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2021 | OriginalPaper | Buchkapitel

1. Introduction to Advanced Manufacturing Processes and Optimization Methodologies

verfasst von : Apoorva Shastri, Aniket Nargundkar, Anand J. Kulkarni

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

Verlag: Springer Singapore

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Abstract

Manufacturing can be defined as the application of mechanical, physical, and chemical processes to convert the geometry, properties, and/or shape of raw material into finished parts or products. This includes all intermediate processes required for the production and integration of the final product. Manufacturing involves interrelated activities which include product design, material selection, production process planning, production, quality assurance, management and marketing of products.

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Nächstes Kapitel A Brief Review of Socio-inspired Metaheuristics
Literatur
1.
Armağan M, Arici AA (2017) Cutting performance of glass-vinyl ester composite by abrasivewater jet. Mater Manuf Processes 32(15):1715–1722
2.
Asad ABMA, Masaki T, Rahman M, Lim HS, Wong YS (2007) Tool-based micro-machining. J Mater Process Technol 192:204–211
3.
Bao W, Chen P, Tansel I, Reen NS, Yang S, Rincon D (2003) Selection of optimal cutting conditions by using the genetically optimized neural network system (GONNS). In: Kaynak O, Alpaydin E, Oja E, Xu L (eds) Artificial neural networks and neural information processing—ICANN/ICONIP 2003. ICANN 2003, ICONIP 2003. Lecture Notes in Computer Science, vol 2714. Springer, Berlin, Heidelberg
4.
Bhattacharyya B, Gangopadhyay S, Sarkar BR (2007) Modelling and analysis of EDMed job surface integrity. J Mater Process Technol 189(1–3):169–177
5.
Camposeco-Negrete C (2019) Prediction and optimization of machining time and surface roughness of AISI O1 tool steel in wire-cut EDM using robust design and desirability approach. Int J Adv Manuf Technol 1–12
6.
Dang XP (2018) Constrained multi-objective optimization of EDM process parameters using kriging model and particle swarm algorithm. Mater Manuf Processes 33(4):397–404
7.
Das MK, Kumar K, Barman TK, Sahoo P (2014) Application of artificial bee colony algorithm for optimization of MRR and surface roughness in EDM of EN31 tool steel. Procedia Mater Sci 6:741–751
8.
Dewangan S, Gangopadhyay S, Biswas CK (2015) Multi-response optimization of surface integrity characteristics of EDM process using grey-fuzzy logic-based hybrid approach. Eng Sci Technol Int J 18(3):361–368
9.
Di Orio G, Cândido G, Barata J, Scholze S, Kotte O, Stokic D (2013) Self-learning production systems (SLPS)-optimization of manufacturing process parameters for the shoe industry. In: 2013 11th IEEE international conference on industrial informatics (INDIN). IEEE, pp 386–391
10.
Dow TA, Scattergood RO (2003) Mesoscale and microscale manufacturing processes: challenges for materials, fabrication and metrology. In: Proceedings of the ASPE winter topical meeting, vol. 28. pp 14–19)
11.
Durairaj M, Gowri S (2013) Parametric optimization for improved tool life and surface finish in micro turning using genetic algorithm. Procedia Eng 64:878–887
12.
Filiz S, Ozdoganlar OB (2010) A model for bending, torsional, and axial vibrations of microand macro-drills including actual drill geometry-part 1: model development and numerical solution. J Manuf Sci Eng 132:041017–1–8
13.
Ganapathy S, Balasubramanian P, Senthilvelan T, Kumar R (2019) Multi-response optimization of machining parameters in EDM using square-shaped nonferrous electrode. In: Adv Manuf Process. Springer, Singapore, pp 287–295
14.
Gopalakannan S, Senthilvelan T (2014) Optimization of machining parameters for EDM operations based on central composite design and desirability approach. J Mech Sci Technol 28(3):1045–1053
