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    Investigation of coated 316L steel surface employing carbon nanotubes mixed-electrical discharge machining for biomedical applications
    (SAGE Publications Ltd, 2023-05-15) Danish, Mohd; Al-Amin, Md; Rubaiee, Saeed; Parameswari, R. P.; Abdul-Rani, Ahmad Majdi; Ahmed, Anas; Yildirim, Mehmet Bayram
    This research focuses on the influence of carbon nanotubes on the modified 316L steel surface properties for potential biomedical applications and explores relationships between the process variables and the modified surface properties. Following Taguchi's L9 (3^4) design, carbon nanotube is added in the electro-discharge machining oil to synthesize a biocompatible and hard coating when the machining of 316L steel with a titanium electrode. A few characterization tools such as scanning electron microscope, goniometer, Vickers's hardness, x-ray diffraction (powder X-ray diffraction), atomic force microscope, energy dispersive X-ray, and MTT ((3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide, a tetrazole) assay were adopted for performing the modified surface characterizations. A thin coating of 14.65 µm attributing to a small contact angle of 58.97° is found. The lowest surface roughness of 1.63?µm in micron scale and 5.641?nm in nano scale is obtained at a low both current and carbon nanotube amount applications. The morphological results confirm a crack-free, micro and nano porous surface. Compositional analysis ensures carbides, intermetallic and oxides formation on the coated surface. Microhardness of 316L steel is improved by about 86% (269.8 HV). Most importantly, approximately 70% cells are alive, which witnesses the use of carbon nanotube in biocompatible coating formation.
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    Technological and tribological characteristics improvement of additively manufactured SS 316L components machined under sustainable cooling conditions
    (Elsevier Ltd., 2023-03-01) Danish, Mohd; Rubaiee, Saeed; Gupta, Munish Kumar; Yildirim, Mehmet Bayram; Ahmed, Anas
    Advancements in digital processes and additive manufacturing technology enable the production produce complex-shaped metallic components by depositing material, layer upon layer, in precise geometric shapes. However, the additively manufactured components may still need some additional machining to meet specific requirements. With this aim, the present work deals with the machining of additively manufactured SS 316L under four different cooling environments, namely dry, flood, minimum quantity lubrication (MQL), and cryogenic carbon dioxide (CO$_2$). The tool wear, surface roughness, cutting temperature, and hardness were evaluated using various cooling methods. Additionally, residual stress was explored with the help of XRD data. The results of the experiments show that cryogenic CO$_2$ performs well in terms of cooling and reduces friction between the tool and the work material, thereby reducing tool wear. Under cryogenic cooling, the surface finish was improved by 43–46%, 33–36%, and 15–17% over dry, flood, and MQL conditions, respectively.
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    A genetic algorithm metaheuristic for bakery distribution vehicle routing problem with load balancing
    (2011-05) Keskintürk, Timur; Yildirim, Mehmet Bayram
    In this paper, we analyze a distribution problem at a bakery company in Istanbul, Turkey. The bakery wants to distribute products with the available fleets of trucks, while maintaining balance in workload between different truck drivers. The resulting problem is very similar to a capacitated vehicle routing problem with load balancing objective with a maximum distribution time and truck capacity constraints. A genetic algorithm meta-heuristic approach is proposed to obtain good quality solutions. The proposed meta-heuristic is utilized on a case study where different trucks serve customers in a large metropolitan area. The distance matrix is generated via a web application using Google Maps. The solutions obtained via the meta-heuristic are compared with the company's own distribution plan and global ant colony optimization algorithm.
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    A nonlinear approach for integrated marketing-economic production quantity problem
    (2010-12) Ghazi-Nezami, Farnaz; Yildirim, Mehmet Bayram
    Pricing is a key activity in determining any firm's profit in a supply chain due to the competitive nature of markets. Consequently, modeling the relation between marketing and manufacturing departments in a manufacturing company in order to come up with optimum decisions is of great importance. In this paper, we analyze a joint marketing-production problem, where the goal is maximizing profit of the company by determining optimal production quantity, marketing expenditure, and unit selling price at a manufacturing company with a finite production rate. The problem is formulated as a multiproduct signomial geometric programming model, which will be transformed into a standard posynomial model through a bi-level stepwise procedure where an optimal solution can be found. The model is illustrated on a numerical example, and some sensitivity analysis is performed.
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    Sustainable single-machine scheduling problem with reliability and energy consumption
    (Curran Associates, Inc., 2011-12) Ghazi-Nezami, Farnaz; Yildirim, Mehmet Bayram; Wang, Pingfeng
    In this paper, a multi-objective model is proposed to minimize energy consumption and total completion time, and to maximize reliability on a single machine. In this problem, jobs arrive over time, and their release dates are known. As a result, one must decide if turning off/on the machine or keeping the machine running idle will be more beneficial in terms of total energy consumption and reliability, since the impacts of idling and turning off/on operations affect the machine's lifetime differently. The proposed model is solved using the multi-objective optimization approach, and some sensitivity analysis is performed to gain insight.