Multi-attribute decision making parametric optimization and modelling in friction stir welding through grey relation taguchi analysis and ANOVA: A case study

2018 ◽  
Author(s):  
S. Rajendrakumar ◽  
S. P. Sundar Singh Sivam ◽  
K. Saravanan ◽  
K. Sathiya Moorthy ◽  
D. Kumaran
Keyword(s):  
Decision Making ◽  
Friction Stir Welding ◽  
Parametric Optimization ◽  
Taguchi Analysis ◽  
Friction Stir ◽  
Multi Attribute Decision Making ◽  
Grey Relation

Fuzzy Analytic Hierarchy Process and Its Application to E-Marketplace Selection

2013 ◽  
pp. 26-44 ◽  
Author(s):  
Beyza Ahlatcioglu Ozkok ◽  
Elisa Pappalardo
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Fuzzy Ahp ◽  
Multi Criteria Decision Making ◽  
Linguistic Variables ◽  
Analytic Hierarchy ◽  
Multi Attribute Decision Making ◽  
Electronic Parts ◽  
Hierarchy Process

Making decisions is a part of daily life. The nature of decision-making includes multiple and usually conflicting criteria. Multi Criteria Decision-Making (MCDM) problems are handled under two main headings: Multi Attribute Decision Making (MADM) and Multi Objective Decision Making (MODM). Analytic Hierarchy Process (AHP) is a widely used multi-criteria decision making approach and has successfully been applied to many practical problems. Traditional AHP requires exact or crisp judgments (numbers). However, due to the complexity and uncertainty involved in real world decision problems, decision makers might be more reluctant to provide crisp judgments than fuzzy ones. Furthermore, even when people use the same words, individual judgments of events are invariably subjective, and the interpretations that they attach to the same words may differ. This is why fuzzy numbers and fuzzy sets have been introduced to characterize linguistic variables. Here, the authors overview the most known fuzzy AHP approaches and their application, and they present a case study to select an e-marketplace for a firm, which produces and sells electronic parts of computers in Turkey.

Parametric optimization for friction stir welding with AA2024 and AA6061 aluminium alloys by ANOVA and GRG

2020 ◽  
Vol 27 ◽  
pp. 707-711
Author(s):  
C. Chanakyan ◽  
S. Sivasankar ◽  
S.V. Alagarsamy ◽  
S. Dinesh Kumar ◽  
S. Sakthivelu ◽  
...  
Keyword(s):  
Friction Stir Welding ◽  
Aluminium Alloys ◽  
Parametric Optimization ◽  
Friction Stir

Many-Attribute Decision Making Using Iterative Attribute Subsets

2016 ◽  
Author(s):  
Laura Ziegler ◽  
Kemper Lewis
Keyword(s):  
Decision Making ◽  
Large Scale ◽  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Decision Problems ◽  
Trade Off ◽  
Current Design ◽  
Multi Attribute Decision Making

A unique set of cognitive and computational challenges arise in large-scale decision making, in relation to trade-off processing and design space exploration. While several multi-attribute decision making methods exist in the current design literature, many are insufficient or not fully explored for many-attribute decision problems of six or more attributes. To address this scaling in complexity, the methodology presented in this paper strategically elicits preferences over iterative attribute subsets while leveraging principles of the Hypothetical Equivalents and Inequivalents Method (HEIM). A case study demonstrates the effectiveness of the approach in the construction of a systematic representation of preferences and the convergence to a single ‘best’ alternative.

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