Parametric Optimisation of Friction-Stir-Spot-Welded Al 6061-T6 Incorporated with Silicon Carbide Using a Hybrid WASPAS–Taguchi Technique

Chaudhary, Neeru; Singh, Sarbjit; Garg, Mohinder Pal; Garg, Harish; Sharma, Shubham; Li, Changhe; Eldin, Sayed M.; Elkhatib, Samah Elsayed

doi:10.3390/ma15186427

Cited by 9 publications

(2 citation statements)

References 50 publications

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“…CODAS is a relatively advanced distance-based MCDM that ranks alternatives in a methodical scheme based on combining two types of distance: Euclidean and Taxicab [110,111]. The main advantage of WASPAS lies in its hybrid nature that can simultaneously combine weighed sum model and weighed product model [112,113]. Another advantage is its computational simplicity and robustness against rank reversal [114][115][116].…”

Section: Methodsmentioning

confidence: 99%

An Integrated Multi-Criteria Decision Making Model for the Assessment of Public Private Partnerships in Transportation Projects

Mohammed Abdelkader,

Zayed,

El Fathali

et al. 2023

Mathematics

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Public–private partnership (PPP) infrastructure projects have attracted attention over the past few years. In this regard, the selection of private partners is an integral decision to ensure its success. The selection process needs to identify, scrutinize, and pre-qualify potential private partners that sustain the greatest potential in delivering the designated public–private partnership projects. To this end, this research paper proposes an integrated multi-criteria decision-making (MCDM) model for the purpose of selection of the best private partners in PPP projects. The developed model (HYBD_MCDM) is conceptualized based on two tiers of multi-criteria decision making. In the first tier, the fuzzy analytical network process (FANP) is exploited to scrutinize the relative importance of the priorities of the selection criteria of private partners. In this respect, the PPP selection criteria are categorized as safety, environmental, technical, financial, political policy, and managerial. In the second tier, a set of seven multi-criteria decision-making (MCDM) algorithms is leveraged to determine the best private partners to deliver PPP projects. These algorithms comprise the combined compromise solution (CoCoSo), simple weighted sum product (WISP), measurement alternatives and ranking according to compromise solution (MARCOS), combinative distance-based assessment (CODAS), weighted aggregate sum product assessment (WASPAS), technique for order of preference by similarity to ideal solution (TOPSIS), and FANP. Thereafter, the Copeland algorithm is deployed to amalgamate the obtained rankings from the seven MCDM algorithms. Four real-world case studies are analyzed to test the implementation and applicability of the developed integrated model. The results indicate that varying levels of importance were exhibited among the managerial, political, and safety and environmental criteria based on the nature of the infrastructure projects. Additionally, the financial and technical criteria were appended as the most important criteria across the different infrastructure projects. It can be argued that the developed model can guide executives of governments to appraise their partner’s ability to achieve their strategic objectives. It also sheds light on prospective private partners’ strengths, weaknesses, and capacities in an attempt to neutralize threats and exploit opportunities offered by today’s construction business market.

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Section: Methodsmentioning

confidence: 99%

An Integrated Multi-Criteria Decision Making Model for the Assessment of Public Private Partnerships in Transportation Projects

Mohammed Abdelkader,

Zayed,

El Fathali

et al. 2023

Mathematics

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“…Based on the results of the experiment, they suggested using the WASPAS technique. To optimize the 'friction stir spot welding' parameters of Al 6061-T6 incorporated with silicon carbide, Chaudhary et al [21] used a hybrid WASPAS-Taguchi technique. Increased strength and hardness of the welded joint were the desired outcomes.…”

Section: Introductionmentioning

confidence: 99%

Exploring machine vision measurements through innovative cyclic-lead-follower statistical technique: an experimental study

Zende,

Pawade

2024

Eng. Res. Express

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In metrology systems, machine vision systems are often utilized for non-contact inspection. The most important phase in ensuring measurement accuracy is camera calibration and estimation of pixel measurement errors, which establish the correspondence between image coordinates and object coordinates. Multiple calibration techniques improve the effectiveness of machine vision systems. However, a number of factors lead to variations in the camera calibration procedure, which must be optimized. This study explains a novel 'Cyclic-Lead-Follower' statistical methodology proposed for camera calibration and measurement to estimate the errors in pixel measurement, employing four slip gauges for measurement. Several multi-criteria decision-making techniques, including WSM, WPM, WASPAS, and TOPSIS, were used to optimize the results of the proposed Cyclic-Lead-Follower methods. The proposed Cyclic-Lead-Follower method improves the accuracy of the camera calibration and measurement system, which employs the exponential moving average statistical method when compared to the traditional calibration method. The proposed calibration method produces lower exponential moving average values than the traditional calibration method, with an average percentage error of approximately 46% in the exponential moving average. The use of an exponential moving average in a validation experiment of the Cyclic-Lead-Follower method decreased the measurement percentage errors, which were estimated to be 0.57%. The proposed method can be used in machine vision systems due to its robustness, accuracy, and cost-effectiveness.

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Advancements in Laser Beam Welding for Dissimilar Material Joining: Exploring Weldability Assessment, Challenges, Parametric Influences on the Mechanical–Microstructural Properties in Steel‐Alloyed Metal Combinations

Biswas,

Banerjee,

Sen

et al. 2024

steel research int.

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With the growing demands in several sectors such as the automotive, biomedical, construction, shipbuilding, aerospace, and other manufacturing units, employment of welding techniques has observed a rapid boom in recent times. Laser welding technique is one such recent sign of progress in the fabrication field. Laser beam welding is a radiant energy welding process widely adapted to join a variety of metals and nonmetals. The demand for the dissimilar material welding increases with the increase in industrial needs. Several severe challenges need to be overcome to have such dissimilar welded components mainly as the significant difference in melting point, different combinations of mechanical, metallurgical, chemical, and thermal properties. The present approach attempts to study the weldability of steel and its alloys with other metals and parametric effects on mechanical and microstructural properties. The study reveals that the laser beam offset plays a vital role to achieve sound quality welded joint with desirable weld strength. It has been found that 0.32 mm beam offset generates 243 MPa ultimate tensile strength in the 316L to TC4 dissimilar welds. Again, the addition of interlayers also improves the joint strength of both steel‐to‐aluminum and steel‐to‐titanium dissimilar welded joints.

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Parametric Optimisation of Friction-Stir-Spot-Welded Al 6061-T6 Incorporated with Silicon Carbide Using a Hybrid WASPAS–Taguchi Technique

Cited by 9 publications

References 50 publications

An Integrated Multi-Criteria Decision Making Model for the Assessment of Public Private Partnerships in Transportation Projects

An Integrated Multi-Criteria Decision Making Model for the Assessment of Public Private Partnerships in Transportation Projects

Exploring machine vision measurements through innovative cyclic-lead-follower statistical technique: an experimental study

Advancements in Laser Beam Welding for Dissimilar Material Joining: Exploring Weldability Assessment, Challenges, Parametric Influences on the Mechanical–Microstructural Properties in Steel‐Alloyed Metal Combinations

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