Browsing by Author "Jahanzaib, Mirza"

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    Effect of different dielectrics on material removal rate, electrode wear rate and microstructures in EDM
    (Elsevier, 2017-05-09) Niamat, Misbah; Sarfraz, Shoaib; Aziz, Haris; Jahanzaib, Mirza; Shehab, Essam; Ahmad, Wasim; Hussain, Salman
    Diesinker electric discharge machining is widely used non-conventional technique for making high precision and complex shaped parts. Dielectrics and electrical parameters were considered as the main factors for EDM performance. In this paper, the effects of pulse-on-time (μs) and current (ampere) were evaluated for performance measures using kerosene and water as dielectrics. A comparison was performed for both dielectrics in terms of material removal rate (mm3/min), electrode wear rate (mm3/min), and microstructures. Aluminum 6061 T6 alloy was used as material for this research due to its extensive use in aerospace and automotive industries. Experiments were designed using Taguchi L9 orthogonal array (OA). Time series graphs were plotted to compare material removal rate and electrode wear rate. Microstructures were taken by scanning electron microscope to analyze the surface produced in terms of cracks, globules and micro-holes. Higher material removal rate and lower electrode wear were achieved with kerosene dielectric. The novelty of this research work, apart from its practical application, is that Aluminum 6061 T6 alloy is used as work material to compare the performance of dielectrics (kerosene and distilled water). Paper presented at: Complex Systems Engineering and Development Proceedings of the 27th CIRP Design Conference Cranfield University, UK 10th – 12th May 2017.
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    Investigation of electric discharge machining parameters to minimize surface roughness
    (Pakistan Association for the Advancement of Science, 2016-09-30) Sarosh, M.; Jahanzaib, Mirza; Mumtaz, J.; Sarfraz, Shoaib
    : Surface roughness during electrical discharge machining (EDM) was determined, in which material is removed by thermo-electric process due to the occurrence of successive discharge between workpiece and electrode. Box-Behnken design (BBD) involving four parameters discharge current (I), Pulse ON time (PON), Pulse OFF time (POFF) and Gap voltage, with three levels was employed to minimize the surface roughness. Other parameters such as Servo speed, Polarity and Die-electric pressure were kept constant throughout the machining. A copper electrode tool was used to machine the holes in AISI 1045 steel work piece. Mathematical models were developed using Response Surface Methodology (RSM), while Analysis of variance (ANOVA) was used to observe individual effect, interaction between parameters, and to check validity of models. Results revealed that pulse on time and discharge current were two main significant parameters that statistically affected surface roughness.
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    Investigation of temperature in orthopaedic drilling using response surface methodology
    (Pakistan Association for the Advancement of Science, 2016-09-30) Jamil, Muhammad; Sarfraz, Shoaib; Jahanzaib, Mirza
    Rise in temperature is inevitable in orthopaedic drilling. Massive research had been done in the field of orthopaedic drilling to investigate the effect of cutting conditions, bone related parameters, and drill bit geometric parameters on heat generation and minimum surrounding tissues injury. In present research, contradictory conclusions regarding the cutting conditions and drill bit geometric parameters were observed. Minimum temperature of 31°C was achieved at speed of 186 rpm, feed of 0.196 mm/rev, drill diameter of 3.85mm, and drill tip angle of 110°. Response Surface Methodology (RSM) was used to develop a mathematical model to predict the type of relationship between inputs and response. It was concluded that the most influencing parameter was drill diameter.
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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.
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    A smart algorithm for multi-criteria optimization of model sequencing problem in assembly lines
    (Elsevier, 2019-07-31) Rauf, Mudassar; Guan, Zailin; Sarfraz, Shoaib; Mumtaz, Jabir; Shehab, Essam; Jahanzaib, Mirza; Hanif, Muhammad
    Assembly Lines (ALs) are used for mass production as they offer lots of advantages over other production systems in terms of lead time and cost. The advent of mass customization has forced the manufacturing industries to update to Mixed-Model Assembly Lines (MMALs) but at the cost of increased complexity. In the real world, industries need to determine the sequence of models based on various conflicting performance measures/criteria. This paper investigates the Multi-Criteria Model Sequencing Problem (MC-MSP) using a modified simulation integrated Smart Multi-Criteria Nawaz, Enscore, and Ham (SMC-NEH) algorithm. To address the multiple criteria, a modified simulation integrated Smart Multi-Criteria Nawaz, Enscore, and Ham (SMC-NEH) algorithm was developed by integrating a priori approach with NEH algorithm. Discrete Event Simulation (DES) was used to evaluate each solution. A mathematical model was developed for three criteria: flow time, makespan and idle time. Further, to validate the effectiveness of the proposed SMC-NEH a case study and Taillard's benchmark instances were solved and a Multi-Criteria Decision-Making (MCDM) analysis was performed to compare the performance of the proposed SMC-NEH algorithm with the traditional NEH algorithm and its variants. The results showed that the proposed SMC-NEH algorithm outperformed the others in optimizing the conflicting multi-criteria problem.