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Prahlada Rao, K.
- Metal Injection Molding - A Review
Abstract Views :330 |
PDF Views:1
Authors
Affiliations
1 Madanapalle Institute of Technology and Science, Madanapalle, IN
2 J.N.T.U.A.College of Engineering, Anantapuramu, IN
1 Madanapalle Institute of Technology and Science, Madanapalle, IN
2 J.N.T.U.A.College of Engineering, Anantapuramu, IN
Source
Manufacturing Technology Today, Vol 15, No 12 (2016), Pagination: 3-10Abstract
Metal Injection Molding (MIM) is relatively a new technology for producing metal components of complex geometry. MIM is an extension of powder metallurgy process. Various products of metals and its alloys including difficult-to-machine materials such as titanium, tungsten etc., can be effectively manufactured by MIM process. MIM process comprises of four steps; mixing of metal powders with binders, injection molding of coated-metal powders to produce green parts, de-binding to separate binders from green part and the final stage is sintering. The process parameters in mixing, injection molding, de-binding and sintering play a vital role in the quality of final product.
This paper is aimed at reviewing the MIM process parameters and materials.
Keywords
MIM, Green Part, Sintering, Binder, Metal Powders, Mixing, De-Binding.
References
- Moballegh, L; Morshedian, J; Esfandeh, M: Copper injection molding using a thermoplastic binder based on paraffin wax, 'Materials Letters', vol. 59, no. 22, 2005, 2832-2837.
- Liu, ZY; Loh, NH; khor, KA; Tor, SB: Sintering of injection molded M2 high-speed steel, 'Material Letters', vol. 45, no. 1, 2000, 32-38.
- Ozgun, Ozgur; Gulsoy, H Ozkan; Yilmaz, Ramazan; Findik, Fehim: Injection molding of nickel based 625 superalloy: Sintering, heat treatment, microstructure and mechanical properties, 'Journal of Alloys and Compounds', vol. 546, 2013, 192-207.
- Ebel, T: Metal Injection Molding of Titanium, 'Materials Science Forum', vol. 690, 2011, 181-184.
- Luo, TG; Qu, XH; Qin, ML; Ouyang, ML: Dimension precision of metal injection molded pure tungsten, 'Int. Journal of Refractory Metals & Hard Materials', vol. 27, no. 3, 2009, 615-620.
- Loh, NH; Tor, SB; Khor, KA: Production of metal matrix composite part by powder injection molding, 'Journal of Materials Processing Technology', vol. 108, no. 3, 2001, 398-407.
- Li, Duxin; Hou, Haitao; Tan, Zhaoqiang; Lee, Kun: Metal injection Molding of pure Molybdenum, 'Advanced Powder Technology', vol. 20, no. 5, 2009, 480-487.
- Ye, Hezhou; Liu, Xing Yang; Hong, Hanping: Fabriction of metal matrix composites by metal injection molding - A review, 'Journal of Materials Processing Technology', vol. 200, no. 1-3, 2008, 12-24.
- Kryachek, VM: Injection Molding (Review), 'Powder Metallurgy and Metal Ceramics', vol. 43, no. 7-8, 2004.
- Bose, Animesh; Otsuka, Isamu, Yoshida, Takafumi; Toyashima, Hisataka: Metal Injection Molding of Ultra-Fine 316L Stainless Steel Powders, 'Advances in Powder Metallurgy & Particulate Materials', 2007.
- Loh, NH; Tor, SB; Khor, KA: Production of metal matrix composite part by powder injection molding, 'Journal of materials processing technology', vol. 108, no. 3, 2001, 398-407.
- Hwang, KS: Common defects in metal injection molding (MIM).
- Piotter, V: Micro metal injection molding (MicroMIM).
