i-manager Publications

i-manager's Journal on Mechanical Engineering (JME)

Current Issue Vol. 13 Issue 4

Effects of Drill Pipe Length and Weight on Bit on Lateral and Longitudinal Vibrations
Shell Tube Exchanger Parametric Investigation and Performance Simulation using Ansys
Fatigue Life Prediction of Aluminum 6061 Alloy through Experimental and Numerical Analysis under Various Stress Ratios in Axial Tension-Tension Loading Condition
Enhancing the Control of Boron Epoxy Cross-Ply Laminated Composite Plates through Intelligent Implementation of PZT Sensor and Actuator
Ball Mill Energy Efficiency Optimization Techniques: A Review

Most Cited

Volume 9 Issue 3 May - July 2019

Research Paper

Thermoeconomic Analysis of a Single Effect Mechanical Vapor Compression Desalination Unit

Giuma M. Fellah*

Department of Mechanical and Industrial Engineering, University of Tripoli, Libya.

Fellah, G. (2019). Thermoeconomic Analysis of a Single Effect Mechanical Vapor Compression Desalination Unit. i-manager’s Journal on Mechanical Engineering, 9(3),1-8. https://doi.org/10.26634/jme.9.3.15797

Abstract

In this work, the thermoeconomic analysis is performed to assess the performance of a single effect-mechanical vapor compression desalination unit. Thermoeconomic equations based on Specific Exergy Costing (SPECO) method are developed for the analysis. The results show that the unit cost of the product distillate water is 2.59 $/m³ which is in a good agreement with that given in the literature. The effect of the escalation factor of the chemicals' cost on the product unit cost of the fresh water is investigated. The unit price of the product jumps to 3.56$/m³ at escalation factor of 7%. The influence of the compressor efficiency on the specific energy consumption and effectiveness is also investigated. The results show that there is an optimum compressor efficiency at which the product unit price is a minimum

References

[1]. Asiedu-Boateng, P., Yamoah, S., Ameyaw, F., Dzide, S., & Tuffour-Acheampong, K. (2012). Performance analysis of thermal vapour compression desalination system coupled to cogeneration nuclear power plant. Research Journal of Applied Sciences Engineering and Technology, 4(8), 941- 948.

[2]. Catrini, P., Cipollina, A., Micale, G., Piacentino, A., & Tamburini, A. (2017). Exergy analysis and thermoeconomic cost accounting of a combined heat and power steam cycle integrated with a multi effect distillation-thermal vapour compression desalination plant. Energy Conversion and Management, 149, 950-965. https://doi.org/10.1016/ j.enconman.2017.04.032

[3]. El-Dessouky, H. T., & Ettouney, H. M. (2002). st Fundamentals of Salt Water Desalination, (1 ed.). Amsterdam: Elsevier B.V.

[4]. Hanafi, A. S., Mostafa, G. M., Fathy, A., & Waheed, A. (2015). Thermo-economic analysis of combined cycle MED-TVC desalination system. Energy Procedia, 75, 1005- 1020. https://doi.org/10.1016/j.egypro.2015.07.342

[5]. Jamil, M. A., & Zubair, S. M. (2017). On thermoeconomic analysis of a single-effect mechanical vapor compression desalination system. Desalination, 420, 292-307. https://doi.org/10.1016/j.desal.2017.07.024

[6]. Lazzaretto, A., & Tsatsaronis, G. (2006). SPECO: a systematic and general methodology for calculating efficiencies and costs in thermal systems. Energy, 31(8-9), 1257-1289. https://doi.org/10.1016/j.energy.2005.03.011

[7]. Mabrouk, A. A., Nafey, A. S., & Fath, H. E. S. (2007). Analysis of a new design of a multi-stage flash–mechanical vapor compression desalination process. Desalination, 204(1-3), 482-500. https://doi.org/10.1016/j.desal.2006. 02.046

[8]. Mokhtari, H., & Sepahvand, M. (2016). Thermoeconomic and exergy analysis in using hybrid systems (GT+ MED+ RO) for desalination of brackish water in Persian Gulf. Desalination, 399, 1-15. https://doi.org/ 10.1016/j.desal.2016.07.044

[9]. Nafey, A. S., Fath, H. E. S., & Mabrouk, A. A. (2006). Thermoeconomic analysis of multi stage flashthermal vapor compression (MSF-TVC) desalination process. In Tenth International Water Technology Conference (pp. 189-203).

