Browsing by Author "Ismail, Sikiru Oluwarotimi"

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    Chapter 5: Comprehensive study on tool wear during machining of fiber-reinforced polymeric composites
    (Springer, 2020-12-23) Ismail, Sikiru Oluwarotimi; Sarfraz, Shoaib; Niamat, Misbah; Mia, Mozammel; Gupta, Munish Kumar; Pimenov, Danil Yu; Shehab, Essam
    The use of fiber reinforced polymeric (FRP) composites has increased rapidly, especially in many manufacturing (aerospace, automobile and construction) industries. The machining of composite materials is an important manufacturing process. It has attracted several studies over the last decades. Tool wear is a key factor that contributes to the cost of the machining process annually. It occurs due to sudden geometrical damage, frictional force and temperature rise at the tool-work interaction region. Moreover, tool wear is an inevitable, gradual and complex phenomenon. It often causes machined-induced damage on the workpiece/FRP composite materials. Considering the geometry of drill, tool wear may occur at the flank face, rake face and/or cutting edge. There are several factors affecting the tool wear. These include, but are not limited to, drilling parameters and environments/conditions, drill/tool materials and geometries, FRP composite compositions and machining techniques. Hence this chapter focuses on drilling parameters, tool materials and geometries, drilling environments, types of tool wear, mechanisms of tool wear and methods of measurement of wear, effects of wear on machining of composite materials and preventive measures against rapid drill wear. Conclusively, some future perspectives or outlooks concerning the use of drill tools and their associated wears are elucidated, especially with the advancement in science and technology
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    Experimental characterization of electrical discharge machining of aluminum 6061 T6 alloy using different dielectrics
    (King Fahd University of Petroleum & Minerals, 2019-07-08) Niamat, Misbah; Sarfraz, Shoaib; Shehab, Essam; Ismail, Sikiru Oluwarotimi; Khalid, Qazi Salman
    Electrical discharge machining is a non-traditional machining method broadly employed in industries for machining of parts that have typical profiles and require great accuracy. This paper investigates the effects of electrical parameters: pulse-on-time and current on three performance measures (material removal rate, microstructures and electrode wear rate), using distilled water and kerosene as dielectrics. A comparison between dielectrics for the machining of aluminum 6061 T6 alloy material in terms of performance measures was performed. Aluminum 6061 T6 alloy material was selected, because of its growing use in the automotive and aerospace industrial sectors. The experimental sequence was designed using Taguchi technique of L9 orthogonal array by changing three levels of pulse-on-time and current, and test runs were performed separately for each dielectric. The results obtained show that greater electrode wear rate (EWR) and higher material removal rate (MRR) were achieved with distilled water when compared with kerosene. These greater EWR and MRR responses can be attributed to the early breakage of the weak oxide and carbide layers formed on the tool and alloy material surfaces, respectively. The innovative contributions of this study include, but are not limited to, the possibility of machining of aluminum 6061 T6 alloy with graphite electrode to enhance machinability and fast cutting rate employing two different dielectrics.
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    Multi-objective optimisation for minimum quantity lubrication assisted milling process based on hybrid response surface methodology and multi-objective genetic algorithm
    (Sage, 2019-04-22) Mumtaz, Jabir; Li, Zhang; Imran, Muhammad; Yue, Lei; Jahanzaib, Mirza; Sarfraz, Shoaib; Shehab, Essam; Ismail, Sikiru Oluwarotimi; Afzal, Kaynat
    Parametric modelling and optimisation play an important role in choosing the best or optimal cutting conditions and parameters during machining to achieve the desirable results. However, analysis of optimisation of minimum quantity lubrication–assisted milling process has not been addressed in detail. Minimum quantity lubrication method is very effective for cost reduction and promotes green machining. Hence, this article focuses on minimum quantity lubrication–assisted milling machining parameters on AISI 1045 material surface roughness and power consumption. A novel low-cost power measurement system is developed to measure the power consumption. A predictive mathematical model is developed for surface roughness and power consumption. The effects of minimum quantity lubrication and machining parameters are examined to determine the optimum conditions with minimum surface roughness and minimum power consumption. Empirical models are developed to predict surface roughness and power of machine tool effectively and accurately using response surface methodology and multi-objective optimisation genetic algorithm. Comparison of results obtained from response surface methodology and multi-objective optimisation genetic algorithm depict that both measured and predicted values have a close agreement. This model could be helpful to select the best combination of end-milling machining parameters to save power consumption and time, consequently, increasing both productivity and profitability.