example on taguchi
DESCRIPTION
Example on DOE with TaguchiTRANSCRIPT
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Preparation for Taguchi:
I. Selection of input parameters or independent variables
along with their levels:
Sl
No. Parameter (Unit) Symbol Level 1 Level 2 Level 3
1 Cutting Speed
(m/min) A 1 2 3
2 Feed rate (mm/rev) B 1 2 3
3 Depth of Cut (mm) C 0.2 0.25 0.3
4 Material (BHN) D Aliminium MS Iron
5 Cutting point angle
(Degree) E 85 90 95
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Contd..
II. Selection of output parameters or response variables:
Two response variables have been considered for study.
These are-
i) Avarage Surface Roughness (ASR) measured in m
and
ii) Material Removal Rate (MRR) measured in
mm3/min
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Contd..
III. Proposed Orthogonal Array:
Here in this study least array which will be considered is L27
and largest array which may be considered is L64.
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Exp No.
Parameters ASR
A B C D E Mean SD Log of
SD S/N
1 1 1 1 1 1
2 1 1 2 2 2
3 1 1 3 3 3
4 1 2 1 1 1
5 1 2 2 2 2
6 1 2 3 3 3
7 1 3 1 1 1
8 1 3 2 2 2
9 1 3 3 3 3
10 2 1 1 1 1
11 2 1 2 2 2
12 2 1 3 3 3
13 2 2 1 1 1
14 2 2 2 2 2
15 2 2 3 3 3
16 2 3 1 1 1
17 2 3 2 2 2
18 2 3 3 3 3
19 3 1 1 1 1
20 3 1 2 2 2
21 3 1 3 3 3
22 3 2 1 1 1
23 3 2 2 2 2
24 3 2 3 3 3
25 3 3 1 1 1
26 3 3 2 2 2
27 3 3 3 3 3
Contd..
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Work to be done:
I. Determination of target value through experiment
(Denoted by Yi) and their mean value (Y )
II. Then Squared Deviation and Log of SD will be
evaluated.
III. Then ratio of Signal and Noise will be determined by
calculating Mean Squared Deviation.
IV. Then ANOVA table will be prepared.
V. After this optimized combination of level will be
determined by Grey analysis.
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Few recent and relevant work:
A few publications are presented to Optimizing the process
parameter of boring machine. N.Z. Yussefian [14] shows the
production of cutting force for boring operation. Show
Shyan et al [13] use the Taguchi Method and Grey Relation
Analysis to Optimize the CNC Boring process. Rong tai
yang [4] use ANOVA to identify the significant factor and
the response surface counters were constructed for
determining the optimal condition of boring process
parameter.
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Contd
Harisimran singh sodhi [5] use taguchi method to optimize
the cutting parameter of boring. Thomas
Gmeiner and Kristina Sheas [20] work on Autonomous
Reconfiguration of a Flexible Fixture Device gives a
valuable and indeed guidance for designing a fixture for a
cutting tool which changes its direction during cutting.
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References:
1. Chorng-Jyh Tzeng et. al,Optimization of turning operations
with multiple performance characteristics using the Taguchi
method and grey relation analysis, 39, Journal of material
processing technology, 2753-2759.
2. Bharat Pater and Hiren Patel,Optimization of Machining
Parameter for surface roughness in milling operation, 2012,
Int. journal of applied Engineering Research, vol7, no 11,
3. Rong Tai Yang et.al., Modelling and Optimization in Precise
Boring Processes for Aluminium Alloy 6061T6 Components,
Jan 2012/11, Int. journal of precision Engineering and
manufacturing , vol 13, no 1 ,pp.11-16,
4. Harsimran Singh Sodhi et. al, Investigation of Cutting
Parameters For Surface Roughness of Mild Steel In Boring
Process Using Taguchi Method, 2012, Int. Jour. of applied
engineering ,Vol 7, No.11 ,
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Contd..