[10]. Nafey, A. S., Fath, H. E. S., & Mabrouk, A. A. (2008). Thermoeconomic design of a multi-effect evaporation mechanical vapor compression (MEE–MVC) desalination process. Desalination, 230(1-3), 1-15. https://doi.org/ 10.1016/j.desal.2007.08.021

[11]. Sharaf, M. A., Nafey, A. S., & García-Rodríguez, L. (2011). Thermo-economic analysis of solar thermal power cycles assisted MED-VC (multi effect distillation-vapor compression) desalination processes. Energy, 36(5), 2753- 2764. https://doi.org/10.1016/j.energy.2011.02.015

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Research Paper

Experimental Investigation and Optimization of Machining Parameters in Milling of Al6351 Using Hybrid – Artificial Bee Colony Algorithm

P. Hema* , G. Padmanabhan, T. Eswar*

*_*** Department of Mechanical Engineering, S. V. University college of Engineering, Tirupati, Andhra Pradesh, India.

Hema, P., Padmanabhan, G., and Eswar, T. (2019). Experimental Investigation and Optimization of Machining Parameters in Milling of Al6351 Using Hybrid – Artificial Bee Colony Algorithm. i-manager’s Journal on Mechanical Engineering, 9(3),9-18. https://doi.org/10.26634/jme.9.3.16059

Abstract

Simplifying any process of machining is a profoundly difficult, since it basically includes forecasts of ideal cutting parameters and working requirements that are unpredictable and extremely non-linear in nature which influence the overall production costs and workpiece quality. One of the Nature Inspired Algorithms (NIA) is Artificial Bee Colony (ABC) algorithm for process optimization that imitates honey bees intelligent foraging behavior. This paper describes an experimental study of cutting parameters optimization like Cutting Speed, Feed rate, Aluminum Alloy 6351 response depth cut by using Swarm-based optimization. Based on Taguchi design of experiments L18 orthogonal array is selected with three levels of input parameters at various machining conditions. The experiments are performed and predicted the responses like Surface Roughness, Material Removal Rate, Resultant Forces and Temperature. A recent evolutionary heuristic swarm intelligence algorithm called the Hybrid Artificial Bee Colony (HABC) is used to optimize conventional milling processes. This algorithm is used to minimize responses by estimating the optimum parameters of the process. Comparison of the results with the Harmony Search Algorithm (HSA), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are done to examine the performances of various methods. The results suggest that the HABC algorithm outperforms the solution's HSA, PSO and GA quality. Additionally, Multi-Objective Optimization is performed and a combined normalized objective function (Z) is formulated by considering equal weightages to all the objectives. The optimized values of milling parameters are obtained through the HABC algorithm. Confirmatory experiments reveal that the experimental values are moderately close with optimized values.

References

[1]. Agarwal, N. (2012). Surface roughness modeling with machining parameters (speed, feed & depth of cut) in CNC milling. MIT International Journal of Mechanical Engineering, 2(1), 55-61.

[2]. Bahirie, S., & Pothar, V. (2014). Optimization of milling conditions by using particle swarm optimization technique: a review. International Journal of Engineering Trends and Technology, 18(6), 248-251.

[3]. Chavan, S. Y., & Jadhav, V. S. (2013). Determination of optimum cutting parameters for multiperformance characteristics in CNC end milling of Al-Si7Mg aluminum alloy. International Journal of Engineering and Technical Research (IJETR), 1(6),15-21.

[4]. Hricova, J., Kovac, M., & Sugar, P. (2014). Experimental investigation of high speed milling of aluminium alloy. Technical Gazette, 21(4), 773-777.

[5]. Karaboga, D. (2005). An idea based on honey bee swarm for numerical optimization (Vol. 200, pp.1-10). Technical report-tr06, Erciyes University, Computer Engineering Department.

[6]. Karaboga, D., & Basturk, B. (2007, June). Artificial bee colony (ABC) optimization algorithm for solving constrained optimization problems. In Melin P., Castillo O., Aguilar L.T., Kacprzyk J., & Pedrycz W. (Eds) International fuzzy systems association world congress (pp. 789-798). Berlin, Heidelberg: Springer https://doi.org/10.1007/978-3-540- 72950-1_77

[7]. Manjarres, D., Landa-Torres, I., Gil-Lopez, S., Del Ser, J., Bilbao, M. N., Salcedo-Sanz, S., & Geem, Z. W. (2013). A survey on applications of the harmony search algorithm. Engineering Applications of Artificial Intelligence, 26(8), 1818-1831. https://doi.org/10.1016/j.engappai.2013. 05.008

[8]. Prajapati, V. M., Thakkar, K. H., Thakkar, S.A. , & Parikh, H. B. (2013). Study and investigate effects of cutting parameters in CNC milling process for aluminium alloy- 8011h14 through taguchi design method. International Journal of Innovative Research in Science, Engineering and Technology, 2(1), 3271-3276.

