Using entropy weight-based TOPSIS to implement failure mode and effects analysis

2014 ◽  
Author(s):  
Xiaoyu Fu ◽  
Linpeng Huang ◽  
Guannan Su ◽  
Luxi Chen ◽  
Chen Li ◽  
...  
Keyword(s):  
Failure Mode ◽  
Entropy Weight

3D Numerical Model for Hydraulic Fracture Propagation in Tight Ductile Reservoirs, Considering Multiple Influencing Factors via the Entropy Weight Method

SPE Journal ◽  
2021 ◽  
pp. 1-18
Author(s):  
Yang Ju ◽  
Guangjie Wu ◽  
Yongliang Wang ◽  
Peng Liu ◽  
Yongming Yang
Keyword(s):  
Failure Mode ◽  
Hydraulic Fracture ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Fracture Propagation ◽  
Entropy Weight ◽  
Entropy Weight Method ◽  
Weight Method ◽  
Hydraulic Fracture Propagation ◽  
Brittleness And Ductility

Summary In this paper, we introduce the entropy weight method (EWM) to establish a comprehensive evaluation model able to quantify the brittleness of reservoir rocks. Based on the evaluation model and using the adaptive finite element-discrete element (FE-DE) method, a 3D model is established to simulate and compare the propagation behavior of hydraulic fractures in different brittle and ductile reservoirs. A failure criterion combining the Mohr-Coulomb strength criterion and the Rankine tensile criterion is used to characterize the softening and yielding behavior of the fracture tip and the shear plastic failure behavior away from the crack tip during the propagation of a fracture. To understand the effects of rock brittleness and ductility on hydraulic fracture propagation more intuitively, two groups of ideal cases with a single failure mode are designed, and the fracture propagation characteristics are compared and analyzed. By combining natural rock core scenarios with single failure mode cases, a comprehensive evaluation index BIf for reservoir brittleness and ductility is constructed. The simulation experiment results indicate that fractures in brittle reservoirs tended to form a complex network. With enhanced ductility, the yielding and softening of reservoirs hamper fracture propagation, leading to the formation of a simple network, smaller fracture area (FA), larger fracture volume, and the need for higher initiation pressure. The comprehensive index BIf can be used to define brittleness or ductility as the dominant factor of fracturing behavior. That is, 0 < BIf ≤ 0.46 indicates that the reservoir has enhanced ductility and ductile fracturing prevails; 0.72 < BIf < 1 indicates that the reservoir has enhanced brittleness and brittle fracturing prevails; and 0.46 < BIf ≤ 0.72 means a transition from brittle to ductile fracturing. Based on fitting analysis results, the relationship between the calculated FAr and BIf is constructed to quantify the influence of reservoir brittleness and ductility on fracturing. The study provides new perspectives for designing, predicting, and optimizing the fracturing stimulation of tight reservoirs with various brittleness and ductility.

Analytical electron microscopy of grain boundaries in Al-Cu metallizations

1992 ◽  
Vol 50 (2) ◽  
pp. 1684-1685
Author(s):  
J. R. Michael ◽  
A. D. Romig ◽  
D. R. Frear
Keyword(s):  
Electron Microscopy ◽  
Integrated Circuits ◽  
Failure Mode ◽  
Current Density ◽  
Thermal History ◽  
Analytical Electron Microscopy ◽  
Cu Metallization ◽  
Analytical Electron ◽  
Interconnect Lines

Al with additions of Cu is commonly used as the conductor metallizations for integrated circuits, the Cu being added since it improves resistance to electromigration failure. As linewidths decrease to submicrometer dimensions, the current density carried by the interconnect increases dramatically and the probability of electromigration failure increases. To increase the robustness of the interconnect lines to this failure mode, an understanding of the mechanism by which Cu improves resistance to electromigration is needed. A number of theories have been proposed to account for role of Cu on electromigration behavior and many of the theories are dependent of the elemental Cu distribution in the interconnect line. However, there is an incomplete understanding of the distribution of Cu within the Al interconnect as a function of thermal history. In order to understand the role of Cu in reducing electromigration failures better, it is important to characterize the Cu distribution within the microstructure of the Al-Cu metallization.

Risk analysis of cutting system under intuitionistic fuzzy environment

2020 ◽  
Vol 1 (1) ◽  
pp. 162-173
Author(s):  
Dinesh Kumar Kushwaha ◽  
◽  
Dilbagh Panchal ◽  
Anish Sachdeva ◽  
◽  
...  
Keyword(s):  
Risk Assessment ◽  
Failure Mode ◽  
Thermal Power ◽  
Failure Detection ◽  
Engineering System ◽  
Effect Analysis ◽  
Intuitionistic Fuzzy ◽  
Mode Effect ◽  
Cutting System ◽  
Failure Mode Effect Analysis

Failure Mode Effect Analysis (FMEA) is popular and versatile approach applicable to risk assessment and safety improvement of a repairable engineering system. This method encompasses various fields such as manufacturing, healthcare, paper mill, thermal power industry, software industry, services, security etc. in terms of its application. In general, FMEA is based on Risk Priority Number (RPN) score which is found by product of probability of Occurrence (O), Severity of failure (S) and Failure Detection (D). As human judgement is approximate in nature, the accuracy of data obtained from FMEA members depend on degree of subjectivity. The subjective knowledge of members not only contains uncertainty but hesitation too which in turn, affect the results. Fuzzy FMEA considers uncertainty and vagueness of the data/ information obtained from experts. In order to take into account, the hesitation of experts and vague concept, in the present work we propose integrated framework based on Intuitionistic Fuzzy- Failure Mode Effect Analysis (IF-FMEA) and IF-Technique for Order Preference by Similarity to Ideal Solution (IF-TOPSIS) techniques to rank the listed failure causes. Failure cause Fibrizer (FR) was found to be the most critical failure cause with RPN score 0.500. IF-TOPSIS has been implemented within IF-FMEA to compare and verify ranking results obtained by both the IF based approaches. The proposed method was presented with its application for examining the risk assessment of cutting system in sugar mill industry situated in western Uttar Pradesh province of India. The result would be useful for the plant maintenance manager to fix the best maintenance schedule for improving availability of cutting system.

Case Study of Electro-Optical Probing Signal with High Signal-Noise Ratio

2019 ◽  
Author(s):  
Ryan Xiao ◽  
William Wang ◽  
Ang Li ◽  
Shengqiu Xu ◽  
Binghai Liu
Keyword(s):  
Failure Mode ◽  
High Signal ◽  
Signal Noise ◽  
Electrical Failure ◽  
Current Path ◽  
Probing Signal ◽  
Optical Probing ◽  
Noise Ratio ◽  
Case Collection

Abstract With the development of semiconductor technology and the increment quantity of metal layers in past few years, backside EFA (Electrical Failure Analysis) technology has become the dominant method. In this paper, abnormally high Signal Noise Ratio (SNR) signal captured by Electro-Optical Probing (EOP)/Laser Voltage Probing (LVP) from backside is shown and the cause of these phenomena are studied. Based on the real case collection, two kinds of failure mode are summarized, and simulated experiments are performed. The results indicate that when a current path from power to ground is formed, the high SNR signal can be captured at the transistor which was on this current path. It is helpful of this consequence for FA to identify the failure mode by high SNR signal.

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