15.
Gopalsamy BM, Mondal B, Ghosh S (2009) Taguchi method and ANOVA: An approach for process parameters optimization of hard machining while machining hardened steel
16.
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
17.
Gupta K, Jain NK, Laubscher R (2017) Chapter 4-advances in gear manufacturing. In: Advanced gear manufacturing and finishing, 67–125
18.
Huo D, Cheng K, Wardle F (2010) Design of a five-axis ultra-precision micro-milling machine—ULTRAMIll. Part 1: holistic design approach, design considerations and specifications. Int J Adv Manuf Technol 47(9–12): 867–877
19.
Jagadeesh T (2015) Non traditional machining. Mechanical Engineering Department, National Institute of Technology, Calicut
20.
Jain VK (2008) Advanced (non-traditional) machining processes. In: Machining. Springer, London, pp 299–327
21.
Kolli M, Kumar A (2015) Effect of dielectric fluid with surfactant and graphite powder on electrical discharge machining of titanium alloy using Taguchi method. Eng Sci Technol Int J 18(4):524–535
22.
Kumar SL, Jerald J, Kumanan S, Aniket N (2014) Process parameters optimization for micro end-milling operation for CAPP applications. Neural Comput Appl 25(7–8):1941–1950
23.
Malekian M, Park SS, Jun MBG (2009) Modeling of dynamic micro-milling cutting forces. Int J Mach Tools Manuf 49:586–598
24.
Momber AW, Kovacevic R (2012) Principles of abrasive water jet machining. Springer Science& Business Media
25.
Muthuramalingam T, Mohan B (2015) A review on influence of electrical process parameters in EDM process. Arch Civil Mech Eng 15(1):87–94
26.
Palani S, Natarajan U, Chellamalai M (2013) On-line prediction of micro-turning multi-response variables by machine vision system using adaptive neuro-fuzzy inference system (ANFIS). Mach Vis Appl 24(1):19–32
27.
Rahman M, Kumar AS, Prakash JRS (2001) Micro milling of pure copper. J Mater Process Technol 116(1):39–43
28.
Rahman AA, Mamat A,Wagiman A (2009) Effect of machining parameters on hole quality of micro drilling for brass. Modern Appl Sci 3(5):221–230
29.
Rao RV (2010) Advanced modelling and optimization of manufacturing processes: international research and development. Springer Science & Business Media
30.
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
31.
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
32.
33.
Shukla R, Singh D (2017) Experimentation investigation of abrasive water jet machining parameters using Taguchi and Evolutionary optimization techniques. SwarmEvolut Comput 32:167–183
34.
Sofuoğlu MA, Çakır FH, Kuşhan MC, Orak S (2019) Optimization of different non-traditional turning processes using soft computing methods. Soft Comput 23(13):5213–5231
35.
Teimouri R, Baseri H (2014) Optimization of magnetic field assisted EDM using the continuous ACO algorithm. Appl Soft Comput 14:381–389
36.
Yang XS, Deb S (2009) Cuckoo search via Lévy flights. In: 2009 world congress on nature & biologically inspired computing (NaBIC). IEEE, pp 210–214
37.
Zain AM, Haron H, Sharif S (2010) Application of GA to optimize cutting conditions for minimizing surface roughness in end milling machining process. Expert Syst Appl 37(6):4650–4659
38.
Zain AM, Haron H, Sharif S (2011) Optimization of process parameters in the abrasive waterjet machining using integrated SA–GA. Appl Soft Comput 11(8):5350–5359
Metadaten
Titel
Introduction to Advanced Manufacturing Processes and Optimization Methodologies
verfasst von
Apoorva Shastri
Aniket Nargundkar
Anand J. Kulkarni
Copyright-Jahr
2021
Verlag
Springer Singapore
Buch
Socio-Inspired Optimization Methods for Advanced Manufacturing Processes

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

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

Copyright-Jahr: 2021

DOI
https://doi.org/10.1007/978-981-15-7797-0_1

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