- Shu-quan, Liang; Yan, Tang; Bai-yun, Huang: Rheology in metal powder injection molding, J.Cent . South Univ. Technol., 2007, sl-0372-06
- Simultaneous Scheduling of Machines and Tools to Minimise Makespan in Multi Machine FMS Using New Nature Inspired Algorithms
Abstract Views :240 |
PDF Views:2
Authors
Affiliations
1 JNTUA, Ananthpuram, AP, IN
2 GIET, Rajahmundhry, IN
3 JNTUACEA, Ananthapuram, IN
1 JNTUA, Ananthpuram, AP, IN
2 GIET, Rajahmundhry, IN
3 JNTUACEA, Ananthapuram, IN
Source
Manufacturing Technology Today, Vol 16, No 3 (2017), Pagination: 19-27Abstract
This article addresses simultaneous scheduling of machines and tools to generate best optimal sequences that minimize makespan in a multi-machine Flexible Manufacturing System (FMS). Performance of FMS is expected to improve by effective utilization of its resources, by proper integration and synchronization of their scheduling. Three heuristics, Symbiotic Organisms Search (SOS) algorithm, Crow search algorithm(CSA) and Flower pollination algorithm(FPA), have been proposed for solving joint machine and tool scheduling problems neglecting tool transfer times between machines with makespan as objective. The proposed heuristics are tested on various problems with makespan as objective and the results are compared with the results of existing methods. The results show that all the proposed heuristics are outperformed the existing methods and among the proposed heuristics FPA is outperformed.Keywords
Flexible Manufacturing Systems, Symbiotic Organisms Search Algorithm, Crow Search Algorithm, Flower Pollination Algorithm, Simultaneous Scheduling of Tools & Machines.References
- Agnetis, A; Alfieri, A; Brandimarte, P; Prinsecchi, P: Joint Job/Tool Scheduling in a Flexible Manufacturing Cell with No On-Board Tool Magazine, ‘Computer Integrated Manufacturing System’, vol. 10, no. 1, 1997, 61-68.
- Baker, KR: Introduction to Sequencing and Scheduling, Wiley, New York, 1974.
- Jerald, J; Asokan, P: Simultaneous Scheduling of Parts and Automated Guided Vehicles in an FMS Environment using Adaptive Genetic Algorithm, ‘International Journal of Advanced Manufacturing Technology’, vol. 29, no. 5, 2006, 584-589.
- Lee, D; Dicesare, F: Integrated Scheduling of FMSs Employing Automated Guided Vehicles, ‘IEEE Transactions on Industrial Electronics’, vol. 41, no. 6, 1994, 602-610.
- Tsukada, TK; Shin, KG: Distributed Tool Sharing in Flexible Manufacturing Systems, IEEE Transactions on Robotics and Automation, vol.14, no. 3, 1998, 379-389.
- Jun, H; Kim, Y; Sub, H: Heuristics for a Tool Provisioning Problem in a Flexible Manufacturing System with an Automatic Tool Transporter, ‘IEEE Transactions on Robotics and Automation’, vol. 15, no. 3, 1999, 488-497.
- Sureshkumar, N; Sridharan, R: Simulation Modeling and Analysis of Tool Flow Control Decisions in Single Stage Multimachine Flexible Manufacturing System, ‘Robotics and Computer Integrated Manufacturing’, vol. 23, 2007, 361-370.
- Sureshkumar, N; Sridharan, R: Simulation Modeling and Analysis of Tool Flow Control Decisions in a Flexible Manufacturing System, ‘Robotics and Computer Integrated Manufacturing’, vol. 25, 2009, 829-838.
- Prabaharan, T; Nakkeeran, PR; Jawahar, N; Sequencing and Scheduling of Job and Tool in Flexible Manufacturing Cell, ‘International Journal of Advanced Manufacturing Technology’, vol. 29, no. 3, 2006, 729-745.
- Udhayakumar, P; Kumanan, S: Sequencing and Scheduling of Job and Tool in Flexible Manufacturing System Using Ant Colony Optimization Algorithm, ‘International Journal of Advanced Manufacturing Technology’, vol. 50, no. 9, 2010, 1075-1084.
- Aldrin Raj, J; Ravindran, D; Saravanan, M; Prabaharan, T: Simultaneous scheduling of machines and tools in multimachine flexible manufacturing system using artificial immune system algorithm, ‘International Journal of Computer Integrated Manufacturing’, vol. 27, no. 5, 2014, 401-414.
- Cheng, Min-Yuan; Prayogo, Doddy: Symbiotic Organisms Search: A new metaheuristic optimization algorithm, ‘Computers and Structures’, vol. 139, 2014, 98–112.
- Askarzadeh, Alireza: A novel metaheuristic method for solving constrained engineering optimization problems: Crow search algorithm, ‘Computers and Structures’, vol. 169, 2016, 1-12.
