A New Hybrid LGPMBWM-PIV Method for Automotive Material Selection

Wakeel, Saif; Bingöl, Sedat; Ahmad, Shafi; Bashir, M. Nasir; Emamat, Mir Seyed Mohammad Mohsen; Zhou, Dadi; Fayaz, H.

doi:10.31449/inf.v45i1.3246

Cited by 12 publications

(14 citation statements)

References 52 publications

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“…Te aggregated weights of the attributes are multiplied with the normalized value to develop a weighted normalized decision matrix as discussed in equation (14). Further, the absolute dispersion of each acid activator from the best one is determined by employing equation (15), which is identifed is the weighted proximity index value. Subsequently, a proximity value which is the algebraic sum of the weighted proximity index value is computed.…”

Section: Resultsmentioning

confidence: 99%

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Selection of Semiconductor Packaging Materials by Combined Fuzzy AHP-Entropy and Proximity Index Value Method

Bingöl

2022

Mathematical Problems in Engineering

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The residue of no-clean flux (NCF) on the printed circuit board assembly has been one of the major reasons for corrosion reliability failure of electronic devices. The source of aggressive contamination is the carboxylic acid activator as the main cleaning agent for soldering surfaces. Selecting the suitable activator has always been one of the concerns due to its conflicting properties, for example, suberic acid has a lower boiling point that will help in minimizing the residue; however, its dissociation constant is low which will increase the aggressive residue. The selection of a suitable activator based on the conflicting criteria is a multicriteria decision-making (MCDM) problem. In this study, thirty-one carboxylic acids (mono, di, tri, and hydroxyl) were ranked based on the six different criteria, i.e., melting point, molecular weight, boiling point, acid dissociation constant (pKaa value), solubility, and number of carboxylic acids using combined fuzzy AHP-entropy and the proximity index value method. Weight of the criterion was calculated using combined fuzzy AHP-entropy; whereas, ranking of the alternative carboxylic acid was done by the proximity index value method. First, the ranking was done based on the overall carboxylic acid; consequently, the groupwise ranking was also evaluated. As a result of this study, margaric acid occupied rank 1 out of all the thirty-one carboxylic acids and monocarboxylic acids; whereas, malonic acid acquired the lowest rank. In addition, out of 9 dicarboxylic acids, sebacic acid was the most suitable alternative. In the case of tricarboxylic acids, trimesic acid was a suitable alternative. Sensitivity analysis was performed to verify the reliability and consistency of the result obtained through applied MCDM.

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Section: Resultsmentioning

confidence: 99%

“…Te GPBWM had fewer constraints in comparison with the previous BWM-based models. Wakeel et al [15,16] applied the linear GPBWM and PIV to an automotive material selection problem. Amiri et al [17] extended BWM based on the possibilistic distribution.…”

Section: Introductionmentioning

confidence: 99%

Selection of Semiconductor Packaging Materials by Combined Fuzzy AHP-Entropy and Proximity Index Value Method

Bingöl

2022

Mathematical Problems in Engineering

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“…Gesture sequences are recorded by a face recognition system based on a deep neural network given by OpenCV [31]. The refined video is utilized as an input source to the pre-trained HopeNet model [32]. The HopeNet Model is an innovative FCNN-based head positioning model that calculates clear angles from EGB images.…”

Section: Machine Learning Based Classification Methodsmentioning

confidence: 99%

Research on Eye Pupil Location and Eye Tracking by Designing a Fully Conventional Neural Network (FCNN)

Raza¹,

Wang²,

Xue³

et al. 2020

Int. j. technol. eng. stud.

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Eye-tracking has become a significant tool in various areas, incorporating interaction of humans with a computer, computer vision, psychology, and medical diagnostics. Various protocols have been utilized to track the gaze. Although, some may not be accurate in the real world, while others may need explicit custom calibration, which can cause problems. Few of these techniques are associated with low image grades and varying lighting situations. The latest success and popularity of deep studying has dramatically increased the effectiveness of eye-tracking. The convenience of huge datasets additionally improves the function of deep learning-depend techniques. This technical paper introduces the latest deep studying-depend gaze assessment technology with a concentration on Fully Convolution Neural Networks (FCNN). This technical paper also gives an overview of other machine-based eye assessment methods. This research objective to enable the research population to generate significant and useful horizons that can improve the structure and growth of better, more effective deep learning depends on eye-tracking methods. This paper also gives information on different pertained models, network structures, and open origin datasets to help train deep learning models.

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“…This method has the advantage of minimizing the rank reversal phenomenon [7]. With this advantage, it is strongly exploited to rank the solutions in many different cases such as ranking the online learning websites [8], choosing the materials to manufacture some parts in F1 racing cars [9], choosing natural fibers for car roofs [10], evaluating the logistics performance index of EU countries [11], selecting the additives for a material production process [12], selecting the turning processes [13,14], selection of selection of grinding options [15], choosing renewable energy source [16], evaluating the financial performance of companies [17], evaluating the information and communication technology developments of G7 Countries [18], selecting the location for construction of the storehouse in logistics [19], selecting the location for construction of textile facilities in Sivas province in Turkey [20], selecting the suppliers [21], choosing a house design model to minimize the consumption of materials when building [22], selecting offshore location for construction of Offshore wind farm (OWF) in the energy industry [23], ect. Thus, it can be seen that PIV has been successfully used in many cases in many different fields.…”

Section: Introductionmentioning

confidence: 99%

Combination of DOE and PIV methods for multi-criteria decision making

Trung¹,

Tan²

2023

J Appl Eng Science

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When performing the multi-criteria decision making to choose the best solution, if some solutions are removed from the list of solutions or some solutions are added to the list of solutions, the decision making must be re-performed from the begining. This study proposes a new method to remove this limitation. The combination of the DOE (Design Of Experimental) method and PIV (Proximity Indexed Value) method is proposed in this paper. This combination is used to build the relationship between the scores of the solutions and the criteria. When the list of solution to be ranked has been removed or have been added some solutions, the ranking of some solutions only needs to use this relationship without having to recalculate from the beginning. Four different examples were applied to evaluate the effectiveness of the proposed method. The obtained results show that the proposed method ensures the required accuracy as well as its outstanding advantages. The limitations of the proposed method that need to be overcome are also pointed out at the end of this paper.

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A New Hybrid LGPMBWM-PIV Method for Automotive Material Selection

Cited by 12 publications

References 52 publications

Selection of Semiconductor Packaging Materials by Combined Fuzzy AHP-Entropy and Proximity Index Value Method

Selection of Semiconductor Packaging Materials by Combined Fuzzy AHP-Entropy and Proximity Index Value Method

Research on Eye Pupil Location and Eye Tracking by Designing a Fully Conventional Neural Network (FCNN)

Combination of DOE and PIV methods for multi-criteria decision making

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