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Öğe Effect of cobalt nanoparticles on mechanical properties of Sn-58Bi solder joint (vol 33, pg 22573, 2022)(Springer, 2022) Bashir, M. Nasir; Saad, Hafiz Muhammad; Rizwan, Muhammad; Bingol, Sedat; Channa, Iftikhar Ahmed; Gul, Mustabshirha; Haseeb, A. S. M. A.[Abstract Not Available]Öğe Effect of cobalt nanoparticles on mechanical properties of Sn–58Bi solder joint(Springer, 2022) Bashir, M. Nasir; Saad, Hafız Muhammad; Rizwan, Muhammad; Bingöl, Sedat; Channa, Iftikhar Ahmed; Haseeb, Abdul S.Md Abdul; Naher, SumsunBrittle phases are responsible for crack formation and propagation in tin–bismuth (Sn–58Bi) solder material. The purpose of this work is to investigate the effects of various cobalt (Co) nanoparticle (NP) concentrations on the tensile properties of the Sn–58Bi solder matrix. Different aging times were studied to find out the effect of Co NP on ultimate tensile strength. Tin–bismuth solder joints of different Co NP concentrations of 0%, 0.5%, 1%, and 2% were prepared. The reflow process was done at 180 °C for 1 min. Scanning Electron Microscopy and Energy-Dispersive X-ray spectroscopy were used to analyze the solder joints. The tensile test was carried out for the Sn–58Bi and Sn–58Bi–xCo (x = 0.5, 1, and 2) solder joints. The tensile test was run before and after aging time. The tensile results reveal that the addition of Co NP increased the tensile strength significantly at different concentrations of Co NP. The Tensile test revealed that ductility was improved as the temperature was increased. As the aging time increased, the ultimate tensile strength of all samples decreased.Öğe A New hybrid LGPMBWM-PIV method for automotive material selection(Slovensko Drustvo Informatika, 2021) Wakeel, Saif; Bingöl, Sedat; Ahmad, Shafi; Bashir, M. Nasir; Emamat, Mir Seyed Mohammad Mohsen; Ding, Zhou; Fayaz, H.Efforts are continuously being made by researchers to improve fuel efficiency and to reduce CO2 emissions from the passenger cars. To achieve these goal, recent trend is to make the cars components light in weight for which manufacturing car roofs using natural fiber reinforced composites (NFCs) is one of the method. Several natural fibers (NFs)are available as alternative reinforcements for the fabrication of NFCs. Different NFs possess different properties and therefore, it is necessary to select the most appropriate natural fiber for fabrication of the composites which in turn will lead to the desired performance of the vehicle. Selection of the optimal natural fiber, amongst the several alternatives, is basically a multi criteria decision making (MCDM) problem as selection is based on the evaluation of several conflicting criteria. In this study, twelve alternative natural fibers (Flax, Hemp, Jute, Kenaf, Ramie, Okra, PALF, Coir, Isora, Cotton, Banana and Sisal) and six evaluation criteria (Tensile strength, Stiffness, Failure strain, Density, Degradation temperature and Moisture gain) are considered and selection of the optimal NF is made using a newly developed hybrid MCDM method i.e. Linear goal programming model for Best-Worst method (LGPMBWM) and Proximity index value method (PIV). Results of the study reveal that among all considered natural fibers, Ramie fiber is the most suitable alternative for the fabrication of composites and coir fiber is the worst candidate for the same. Ranking results were also supported by five other MCDM methods as there was a strong correlation between PIV and other MCDM methods.Öğe Selection of sustainable material for the manufacturing of complex automotive products using a new hybrid Goal Programming Model for Best Worst Method-Proximity Indexed Value method(Sage Publications INC., 2021) Wakeel, Saif; Bingöl, Sedat; Bashir, M. Nasir; Ahmad, ShafiSelection of the most suitable sustainable material to fulfill the requirements of a product in a specific application is a complex task. Material selection problems are basically multi-criteria decision making problems as selection of the optimal material is based on the evaluation of conflicting criteria. Considering the limitations such as ranking reversal problem of the various multi-criteria decision making methods available in the literature, a combination of two recently developed techniques, i.e. the Goal Programming Model for Best Worst Method and Proximity Indexed Value method, is employed in the present study. This hybrid method was used for selection of the best possible material for manufacturing of a complex automobile part for which F1 race car as advanced automotive and its gearbox casing as sensitive part was used. Available alternative materials considered in the present study are alloys of aluminum, magnesium, titanium, and carbon fiber/epoxy laminate. Whereas, criteria affecting gearbox casing's performance are tensile strength/density, cost, stiffness, damping capacity, thermal conductivity, and sustainable criteria, such as CO2 emission and recycling energy. Goal Programming Model for Best Worst Method is used to determine weights of the criteria and Proximity Indexed Value method is employed for final selection of material. Furthermore, ranking of alternatives was also supported by other multi-criteria decision making methods namely, range of value, weighted product model, simple additive weighting, the technique for order of preference by similarity to ideal solution, a combined compromise solution, and the multi-attributive border approximation area comparison. Membership degree method was also employed to obtain the final optimal ranking of alternative materials from individual results of applied multi-criteria decision making methods. Besides, sensitivity analysis is done to validate reliability of the results and to determine the most critical evaluation criterion. The result of this study revealed that carbon fiber/epoxy laminate is the best alternative material.
