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Introduction to Advanced Manufacturing Processes and Optimization Methodologies Read chapter Read first chapter

2021 | OriginalPaper | Chapter

5. Optimization of Abrasive Water Jet Machining (AWJM)

Authors : Apoorva Shastri, Aniket Nargundkar, Anand J. Kulkarni

Published in: Socio-Inspired Optimization Methods for Advanced Manufacturing Processes

Publisher: Springer Singapore

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Abstract

Abrasive Water Jet Machining (AWJM) is an advanced version of Abrasive Jet Machining (AWJ) which employs water as the carrier medium for abrasive particles. The AWJM process can machine complex shapes and importantly, doesn’t generate heat concentrated zones. Work piece thickness, nozzle diameter, standoff distance and traverse speed are the typical process parameters/variables for AWJM. Kerf taper angle and surface roughness are performance responses as they indicate the geometry and surface finish of machined component, respectively.

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previous chapter Optimization of Electric Discharge Machining (EDM)
next chapter Optimization of Micro Milling Process
Literature
1.
Armağan M, Arici AA (2017) Cutting performance of glass-vinyl ester composite by abrasive water jet. Mater Manuf Process 32(15):1715–1722 CrossRef
2.
Dhanawade A, Kumar S, Kalmekar RV (2016) Abrasive water jet machining of carbon epoxy composite. Def Sci J 66(5):522–528 CrossRef
3.
Eberhart R, Kennedy J (1995) A new optimizer using particle swarm theory. In: MHS’95, Proceedings of the sixth international symposium on micro machine and human science. IEEE, pp 39–43
4.
Gostimirovic M, Pucovsky V, Sekulic M, Rodic D, Pejic V (2019) Evolutionary optimization of jet lag in the abrasive water jet machining. Int J Adv Manuf Technol 101(9–12):3131–3141 CrossRef
5.
Gulia V, Nargundkar A (2019) Optimization of process parameters of abrasive water jet machining using variations of cohort intelligence (CI). In: Applications of artificial intelligence techniques in engineering. Springer, Singapore, pp 467–474
6.
7.
Jagadeesh T (2015) Non traditional machining. Mechanical Engineering Department, National Institute of Technology, Calicut
8.
Jain VK (2008) Advanced (non-traditional) machining processes. In: Machining. Springer, London, pp 299–327
9.
Kechagias J, Petropoulos G, Vaxevanidis N (2012) Application of Taguchi design for quality characterization of abrasive water jet machining of TRIP sheet steels. Int J AdvManuf Technol 62(5–8):635–643 CrossRef
10.
11.
Kulkarni AJ, Durugkar IP, Kumar M (2013) Cohort intelligence: a self supervised learning behavior. In: 2013 IEEE international conference on systems, man, and cybernetics. IEEE, pp 1396–1400
12.
Momber AW, Kovacevic R (2012) Principles of abrasive water jet machining. Springer Science & Business Media
13.
Patankar NS, Kulkarni AJ (2018) Variations of cohort intelligence. Soft Comput 22(6):1731–1747 CrossRef
14.
Samanta S, Chakraborty S (2011) Parametric optimization of some non-traditional machining processes using artificial bee colony algorithm. Eng Appl Artif Intell 24(6):946–957 CrossRef
15.
Schwartzentruber J, Narayanan C, Papini M, Liu HT (2016) Optimized abrasive waterjet nozzle design using genetic algorithms. In: The 23rd international conference on water jetting. At Seattle, USA
16.
Shanmugam DK, Nguyen T, Wang J (2008) A study of delamination on graphite/epoxy composites in abrasive waterjet machining. Compos A Appl Sci Manuf 39(6):923–929 CrossRef
17.
Shastri AS, Kulkarni AJ (2018) Multi-cohort intelligence algorithm: an intra-and inter-group learning behaviour based socio-inspired optimisation methodology. Int J Parallel Emergent Distrib Syst 33(6):675–715 CrossRef
18.
19.
Shukla R, Singh D (2017) Experimentation investigation of abrasive water jet machining parameters using Taguchi and evolutionary optimization techniques. Swarm and Evolut Comput 32:167–183 CrossRef
20.
Shukla R, Singh D (2017) Selection of parameters for advanced machining processes using firefly algorithm. Eng Sci Technol Int Jl 20(1):212–221
21.
Simon D (2008) Biogeography-based optimization. IEEE Trans Evol Comput 12(6):702–713 CrossRef
22.
Yang XS, Deb S (2009) Cuckoo search via Lévy flights. In: 2009 world congress on nature & biologically inspired computing (NaBIC). IEEE, pp 210–214
23.
Yang XS, (2009) Firefly algorithms for multimodal optimization. In: International symposium on stochastic algorithms. Springer, Berlin, Heidelberg. pp 169–178
24.
Zain AM, Haron H, Sharif S (2011) Estimation of the minimum machining performance in the abrasive water jet machining using integrated ANN-SA. Expert Syst Appl 38(7):8316–8326 CrossRef
Metadata
Title
Optimization of Abrasive Water Jet Machining (AWJM)
Authors
Apoorva Shastri
Aniket Nargundkar
Anand J. Kulkarni
Copyright Year
2021
Publisher
Springer Singapore
Book
Socio-Inspired Optimization Methods for Advanced Manufacturing Processes

Print ISBN: 978-981-15-7796-3

Electronic ISBN: 978-981-15-7797-0

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-15-7797-0_5

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