[9]. Prasanth, R. S. S. & Raj, K. H. (2015). Artificial bee colony – Differential evolution (ABC-DE) algorithm for CNC turning process optimization. GE-International Journal of Engineering Research, 3(5), 18-39.

[10]. Rao, S. S. (2009). Engineering optimization (4 Ed.). Hoboken, New Jersey: John Wiley & Sons.

[11]. Reddy, M. N., Reddy, M. N., Kumar, K. V., & Garre, P. (2014). Experimental investigation of tensile strength on Al 6351 to the aerospace structural applications. International Journal of Mechanical Engineering and Technology (IJMET), 5(2), 110-114.

[12]. Selvam, M. D., Dawood, D. A. S., & Karuppusami, D. G. (2012). Optimization of machining parameters for face milling operation in a vertical CNC milling machine using genetic algorithm. IRACST-Engineering Science and Technology: An International Journal (ESTIJ), 2(4), 544-548.

[13]. Sequeira, A. A, Prabhu, R. & Sriram, N. S.(2012). Effect of cutting parameters on cutting force and surface roughness of aluminium components using face milling process- A taguchi approach. IOSR Journal of Mechanical and Civil Engineering, 3(4), 7-13.

[14]. Solaiyappan, A., Mani, K., & Gopalan, V. (2014). Multiobjective optimization of process parameters for electrochemical machining of 6061Al/10% Wt Al2O3/5% Wt SiC composite using hybrid fuzzy-artificial bee colony algorithm. Jordan Journal of Mechanical and Industrial Engineering, 8(5), 323-331.

[15]. Vishnu, A. V., Tilak, K. B. G., Naidu, G. G., & Raju, D. G. J. (2015). Optimization of different process parameters of aluminium Alloy 6351 in CNC milling using Taguchi method. International Journal of Engineering Research and General Science, 3(2),407-413.

[16]. Yildiz, A. R. (2013). Optimization of cutting parameters in multi-pass turning using artificial bee colony-based approach. Information Sciences, 220, 399-407. https://doi.org/10.1016/j.ins.2012.07.012

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Research Paper

A Study on Tribological Behaviour of Nanocoated Piston Ring

Ravindra M. Kanase*

Department of Automobile Engineering, Padmashri Dr. VitthalraoVikhe Patil, Institute of Technology & Engineering(Polytechnic) Pravaranagar, Loni, Ahmednagar, Maharashtra, India.

Kanase, R. M. (2019). A Study on Tribological Behaviour of Nanocoated Piston Ring. i-manager’s Journal on Mechanical Engineering, 9(3), 19-25. https://doi.org/10.26634/jme.9.3.15913

Abstract

The nanopartical material coating can help to improve performance and life of internal combution automobile engines by reducing the frictional wear and friction between IC engine components. In this research study, tribological properties of titanium dioxide (TiO₂) nanocoatings for piston ring application are investigated. Nanocoating samples were prepared by sol-gel process of varying dipping and drying process cycles (40, 50, 60 and 70). In this research study, frictional wear has been carried out on Pin on Disc Tribometer and the tests were taken by varying load and speed. The obtained results shows that TiO₂ Nanocoating exhibits good friction reduction and anti-wear properties and also decreased the coefficient of friction by 4% and 8% at 60 and 70 dipping-drying process cycles respectively, as compared with conventional chromium plated jobs. Also the micrographs of worn surfaces were analyzed by using Scanning Electron Microscopy (SEM).

References

[1]. Adamkiewicz, A., & Drzewieniecki, J. (2012). Operational evaluation of piston ring wear in large marine diesel engines. Journal of Polish CIMAC, 7(1), 9-17.

