Multi-criteria decision-making approaches for aircraft-material selection problem

Boyacı, Aslı Çalış; Tüzemen, Mehmet Çağrı

doi:10.1504/ijmpt.2022.120246

Cited by 9 publications

(6 citation statements)

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“…1. Numerous studies, for example [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20], demonstrate that the ranks (especially ratings) of alternatives can change with variations of any of the arguments in Eq. 1.…”

Section: Methodology 31 Mcdm Rank Modelmentioning

confidence: 99%

“…A common scenario involves the preference for the same alternative across a larger number of methods, often following the majority principle. Borda's rule and its modifications are frequently applied [17][18][19]. Additionally, a statistical approach based on a histogram of the distribution of ranks for a selected set of methods is typical [20].…”

Section: Introductionmentioning

confidence: 99%

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"Thin" Structure of Relations in MCDM Models. Equivalence of the MABAC, TOPSIS(L1) and RS Methods to the Weighted Sum Method

Mukhametzyanov,

Pamucar

2024

Decis. Mak. Appl. Manag. Eng.

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This paper introduces the conceptual framework of the multi-criteria decision-making (MCDM) rank model, which embodies the integration and harmonization of the aggregation method, the weighing method, the decision matrix normalization technique, and the selection of distance metrics. This definition serves to broaden the spectrum of acceptable MCDM methodologies for problem-solving and specifiing the associated tools. A Multi-Method Model (3M) approach is employed for multi-criteria selection to enhance the reliability of the results. The methodology is outlined for adjusting the rankings of alternatives to account for the distinguishability of ratings in a particular MCDM model using the Relative Performance Indicator (RPI) of alternatives. Through RPI, four methods are established for aggregating individual characteristics of alternatives that yield identical results: Weighted Sum Model (WSM), Multi-Attributive Border Approximation area Comparison (MABAC), Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS (L1)), and Ratio System approach (RS), eliminating the need to duplicate these methods in the 3M approach. A comprehensive comparison of numerous multi-criteria methods is conducted based on two lists: ranking and rating. Additionally, a method for step-by-step linear transformation of alternative ratings obtained from various MCDM models is defined, facilitating comparison and aggregation of ratings.

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Section: Methodology 31 Mcdm Rank Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

"Thin" Structure of Relations in MCDM Models. Equivalence of the MABAC, TOPSIS(L1) and RS Methods to the Weighted Sum Method

Mukhametzyanov,

Pamucar

2024

Decis. Mak. Appl. Manag. Eng.

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“…The fabric that satisfies the preferred physicochemical characteristics at the best rate can be identified by a variety of MCDM processes depending on the character traits of the choice of suitable materials. As a result, technicians will be able to choose the best material before wasting time and money on timeconsuming and costly methods like development and testing and different mechanical experiments [12].…”

Section: Introductionmentioning

confidence: 99%

Assessment of Material Selection Problem for Aircraft Parts Using the GRA method

2023

aae

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Composites can simultaneously enhance materials and designs while having superior mechanical qualities. Composites can have notably better "strength, stiffness, corrosion, wear, and fatigue resistance" than typical composites, which is important for developing aviation constituent parts. The mechanical qualities of the composite fabric must be crafted to fit its intended application or the exploited circumstances. For "the manufacture of aeroplanes", many metals and synthetic fibres are preferred today. Thousands of people of polymers must be chosen by engineers, but only 0.05 per cent of those may be used in the aerospace sector and still have the desired properties. The choice of proper raw materials from tens of thousands of components has grown to be a significant problem. In a "Multi-criteria decisionmaking (MCDM)" situation, the optimal material for an aeroplane must be selected from a range of alternatives. The finest components for aeroplane parts are chosen in this study using strategies focused on "the Grey Relational Analysis (GRA) method".

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“…Altun et al [24] described an approach to determining forces applied to elements of machines using artificial neural networks. Boyaci and Tuzemen [25] applied different multicriteria decision-making approaches (i.e., a complex proportional assessment method) for material selection in the aerospace industry.…”

Section: Introductionmentioning

confidence: 99%

Using Regression Analysis for Automated Material Selection in Smart Manufacturing

et al. 2022

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In intelligent manufacturing, the phase content and physical and mechanical properties of construction materials can vary due to different suppliers of blanks manufacturers. Therefore, evaluating the composition and properties for implementing a decision-making approach in material selection using up-to-date software is a topical problem in smart manufacturing. Therefore, the article aims to develop a comprehensive automated material selection approach. The proposed method is based on the comprehensive use of normalization and probability approaches and the linear regression procedure formulated in a matrix form. As a result of the study, analytical dependencies for automated material selection were developed. Based on the hypotheses about the impact of the phase composition on physical and mechanical properties, the proposed approach was proven qualitatively and quantitively for carbon steels from AISI 1010 to AISI 1060. The achieved results allowed evaluating the phase composition and physical properties for an arbitrary material from a particular group by its mechanical properties. Overall, an automated material selection approach based on decision-making criteria is helpful for mechanical engineering, smart manufacturing, and industrial engineering purposes.

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Multi-criteria decision-making approaches for aircraft-material selection problem

Cited by 9 publications

References 0 publications

"Thin" Structure of Relations in MCDM Models. Equivalence of the MABAC, TOPSIS(L1) and RS Methods to the Weighted Sum Method

"Thin" Structure of Relations in MCDM Models. Equivalence of the MABAC, TOPSIS(L1) and RS Methods to the Weighted Sum Method

Assessment of Material Selection Problem for Aircraft Parts Using the GRA method

Using Regression Analysis for Automated Material Selection in Smart Manufacturing

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