- Yang, Xin-She: Flower Pollination Algorithm for global optimization, Unconventional computation and natural computation 2012, LNCS’, vol. 7445, 2012, 240-249
- Photoelastic Stress Intensification of Fillet Welded T-Joint
Abstract Views :153 |
PDF Views:0
Authors
Affiliations
1 Dept. of Mechanical Engg., S. R. K. R. Engg. College, Bhimavaram, IN
2 Department of Mechanical Engg., J. N. T. U. College of Engg., Anantapur, IN
1 Dept. of Mechanical Engg., S. R. K. R. Engg. College, Bhimavaram, IN
2 Department of Mechanical Engg., J. N. T. U. College of Engg., Anantapur, IN
Source
Manufacturing Technology Today, Vol 8, No 7 (2009), Pagination: 31-40Abstract
Fillet welded T-Joint with and without crack like discontinuities (such as undercut, overlap and intrinsic flaw) is analyzed using photo elasticity technique. Unit stress intensification for opening mode and shearing mode are determined for the model having intrinsic flaw containing undercut, overlap at lower and upper toes under various loading conditions, weld leg sizes and weld shapes. The photoelasticity results are given in terms of unit stress intensity factor Vs load angle. The influences of applied load angle, weld leg size and weld shape on weld discontinuities are studied.- High Speed Machining of Al-SiC (20p) MMC Using PCD Inserts
Abstract Views :172 |
PDF Views:0
Authors
Affiliations
1 Dept. of Mech. Engg., Sri Venkateswara College of Engineering, Sriperumbudur, IN
2 GTRE (DRDO), Bangalore, IN
3 XLRI, Jamshedpur, IN
4 JNTU College of Engineering, Anantapur, IN
5 BSA Crescent Engineering College, Chennai, IN
1 Dept. of Mech. Engg., Sri Venkateswara College of Engineering, Sriperumbudur, IN
2 GTRE (DRDO), Bangalore, IN
3 XLRI, Jamshedpur, IN
4 JNTU College of Engineering, Anantapur, IN
5 BSA Crescent Engineering College, Chennai, IN
Source
Manufacturing Technology Today, Vol 6, No 10 (2007), Pagination: 10-15Abstract
Aluminium Silicon Carbide (Al.SiC) metal matrix composite (MMC) materials have a set of mechanical and physical properties that are ideally suited for applications in aerospace, automobile industries. Despite the superior set of mechanical and physical properties, the usage of MMC's in industry is still limited owing to difficulties in machining. To overcome this barrier, this paper performs a thorough study about the machinability of Al-SiC (MMC) with PCD insert tool to establish machining guidelines.The focus of the investigation is to determine the optimum machining conditions by adjusting the spindle speeds, depth of cut and feed, and observing the corresponding behaviour of cutting force, surface imperfections, power consumed, and MRR. The worn out tool is subjected to microscopic analysis to evaluate the wear on the tool.On completion of the experimental test, an artificial neural network (ANN) is used to validate the results obtained and also to predict the behaviour of the system under any condition within the operating range.- Simultaneous Scheduling of Machines and AGVs Using Flower Pollination Algorithm: A New Nature-Inspired Meta-Heuristic
Abstract Views :207 |
PDF Views:0
Authors
Affiliations
1 JNTUA, Ananthapuram, Andhra Pradesh, IN
2 GIET, Rajahmundhry, Andhra Pradesh, IN
3 JNTUACEA, Ananthapuram, Andhra Pradesh, IN
1 JNTUA, Ananthapuram, Andhra Pradesh, IN
2 GIET, Rajahmundhry, Andhra Pradesh, IN
3 JNTUACEA, Ananthapuram, Andhra Pradesh, IN
Source
Manufacturing Technology Today, Vol 17, No 7 (2018), Pagination: 19-30Abstract
This paper addresses the problem of simultaneous scheduling of machines and two identical automated guided vehicles (AGVs) in a flexible manufacturing system (FMS). It is a NP–hard problem which is very complex. For solving this problem, a new nature inspired meta-heuristic Flower pollination Algorithm (FPA) is proposed. The problem consists of two interrelated problems, scheduling of machines and scheduling of AGVs. A simultaneous scheduling of these, in order to minimize the makespan will result in an FMS being able to complete all the jobs assigned to it at earliest time possible, thus saving resources. Improvement in performance of FMS can be expected by efficient utilization of its resources, by proper integration and synchronization of their scheduling. The proposed heuristic is tested on problems generated by various researchers and the results are compared with results of existing methods. The results show that the proposed heuristic is outperformed the existing methods.Keywords
Flexible Manufacturing Systems, Flower Pollination Algorithm, Simultaneous Scheduling of Machines and AGVs, Minimization of Makespan.References
- Baker, KR: Introduction to Sequencing and Scheduling. New York, Wiley, 1974.
- Lee, D and DICESARE, F: Integrated Scheduling of FMSs Employing Automated Guided Vehicles, 'IEEE Transactions on Industrial Electronics', 41(6), 1994, 602–610.
- Agnetis, Alfieri, AA; Brandimarte, P and Prinsecchi, P: Joint Job/Tool Scheduling in a Flexible Manufacturing Cell with No On-Board Tool Magazine” 'Computer Integrated Manufacturing System', 10(1), 1997, 61–68.