[2]. Asthana, R., Kumar, A., & Dahotre, N. B. (2006). Nanomaterials and nanomanufacturing. Material processing and Manufacturing Science, 551-614. https://doi.org/10.1016/B978-075067716-5/50010-8

[3]. Dahotre, N. B., & Nayak, S. (2005). Nanocoatings for engine application. Surface and Coatings Technology, 194(1), 58-67. https://doi.org/10.1016/j.surfcoat.2004. 05.006

[4]. Holmberg, K., Ronkainen, H., Laukkanen, A., & Wallin, K. (2007). Friction and wear of coated surfaces—scales, modelling and simulation of tribomechanisms. Surface and Coatings Technology, 202(4-7), 1034-1049. https://doi.org/10.1016/j.surfcoat.2007.07.105

[5]. Jeong, D. H., Gonzalez, F., Palumbo, G., Aust, K. T., & Erb, U. (2001). The effect of grain size on the wear properties of electrodeposited nanocrystalline nickel coatings. Scripta Materialia, 3(44), 493-499. https://doi.org/10.1016/ S1359-6462(00)00625-4

[6]. Josephson, M., & Laesson, A. H. (2005). Nanostructured WC-Co coating. Retrieved from http://mixtra.se/nano/ PRES-NANO.pdf

[7]. Li, J. Z. (2013). Computational simulation and prototype testing of nanocoating on products in aerospace industry. In Advanced Materials Research (Vol. 750, pp. 2088-2091). Trans Tech Publications. https://doi.org/10.4028/www. scientific.net/AMR.750- 752.2088

[8]. Prabhu, S., & Vinayagam, B. K. (2009). Nanocoating for engine application. International Journal of Nanotechnology and Applications, 3(1),17-28.

[9]. Priyan, M. S., & Hariharan, P. (2012). The study on tribology and surface interface characterization of FE based alloy coating deposited by HVOF method. Procedia Engineering, 38, 3741-3756. https://doi.org/10.1016/ j.proeng.2012.06.430

[10]. Truhan, J. J., Qu, J., & Blau, P. J. (2005). A rig test to measure friction and wear of heavy duty diesel engine piston rings and cylinder liners using realistic lubricants. Tribology International, 38(3), 211-218. https://doi.org/ 10.1016/j.proeng.2012.06.430

[11]. Tung, S. C., & McMillan, M. L. (2004). Automotive tribology overview of current advances and challenges for the future. Tribology International, 37(7), 517-536. https://doi.org/10.1016/j.triboint.2004.01.013

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Research Paper

Investigation of Surface Roughness on Hybrid Composites using Stir Casting Technique

P. Saritha* , A. Satyadevi, P. Ravikanth Raju*

_ Department of Mechanical Engineering, GITAM University, Hyderabad, Telangana, India.

Department of Mechanical Engineering, Anurag Group of Institutions, Hyderabad, Telangana, India.

Saritha, P., Satyadevi, G., and Raju, P. R. (2019). Investigation of Surface Roughness on Hybrid Composites using Stir Casting Technique. i-manager’s Journal on Mechanical Engineering, 9(3), 26-31. https://doi.org/10.26634/jme.9.3.15891

Abstract

This paper brings out the results of hybrid composites produced by stir casting process. The material which is stir casted are processed by facing and turning operation using CNC machine in which turning, facing, step turning and milling operation are carried without changing the tools and workpiece in one setup. The metal removal takes place by varying speed and feed of the machine on work pieces. For modeling and enhancing performance of manufacturing technologies numerical methods are used. Optimum machining parameters plays a significant role in deciding the economy of work piece. The present work is aimed to find the optimal process parameters of hybrid composites during turning procedure. As it has wide applications in space and bearings this composites has been taken as work materials. To know the ideal process parameters, intellectual assessment tools are applied. In this work the Surface Roughness (R_a) of the three sample work pieces of hybrid composites were prepared by keeping 3% molybdenum disulphide constant and 5%, 10%, 15% varying silicon carbide reinforced with Al7075. The experiment have been planned according to Taguchi's L9 (3)³ .

References

[1]. Chavoshi, S. Z., & Tajdari, M. (2010). Surface roughness modelling in hard turning operation of AISI 4140 using CBN cutting tool. International Journal of Material Forming, 3(4), 233-239. https://doi.org/10.1007/s12289-009-0679-2

[2]. Čuš, F., & Župerl, U. (2015). Surface roughness control simulation of turning processes. Strojniški vestnik Journal of Mechanical Engineering, 61(4), 245-253. https://doi.org/ 10.5545/sv-jme.2014.2345

[3]. Doddapattar, B. N., & Puneeth, S. (2017). Optimization of cutting parameters using signal-to-noise ratio for turning aluminium alloy Al7050. International Journal of Ignited Minds (IJIMIINDS), 1(9), 1-6.

