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

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

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.

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..

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.

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.

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.

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 ,

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

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.

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.

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)

THANK YOU