5. Yogendra Tyagi,Vedansh Chaturvedi ,Jyoti Vimal, Parametric
Optimization of Driling machining process using Taguchi and
Anova approach, July 2012, Int. Journal of Emerging
Technology and Advanced Engineering, vol 2, issue 7.
6. F. Atabey, I.Lazoglu, Y. Altintas, Mechanics of Boring
process- Part 1, 33, Int. J. Of Machine Tool &Manufacturing,
43, 463-476.
7. S. Balasubramanian &S .Ganapathy, Grey relational analysis
to determine optimum process parameters for Wire Electro
Discharge Machining (WEDM). Jan. 2011, International
Journal of Engg. Science and Technology,Vol 3, No. 1,
8. Meng Lu, Kees Wevers,Grey system theory and Application
: A Way forward, Oct. 28 36, 11 Chinese ,Hsinchu ,Taiwan
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Contd..
9. Edmundas Kazimieras Zavadskas, Arturas Kaklauskas, et.al.,
Multi-attribute decision-making model by applying grey
numbers, 39,informatics , vol 20,no 2, 305-320
10. C.C.Tsao, GreyTaguchi method to optimize the milling
parameters of aluminum alloy, 39, Int.J.Adv. Manufacturing
Technology , 40:40 41-48
11. Show Shyan Lin,Ming-Tsan Chuang,Jeong-Lian Wen,
Optimization of 6061T6 CNC Boring process using the
Taguchi Method and Grey Relation Analysis, 39, The Open
Industrial and Manufacturing Journal, 2, 14 20.
12. Mohamad Manuar, Joseph Ching- Chen and Nadeem
Ahmad Mufti, Investigation of Cutting Parameters Effect for
Minimization of Surface Roughness in Internal Turning, Feb
2011, International Journal of Precision Engineering and
manufacturing , Vol. 12, No. 1, pp 121-127.
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Contd..
13. N.Z. Yussefian , B. Moetakef-Imani , H. El-Mounayri,The
prediction of cutting force for boring process, 38,
International journal of Machine tool and manufacturing, 48 ,
1387-1394.
14. M. Kaymakci,Z.M.Kilic, Y.Altintas,Unified cutting force model
for turning ,boring and milling operation, 2012, International
journal of Machine tool and manufacturing, 54-55, 34-45.
15. Hakan Aydin, Ali Bayram, Ugur Esme, Yigit Kazancoglu, Onur
Guven, Application of grey relation analysis (GRA) and
Taguchi method for the parametric optimization of fiction stir
welding, 2010,Material and technology , 44 (4), 205-211.
16. Yigit Kazancoglu, Ugur Esme, Melih Bayramoglu, Onur
Guven, Multi-Objective Optimization Of The Cutting Forces
In Turning Operations Using The Grey-Based Taguchi
Method,Material and technology , 2011 , 45, 2 , 105- 110.
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Contd..
17. Show-Shyan Lin, Ming-Tsan Chuang, Jeong-Lian Wen, and
Yung-Kuang Yan, " Optimization of 6061T6 CNC Boring
Process Using the Taguchi Method and Grey Relational
Analysis", The Open Industrial and Manufacturing
Engineering Journal, 39, 2, 14-20
18. Utpal Roy and Jianmin Liao, Fixturing Analysis For Stability
Consideration in an Automated Fixture Design System, J.
Manuf. Sci. Eng. 124(1), 98-104 (Apr 01, 31) (7 pages)
19. Mervyn Fathianathan, A. Senthil Kumar and A. Y. C. Nee, An
Adaptive Machining Fixture Design System for Automatically
Dealing With Design Changes, J. Comput. Inf. Sci.
Eng. 7(3), 259-268 (Apr 02, 37) (10 pages)
20. Thomas Gmeiner and Kristina Shea, An Ontology for the
Autonomous Reconfiguration of a Flexible Fixture Device, J.
Comput. Inf. Sci. Eng. 13(2), 0213 (Apr 22, 2013) (11 pages)
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