[4]. Krishnamurthy, L., Sridhara, B. K., & Budan, A. D. (2011). Comparative study on the machinability aspects of aluminium-silicon carbide and aluminium-graphite-silicon carbide hybrid composites. International Journal of Machining and Machinability of Materials, 10(1-2), 137- 152.

[5]. Manna, A. & Bhattacharyya, B. (2003). A study on machinability of Al/SiC-MMC, Journal of Materials Processing Technology, 140, 711-716.

[6]. Marcos-Bárcena, M., Sebastián-Pérez, M. A., Contreras-Samper, J. P., Sánchez-Carrilero, M., Sánchez- López, M., & Sánchez-Sola, J. M. (2005). Study of roundness on cylindrical bars turned of aluminium–copper alloys UNS A92024. Journal of Materials Processing Technology, 162, 644-648. https://doi.org/10.1016/ j.jmatprotec.2005.02.061

[7]. Özel, T., Hsu, T. K., & Zeren, E. (2005). Effects of cutting edge geometry, workpiece hardness, feed rate and cutting speed on surface roughness and forces in finish turning of hardened AISI H13 steel. The International Journal of Advanced Manufacturing Technology, 25(3-4), 262- 269. https://doi.org/10.1007/s00170-003-1878-5

[8]. Pop, A. B., & Titu, M. A. (2016, November). Regarding to the variance analysis of regression equation of the surface roughness obtained by end milling process of 7136 aluminium alloy. In IOP Conference Series: Materials Science and Engineering (Vol. 161, No. 1). IOP Publishing. https://doi.org/10.1088/1757-899X/161/1/012015

[9]. Prasad, T., Rao, P. C. S., & Kiran, B. R. (2017). Investigation of mechanical properties of Al7075 with magnesium oxide nano powder MMC. IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE), 60-65.

[10]. Rajan, B., & Avis, A. (2016). Optimization of suface roughness in turning by taguchi method. IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE), 78-82.

[11]. Ross, P. J. (2005). Taguchi Techniques for Quality Engineering, (7^th Ed.). New York, USA : McGraw-Hill.

[12]. Roy, R. K. (1990). A Primer on the Taguchi Method. (Competitive Manufacturing Series). (1^st Ed.). New York, USA: Van Nostrand Reinhold.

[13]. Saritha, P., Satyadevi, D., Raju, R. P., & Sri, P. S. (2018). Effect of zirconium on mechanical behavior of aluminum 7075. International Journal of Science and Research, 7(3), 945-948.

[14]. Singh, G. S., Singh, B., & Singh, K. (2014). K. Optimization of cutting forces during turning of Al/SiC/Gr hybrid metal matrix composite. International Journal of Research in Mechanical Engineering & Technology, 4(2), 135-138.

[15]. Srinivasan, A., Arunachalam, R. M., Ramesh, S., & Senthilkumaar, J. S. (2012). Machining performance study on metal matrix composites-a response surface methodology approach. American Journal of Applied Sciences, 9(4), 478-483.

[16]. Suksawat, B. (2011). Development of in-process surface roughness evaluation system for cast nylon 6 turning operation. Procedia Engineering, 15, 4841-4846. https://doi.org/10.1016/j.proeng.2011.08.903

[17]. Zębala, W., Gawlik, J., Matras, A., Struzikiewicz, G., & Ślusarczyk, Ł. (2014). Research of surface finish during titanium alloy turning. In Key Engineering Materials (Vol. 581, pp. 409-414). Trans Tech Publications. https://doi.org/10.4028/www.scientific.net/KEM.581.409

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Research Paper

Design and Analysis of First Stage Rocket Engine using Butane and Liquid Oxygen

Samarpan Deb Majumder*

Department of Mechanical Engineering, Institute of Engineering and Management, Kolkata, West Bengal, India.

Majumder, S. D. (2019). Design and Analysis of First Stage Rocket Engine using Butane and Liquid Oxygen. i-manager’s Journal on Mechanical Engineering, 9(3), 32-41. https://doi.org/10.26634/jme.9.3.15806

Abstract

The manuscript demonstrates the designing of a first stage rocket engine using butane as a fuel and liquid oxygen as the oxidizer combination for yielding higher values of heat of combustion, Mach number, specific Impulse and the exit velocity through the nozzle. The purpose of this research is to provide a fuel oxidizer combination whose heat of combustion would be much higher. With a higher calorific value of butane, it needs very little oxidizer to burn resulting in reducing the weight of the rocket. Chemical Experimental Analysis has shown that the calorific value of butane and liquid oxygen together will yield much higher values in comparison to that of the present combination of fuel and oxidizers. The research paper analyses the design calculations of the space shuttle engine; Solid Works Design of complete Rocket Engine; comparative study of the model rocket with the Orion test rocket; CFD analysis of Rocket Engine.

