of n components of unit A and m components of unit B is assumed to be an IVIFS defined over the universe of discourse [0, 1]. Thus, the reliability of the system obtained is an IVIFS that covers the inherited uncertainty in data collection and reliability evaluation of a powerloom plant.

Microelectronics Reliability, 1995

Applied Mathematical Modelling, 2014

ABSTRACT A dual hesitant fuzzy set (DHFS) consists of two parts, that is, the membership hesitanc... more ABSTRACT A dual hesitant fuzzy set (DHFS) consists of two parts, that is, the membership hesitancy function and the nonmembership hesitancy function, supporting a more exemplary and flexible access to assign values for each element in the domain, and can handle two kinds of hesitancy in this situation. It can be considered as a powerful tool to express uncertain information in the process of group decision making. Therefore, we propose a correlation coefficient between DHFSs as a new extension of existing correlation coefficients for hesitant fuzzy sets and intuitionistic fuzzy sets and apply it to multiple attribute decision making under dual hesitant fuzzy environments. Through the weighted correlation coefficient between each alternative and the ideal alternative, the ranking order of all alternatives can be determined and the best alternative can be easily identified as well. Finally, a practical example of investment alternatives is given to demonstrate the practicality and effectiveness of the developed approach.