- Jerald, J; and Asokan, P: Simultaneous Scheduling of Parts and Automated Guided Vehicles in an FMS Environment using Adaptive Genetic Algorithm. International Journal of Advanced Manufacturing Technology, 29(5), 2006, 584–589.
- Raman, N; Talbot, FB, Rachamadgu, RV: Simultaneous scheduling of machines and material handling devices in automated manufacturing [C]// Stecke KE, Suri R: Proceedings of the Second ORSA/TIMS Conference on Flexible Manufacturing Systems. University of Michigan, Ann Arbor, MI, USA, 1986: 455−466.
- Ulusoy, G; Bilge U: Simultaneous scheduling of machines and automated guided vehicles [J], 'International Journal of Production Research', 1993, 31(12): 2857−2873.
- Bilge, U; Ulusoy, G: A time window approach to simultaneous scheduling of machines and material handling system in FMS [J]. 'Operations Research', 1995, 43: 1058−1070.
- Ulusoy, G; Sivrikaya-Serifoglu F; Bilge,U: A genetic algorithm approach to the simultaneous scheduling of machines and automated guided vehicles [J]. 'Computers & Industrial Engineering', 1997, 24(4): 335−351.
- Abdelmaguid, TF; Nassef, ON; Kamal, BA; Hassan, MF: A hybrid GA/heuristic approach to the simultaneous scheduling of machines and automated guided vehicles [J]. 'International Journal of Production Research', 2004, 42: 267−281.
- Murayama, N; Kawata, S: A genetic algorithm approach to simultaneous scheduling of processing machines and multiple-load automated guided vehicles [J]. 'Transactions of the Japan Society of Mechanical Engineers C', 2005, 71(712): 3638−3643. (in Japanese)
- Jerald J; Asokan P, Saravanan R, Rani, A D C. Simultaneous scheduling of parts and AGVs in an FMS using non-traditional optimization algorithms [J], 'International Journal of Applied Management and Technology, 2005, 3(1): 305−315.
- Jerald, J; Asokan, P; Saravanan, R, RANI A D C: Simultaneous scheduling of parts and automated guided vehicles in an FMS environment using adaptive genetic algorithms [J], 'International Journal of Advanced Manufacturing Technology', 2006, 59: 584−589.
- Murayama, N; Kawata, S: Simulated annealing method for simultaneous scheduling of machines and multiple-load AGVs [C]// IJCC Workshop on Digital Engineering. Pyeongchang-gun, Gangwon-do, SouthKorea, 2006: 55−62. (in Japanese)
- Reddy, BSP; Rao, C S P: A hybrid multi-objective GA for simultaneous scheduling of machines and AGVs in FMS [J]. 'International Journal of Advanced Manufacturing Technology', 2006, 31(5/6): 602−613.
- Deroussi, L; Gourgand, M; Tchernev, N: A simple met heuristic approach to the simultaneous scheduling of machines and automated guided vehicles [J]. 'International Journal of Production Research', 2008, 46(8): 2143−2164.
- Philippe Lacomme, Mohand Larabi, Nikolay Tchernev Job-shop based framework for simultaneous scheduling of machines and automated guided vehicles, 'Int. J. Production Economics', 143, 2013, 24–34
- Stecke, KE: Design, planning, scheduling, and control problems of flexible manufacturing systems [J]. 'Annals of Operations Research', 1985, 3(1): 3−12.
- Xin-She Yang, Flower pollination algorithm for global optimization, in: Unconventional Computation and Natural Computation 2012, Lecture Notes in Computer Science, vol. 7445, 2012, 240-249
- Simultaneous Scheduling of Machines and AGVs Using Crow Search Algorithm: A New Nature-Inspired Meta-Heuristic
Abstract Views :237 |
PDF Views:2
Authors
Affiliations
1 JNTUA, Ananthpuram, AP, IN
2 GIET, Rajahmundhry, IN
3 Mech. Engg. JNTUACEA, Ananthapuram, IN
1 JNTUA, Ananthpuram, AP, IN
2 GIET, Rajahmundhry, IN
3 Mech. Engg. JNTUACEA, Ananthapuram, IN
Source
Manufacturing Technology Today, Vol 17, No 9 (2018), Pagination: 19-30Abstract
This paper addresses the problem of simultaneous scheduling of machines and two identical automated guided vehicles (AGVs) in a flexible manufacturing system (FMS). It is a NP–hard problem which is very complex. For solving this problem, a new nature inspired meta-heuristic Crow Search Algorithm (CSA) is proposed. The problem consists of two interrelated problems, scheduling of machines and scheduling of AGVs. A simultaneous scheduling of these, in order to minimize the makespan will result in an FMS being able to complete all the jobs assigned to it at earliest time possible, thus saving resources. Improvement in performance of FMS can be expected by efficient utilization of its resources, by proper integration and synchronization of their scheduling. The proposed heuristic is tested on problems generated by various researchers and the results are compared with the results of existing methods. The results show that the proposed heuristic outperforms the existing methods.Keywords
Flexible Manufacturing Systems, Crow Search Algorithm, Simultaneous Scheduling of Machines and AGVs, Minimization of Makespan.References
- Baker, K.R Introduction to Sequencing and Scheduling. New York, Wiley, 1974.