References

[1]. Aherne, M. R., Barrett, J. T., Hoag, L., Teegarden, E., & Ramadas, R. (2011). Aeneas--Colony I Meets Three-Axis Pointing. In 25^thAnnual AIAA/USU Conference on Small Satellite, SSC11-XII-7, 1-11.

[2]. Bainbridge, R., & Horton, T. R. (1971). The production of liquid hydrogen at the rocket propulsion establishment. Cryogenics, 11(6), 456-468. https://doi.org/10.1016/0011- 2275(71)90270-0

[3]. Geeroms, D., Bertho, S., De Roeve, M., Lempens, R., Ordies, M., & Prooth, J. (2015, September). ARDUSAT, an Arduino-Based CubeSat Providing Students with the Opportunity to Create their own Satellite Experiment and Collect Real-World Space Data. In 22^nd ESA Symposium on European Rocket and Balloon Programmes and Related Research (Vol. 730, p. 643-647).

[4]. Georgiadis, N., DalBello, T., Trefny, C., & Johns, A. (2006). Aerodynamic design and analysis of high performance nozzles for Mach 4 accelerator vehicles. In 44^thAIAA Aerospace Sciences Meeting and Exhibit (pp 1- 14). https://doi.org/10.2514/6.2006-16

[5]. Haidn, O. J. (2008). Advanced rocket engines. In Advances on Propulsion Technology for High-Speed Aircraft, 1, 6-1, 6-40.

[6]. Haidn, O. J., & Habiballah, M. (2003). Research on high pressure cryogenic combustion. Aerospace Science and Technology, 7(6), 473-491. https://doi.org/10.1016/S1270- 9638(03)00052-X

[7]. Kestilä, A., Tikka, T., Peitso, P., Rantanen, J., Näsilä, A., Nordling, K., ... & Hallikainen, M. (2013). Aalto-1 nanosatellite–technical description and mission objectives. Geoscientific Instrumentation, Methods and Data Systems, 2(1), 121-130. https://doi.org/10.5194/gid-2- 925-2012

[8]. Kim. J. T. (2003). A CubeSat (HAUSAT-1). Mission and system design. (Postgraduate Thesis). Korea Aerospace University.

[9]. Lim, L. S., Bui, T. D. V., Lau, Z., Soon, J. J., Lew, J. M., Aung, H., ... & Chen, S. S. (2015, August). Development and design challenges in VELOX-I nanosatellite. In 2015 International Conference on Space Science and Communication (IconSpace) (pp. 158-163). IEEE.

[10]. Mehrparvar, A., Pignatelli, D., Carnahan, J., Munakata, R., Lan, W., Toorian, A., ... & Lee, S. (2014). CubeSat design specification (CDS) REV 13. The CubeSat Project, San Luis Obispo, CA, 1-42.

[11]. Murphy, T., Kanaber, J., & Koehler, C. (2011). PEZ: expanding CubeSat capabilities through innovative mechanism design. In 25^th Annual AIAA/USU Conference on Small Satellite, SSC11-XII-5, 1-4.

[12]. Pohl, S., Jarczyk, M., Pfitzner, M., & Rogg, B. (2013). Real gas CFD simulations of hydrogen/oxygen supercritical combustion. Progress in Propulsion Physics, 4, 583-614. https://doi.org/10.1051/eucass/201304583

[13]. Ribert, G., Zong, N., Yang, V., Pons, L., Darabiha, N., & Candel, S. (2008). Counterflow diffusion flames of general fluids: Oxygen/hydrogen mixtures. Combustion and Flame, 154(3), 319-330. https://doi.org/10.1016/j.combustflame. 2008.04.023

[14]. Smith, M., Seager, S., Pong, C., Knutson, M., Miller, D., Henderson, T., ... & Murphy, S. (2011). The ExoplanetSat mission to detect transiting exoplanets with a cubesat space telescope. In 25^th Annual AIAA/USU Conference on Small Satellite, SSC11-XII-4, 1-9.

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[16]. Young, Q., Burt, R., Watson, M., & Zollinger, L. (2009, August). PEARL CubeSat bus building toward operational missions. In Small Satellites Conference from AIAA/Utah State University, Logan, Utah.

