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    Improvement in 316L steel surface features, corrosion and biocompatibility through novel CNT-assisted hydroxyapatite powder mixed-EDM process
    (Springer Link, 2023-06-22) Al-Amin, Md; Danish, Mohd; Rubaiee, Saeed; Ahmed, Anas; Abdul-Rani, Ahmad Majdi; Mannan, Abdul; Yildirim, Mehmet Bayram
    Although coating the biomaterials with hydroxyapatite powder (HAp) mixed electro discharge machining (EDM) is required to improve their biological responses, the modified 316L stainless steel shows a low coating adhesion and cracked surface, which is prone to poor corrosion resistance and surface integrity. In addition, inferior biological responses are noticed, since a little amount of HAp is detected in the coating. The primary objective of this study is to assess the CNT reinforced HAp-based coating on a 316L stainless steel to improve the surface features, corrosion and biocompatibility. This study also establishes a link between the process variables and the material's properties and shows the feasibility of multiple additive mixed EDM method. Following ASTM standard, several surface characterization tools were used to characterize the surface of the modified 316L stainless steel. CNT (0.4 g/l) added to the HAp mixed-EDM method results in a uniform and thin coating of 12.4 m with shallow craters, nanopores and no cracks. A small corrosion rate of 0.00033 mm per annum is recorded. The presence of carbon incorporated Ca-P-based alloys in the coating ensures a high coating adhesion of 32.6 MPa and a high biocompatibility of more than 95% alive cells.
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    Investigation of coated 316L steel surface: Surface morphology, composition, corrosion, and biocompatibility using hydroxyapatite mixed-EDM process
    (Elsevier B.V., 2023-08-25) Danish, Mohd; Al-Amin, Md; Rubaiee, Saeed; Gul, Iqtidar Ahmed; Ahmed, Anas; Rahman, Mohammad Obaidur; Zhang, Cunhan; Yildirim, Mehmet Bayram
    316L stainless steel belongs to insufficient biological responses and corrosion resistance. Although hydroxyapatite powder (HAp)-based coating improves biological responses and corrosion resistance of the 316L stainless steel, these coatings have resulted in inferior adhesion strength and cracked surface. This study aims to synthesize a highly biocompatible and corrosion resistant coating on the 316L stainless steel with a high adhesion strength and surface integrity using the electro discharge machining (EDM) method. The study also aims to explore the impacts of process parameters on the surface features. To reach the set objectives, several characterisation methods including atomic force microscopy (AFM), scanning electronic microscopy (SEM), X-ray powder diffraction (XRD), Potentiostat (electrochemical cell), MTT assay and X-ray photoelectron spectroscopy (XPS) were adopted. The HAp-mixed EDM method synthesized a biocompatible and corrosion resistant coating with an average thickness of 14.6 μm and 20.8MPa adhesion strength comprising of Ca-P based oxides and carbides. The modified surface showed nano surface roughness of 18.5 nm. The oxides and carbides formed in the coating improved the cell viability of 316L stainless steel surface to 87% and corrosion resistance to 0.00123 mm per year. This study is trying to gain the attention of 316L stainless steel-based bioimplant manufacturers to launch the hydroxyapatite mixed-EDM method for concurrent machining and coating.
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    Key initiatives to improve the machining characteristics of Inconel-718 alloy: Experimental analysis and optimization
    (Elsevier, 2022-11-03) Rubaiee, Saeed; Danish, Mohd; Gupta, Munish Kumar; Ahmed, Anas; Yahya, Syed Mohd; Yildirim, Mehmet Bayram; Sarikaya, Murat; Korkmaz, Mehmet Erdi
    Inconel 718 is a heat-resistant Ni-based superalloy widely used, particularly, in aircraft and aero-engineering applications. It has poor machinability due to its unique thermal and mechanical properties. For this reason, studies have been carried out from past to present to improve the machinability of Nickel-based (Ni) alloys. Further improvement can be achieved by applying hybrid multi-objective optimization strategies to ensure that cutting parameters and cooling/lubrication strategies are also adjusted effectively. That is why, in this research, the machinability of Inconel 718 is optimized under various sustainable lubricating environments i.e., dry medium, minimum quantity lubrication (MQL), nano-MQL, and cryogenic conditions at different machining parameters during end-milling process. Subsequently, the analysis of variance (ANOVA) approach was implanted to apprehend the impact of each machining parameter. Finally, to optimize machining environments, two advanced optimization algorithms (non-dominated sorting genetic algorithm II (NSGA-II) and the Teaching-learning-based optimization (TLBO) approach) were introduced. As a result, both methods have demonstrated remarkable efficiency in machine response prediction. Both methodologies demonstrate that a cutting speed of 90 m/min, feed rate of 0.05 mm/rev, and CO$_2$ snow are the optimal circumstances for minimizing machining responses during milling of Inconel 718.
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    Impact of commitment, information sharing, and information usage on supplier performance: a Bayesian belief network approach
    (Springer Nature, 2019-12-19) Sener, Abdurrezzak; Barut, Mehmet; Dag, Ali; Yildirim, Mehmet Bayram
    Due to the proliferation of information systems and technology, supply chains have the capability of acquiring an enormous amount of supplier data in their databases. However, much of the useful supplier-specific insights in terms of supplier performance metrics are mostly hidden and untouched. The current emphasis on supplier performance makes relationship commitment and information management functions an ideal application area to benefit from the use of data-mining tools for the decision-making process and improving supplier performance. By employing Bayesian belief networks, this study investigates the role of the major variables of commitment, information sharing, quality of shared information, and information usage in relation to supplier performance in the U.S. aircraft manufacturing supply chain. The results provide insightful guidance to managers on how to enhance performance
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    Effectiveness of capacity rationing heuristics in make to order environment
    (Inderscience Publishers, 2015) Barut, Mehmet; Yildirim, Mehmet Bayram; Sridharan, V.
    This paper investigates the effectiveness of a dynamic capacity-rationing heuristic for order acceptance and rejection in a capacitated make-to-order manufacturing environment. The heuristics developed for managing capacity has been shown to work better than accepting orders on a first-come, first-served basis. However, realised effectiveness versus potential effectiveness with respect to optimum has not been investigated. Results of this study reveal that the rationing heuristic is very effective in yielding results in proximity of optimum solution when customer segments are very distinct or highly differentiated and when implied utilisation is very high. On the other hand, when the attractiveness of higher profitable customer segment diminishes and capacity is not tight there is a significant potential to improve the heuristic.