- Lee,D; ANDF.DICESARE. Integrated Scheduling of FMSs Employing Automated Guided Vehicles, IEEE Transactions on Industrial Electronics, 41(6), 602–610, 1994.
- AGNETIS, A.A.ALFIERI, P BRANDIMARTE, and P. Prinsecchi: Joint Job/Tool Scheduling in a Flexible Manufacturing Cell with No On-Board Tool Magazine, 'Computer Integrated Manufacturing System', 10 (1), 61–68 1997.
- Jerald, J; Asokan, P: Simultaneous Scheduling of Parts and Automated Guided Vehicles in an FMS Environment using Adaptive Genetic Algorithm, 'International Journal of Advanced Manufacturing Technology', 29 (5), 584–589, 2006.
- Raman, N; Talbot, FB, Rachamadgu, RV: Simultaneous scheduling of machines and material handling devices in automated manufacturing [C]// STECKE K E, SURI R. Proceedings of the Second ORSA/TIMS Conference on Flexible Manufacturing Systems. University of Michigan, Ann Arbor, MI,USA, 1986: 455−466.
- Ulusoy, G; Bilge, U: Simultaneous scheduling of machines and automated guided vehicles [J].
- International Journal of Production Research, 1993, 31(12): 2857−2873.
- Bilge U, Ulusoy G: A time window approach to simultaneous scheduling of machines and material handling system in FMS [J]. Operations Research, 1995, 43: 1058−1070.
- Ulusoy, G; Sivrikaya-Serifoglu F, Bilge U: A genetic algorithm approach to the simultaneous scheduling of machines and automated guided vehicles [J], 'Computers & Industrial Engineering', 1997, 24 (4): 335−351.
- Abdelmaguid, TF; Nassef, ON; Kamal, BA; Hassan, MF: A hybrid GA/heuristic approach to the simultaneous scheduling of machines and automated guided vehicles [J], 'International Journal of Production Research', 2004, 42: 267−281.
- Murayama, N; Kawata, S: A genetic algorithm approach to simultaneous scheduling of processing machines and multiple-load automated guided vehicles [J], 'Transactions of the Japan Society of Mechanical Engineers C', 2005, 71 (712): 3638−3643. (in Japanese)
- Jerald, J; Asokan, P; Saravanan, R; Rani A D C: Simultaneous scheduling of parts and AGVs in an FMS using non-traditional optimization algorithms [J], 'International Journal of Applied Management and Technology', 2005, 3(1): 305−315.
- Jerald, J; Asokan P; Saravanan R; Rani A D C: Simultaneous scheduling of parts and automated guided vehicles in an FMS environment using adaptive genetic algorithms [J], 'International Journal of Advanced Manufacturing Technology', 2006, 59: 584−589
- Murayama, N; Kawata, S: Simulated annealing method for simultaneous scheduling of machines and multiple-load AGVs [C]// IJCC Workshop on Digital Engineering, Pyeongchang-gun, Gangwon-do, South Korea, 2006: 55−62. (in Japanese)
- Reddy, B S P; Rao, C S P: A hybrid multi-objective GA for simultaneous scheduling of machines and AGVs in FMS [J], 'International Journal of Advanced Manufacturing Technology', 2006, 31 (5/6): 602−613.
- Deroussi, L; Gourgand, M; Tchernev, N: A simple met heuristic approach to the simultaneous scheduling of machines and automated guided vehicles [J]. International Journal of Production Research, 2008, 46(8): 2143−2164.
- Philippe Lacomme, Mohand Larabi, Nikolay Tchernev: Job-shop based framework for simultaneous scheduling of machines and automated guided vehicles, 'Int. J. Production Economics', 143, 2013, 24–34
- Stecke, KE: Design, planning, scheduling, and control problems of flexible manufacturing systems [J], 'Annals of Operations Research', 1985, 3(1):3−12.
- Alireza Askarzadeh, A novel metaheuristic method for solving constrained engineering optimization problems: Crow search algorithm,Computers and Structures 169, 2016, 1– 12