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Research Paper

Optimization Analysis of H-13 Alloy using EDM by Taguchi Method

Hareendranath Mada* , R. J. V. Anil Kumar**

*_** Department of Mechanical Engineering, Jawaharlal Nehru Technological University, Anantapuramu, Andhra Pradesh, India.

Mada, H., and Kumar, R. J. V. A. (2019). Optimization Analysis of H-13 Alloy using EDM by Taguchi Method. i-manager’s Journal on Mechanical Engineering, 9(3), 42-49. https://doi.org/10.26634/jme.9.3.16037

Abstract

The non-conventional machining methods are used for machining very hard materials and to prepare difficult shapes. Electrical discharge machining (EDM) is the most commonly used non-conventional machining processes for machining hard and brittle materials with good accuracy. Tool steel is an alloy of steel which is used for applications like die preparation, tool preparation etc. In this work, H-13 alloy of tool steel is selected for machining to find out Surface Roughness and Material Removal Rate (MRR) through EDM. It is also proposed to optimize EDM process parameters. The process parameters for optimisation are pulse on time, pulse off time, current, material removal rate and surface roughness. To optimize the process parameters Taguchi L9 Orthogonal array were used.

References

[1]. Aliakbari, E., & Baseri, H. (2012). Optimization of machining parameters in rotary EDM process by using the Taguchi method. The International Journal of Advanced Manufacturing Technology, 62(9-12), 1041-1053. https://doi.org/10.1007/s00170-011-3862-9

[2]. Dhanabalan, S., Sivakumar, K., & Narayanan, S. C. (2012). Optimization of EDM process parameters with multiple performance characteristics for titanium grades. European Journal of Scientific Research, 68(3), 297-305.

[3]. Gopalakannan, S., Senthilvelan, T., & Ranganathan, S. (2012). Modeling and optimization of EDM process parameters on machining of Al 7075-B4C MMC using RSM. Procedia Engineering, 38, 685-690. https://doi.org/ 10.1016/j.proeng.2012.06.086

[4]. Kodlinge, P. G., & Khire, M. (2012). Some studies on machinability of tungsten carbide during EDM operations. International Journal of Engineering Science and Technology, 3(1).

[5]. Kumar, A., & Maheshwari, S. (2015). Optimization of Submerged Arc Welding Rutile Based Flux constituents by Hybrid Grey, Fuzzy and Taguchi Analysis. Advanced Materials Manufacturing & Characterization, 5(2), 63-70.

[6]. Rao, P. S., Ramji, K., & Satyanarayana, B. (2014). Experimental investigation and optimization of wire EDM parameters for surface roughness, MRR and white layer in machining of aluminium alloy. Procedia Materials Science, 5, 2197-2206. https://doi.org/10.1016/j.mspro. 2014.07.426

[7]. Sivaiah, P., & Bodicherla, U. (2019). Effect of Surface Texture Tools and Minimum Quantity Lubrication (MQL) on tool Wear and Surface Roughness in CNC Turning of AISI 52100 Steel. Journal of The Institution of Engineers (India): Series C, 1–11. https://doi.org/10.1007/s40032-019-00512- 2

[8]. Sivaiah, P., & Chakradhar, D. (2017). Multi-objective optimisation of cryogenic turning process using Taguchibased grey relational analysis. International Journal of Machining and Machinability of Materials, 19(4), 297-312. https://doi.org/10.1504/IJMMM.2017.086161

[9]. Sivaiah, P., & Chakradhar, D. (2018a). Analysis and modeling of cryogenic turning operation using response surface methodology. Silicon, 10(6), 2751–2768. https://doi.org/10.1007/s12633-018-9816-1

[10]. Sivaiah, P., & Chakradhar, D. (2018b). Multi performance characteristics optimization in cryogenic turning of 17-4 PH stainless steel using Taguchi coupled grey relational analysis. Advances in Materials and Processing Technologies, 4(3), 431-447. https://doi.org/10. 1080/2374068X.2018.1452132

[11]. Sivaiah, P., & Chakradhar, D. (2019a). Modeling and optimization of sustainable manufacturing process in machining of 17-4 PH stainless steel. Measurement, 134, 142-152. https://doi.org/10.1016/j.measurement. 2018.10.067

[12]. Sivaiah, P., & Chakradhar, D. (2019b). The effectiveness of a novel cryogenic cooling approach on turning performance characteristics during machining of 17-4 PH stainless steel material. Silicon, 11(1), 25-38. https://doi.org/ 10.1007/s12633-018-9875-3

