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Öğe A HYBRID MULTI-CRITERIA DECISION MAKING METHOD FOR ROBOT SELECTION IN FLEXIBLE MANUFACTURING SYSTEM(2020) Bingöl, Sedat; Ahmad, Shafi; Wakeel, SaifAdvancement of the manufacturing system is governed by robots which improve the productquality and decrease market availability period. Different robots have been used for the pick and dropthe operation of components in flexible manufacturing systems (FMS). Each robot have their advantagesand disadvantages therefore, selection of the most suitable robot is significantly important. The selectionof robots based on various criteria is a multi-decision making problem (MCDM). In this study sevenrobots (R1, R2, R3, R4, R5, R6, R7) are ranked using the proposed approach on the basis of five criteriaviz. load capacity (LC), memory capacity (MC), manipulator reach (MR), maximum tip speed (MTS), andrepeatability (RE) by employing hybrid Criteria Importance Through Inter criteria Correlation(CRITIC) and Multi-attributive border approximation area comparison (MABAC) methods. Weights ofcriteria were obtained using correlation coefficient and standard deviation method whereas, the rankingof alternative was done using hybrid CRITIC and MABAC method. As a result of this study, robot R3acquired the first rank whereas, R1 occupied the last rank which showed that R3 is the most suitablerobot for the pick and place operation in FMS. Besides, Ranking comparison was also done with otherMCDM methods.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 A novel approach based on grey simplified best–worst method and grey possibility degree for evaluating materials in semiconductor industries(Springer Science and Business Media, 2023) Emamat, Mir Seyed Mohammad Mohsen; Wakeel, Saif; Amiri, Maghsoud; Ahmad, Shafi; Bingol, SedatThe reliability of flip-chip packages is significantly impacted by the type of packaging materials, such as underfill, solder, flux, and solder mask. Underfill reduces the coefficient of thermal expansion (CTE) mismatch between the semiconductor chip and printed circuit board, thereby minimizing the chances of thermal fatigue failure of the package. There are a plethora of underfill suppliers and selecting the most suitable underfill for preparing a flip-chip package is critical as there are conflicting criteria. These criteria are limited to glass transition temperature (Tg), CTE, elastic modulus (E), coefficient of moisture expansion, fracture toughness (Kic), shear strength, and flowability. Choosing appropriate alternatives based on the above conflicting criteria is basically a multi-criteria problem. This research proposes a grey simplified best–worst method (GSBWM) to identify the criteria weight. The proposed method has less calculation complexity than the previous grey best–worst methods, and it does not need operations research and modeling knowledge, and optimization software to solve it. The accuracy of the GSBWM is investigated using three data sets. The results showed the high accuracy of the proposed method in all data sets. This study employed the combination of GSBWM and a grey possibility degree based method to select the most suitable underfill material for reliable flip-chip packages as a real-world problem.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.Öğe Supplier selection for high temperature die attach by hybrid entropy-range of value MCDM technique: A semiconductor industry(Institute of Electrical and Electronics Engineers Inc., 2020) Wakeel, Saif; Ahmad, Shafi; Bingöl, Sedat; Bashir, Muhammad Nasir; Paçal, Tuğçe Cemre; Khan, Zahid Akhtar; 0000-0002-3595-3878; 0000-0001-9620-5980Demands of High temperature die attach material (HTDM) are growing to increase the efficiency of Microelectronic packaging. However, Appropriate HTDM supplier selection is one of the major concerns for semiconductors industries due to various conflicting criteria. This study will employ a multicriteria decision making modelling (MCDM) to select the suitable HTDM supplier. Seven different international HTDM supplier (S1, S2, S3, S4, S5,S6,S7) are ranked based on eight conflicting criteria (electrical resistivity, thermal conductivity, impression, management system, production facility, geographical location, response speed and use of technology) by employing hybrid entropy-range of value (E-ROV) method. The result of this study showed that S7 is the most suitable supplier as it occupies rank one in the modelling and S5 being a worst. Sensitivity analysis illustrated that the results of E-ROV are consistent and reliable. Based on these results, E-ROV method can also be applied for supplier selection of various production complex parts in semiconductor industry.