[13]. Sivaiah, P., & Chakradhar, D. (2019c). Performance improvement of cryogenic turning process during machining of 17-4 PH stainless steel using multi objective optimization techniques. Measurement, 136, 326-336. https://doi.org/10.1016/j.measurement.2018.12.094

[14]. Sivaiah, P., Mallikarjuna, P., Uma, B., & Chalapathi, K. V. (2018). Optimization of Environmental Friendly Turning Process Using Taguchi Integrated Grey Relational Analysis During Machining of 17-4 PH Stainless Steel. i-Manager's Journal on Mechanical Engineering, 8(4), 8-17. https://doi.org/10.26634/jme.8.4.14190

i-manager's Journal on Mechanical Engineering (JME)

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Volume 9 Issue 3 May - July 2019

Thermoeconomic Analysis of a Single Effect Mechanical Vapor Compression Desalination Unit

Giuma M. Fellah*

Department of Mechanical and Industrial Engineering, University of Tripoli, Libya.

Fellah, G. (2019). Thermoeconomic Analysis of a Single Effect Mechanical Vapor Compression Desalination Unit. i-manager’s Journal on Mechanical Engineering, 9(3),1-8. https://doi.org/10.26634/jme.9.3.15797

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Experimental Investigation and Optimization of Machining Parameters in Milling of Al6351 Using Hybrid – Artificial Bee Colony Algorithm

P. Hema* , G. Padmanabhan**, T. Eswar***

*_*** Department of Mechanical Engineering, S. V. University college of Engineering, Tirupati, Andhra Pradesh, India.

Hema, P., Padmanabhan, G., and Eswar, T. (2019). Experimental Investigation and Optimization of Machining Parameters in Milling of Al6351 Using Hybrid – Artificial Bee Colony Algorithm. i-manager’s Journal on Mechanical Engineering, 9(3),9-18. https://doi.org/10.26634/jme.9.3.16059

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A Study on Tribological Behaviour of Nanocoated Piston Ring

Ravindra M. Kanase*

Department of Automobile Engineering, Padmashri Dr. VitthalraoVikhe Patil, Institute of Technology & Engineering(Polytechnic) Pravaranagar, Loni, Ahmednagar, Maharashtra, India.

Kanase, R. M. (2019). A Study on Tribological Behaviour of Nanocoated Piston Ring. i-manager’s Journal on Mechanical Engineering, 9(3), 19-25. https://doi.org/10.26634/jme.9.3.15913

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Investigation of Surface Roughness on Hybrid Composites using Stir Casting Technique

P. Saritha* , A. Satyadevi**, P. Ravikanth Raju***

*_** Department of Mechanical Engineering, GITAM University, Hyderabad, Telangana, India. *** Department of Mechanical Engineering, Anurag Group of Institutions, Hyderabad, Telangana, India.

Saritha, P., Satyadevi, G., and Raju, P. R. (2019). Investigation of Surface Roughness on Hybrid Composites using Stir Casting Technique. i-manager’s Journal on Mechanical Engineering, 9(3), 26-31. https://doi.org/10.26634/jme.9.3.15891

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Design and Analysis of First Stage Rocket Engine using Butane and Liquid Oxygen

Samarpan Deb Majumder*

Department of Mechanical Engineering, Institute of Engineering and Management, Kolkata, West Bengal, India.

Majumder, S. D. (2019). Design and Analysis of First Stage Rocket Engine using Butane and Liquid Oxygen. i-manager’s Journal on Mechanical Engineering, 9(3), 32-41. https://doi.org/10.26634/jme.9.3.15806

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Optimization Analysis of H-13 Alloy using EDM by Taguchi Method

Hareendranath Mada* , R. J. V. Anil Kumar**

*_** Department of Mechanical Engineering, Jawaharlal Nehru Technological University, Anantapuramu, Andhra Pradesh, India.

Mada, H., and Kumar, R. J. V. A. (2019). Optimization Analysis of H-13 Alloy using EDM by Taguchi Method. i-manager’s Journal on Mechanical Engineering, 9(3), 42-49. https://doi.org/10.26634/jme.9.3.16037

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P. Hema* , G. Padmanabhan, T. Eswar*

P. Saritha* , A. Satyadevi, P. Ravikanth Raju*

_ Department of Mechanical Engineering, GITAM University, Hyderabad, Telangana, India.

Department of Mechanical Engineering, Anurag Group of Institutions, Hyderabad, Telangana, India.