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DIE CASTING PROCESS OPTIMIZATION OF -MPI MANIFOLD USING TAGUCHI METHOD

DIE CASTING PROCESS OPTIMIZATION OF -MPI MANIFOLD USING TAGUCHI METHOD. NATARAJAN U 2008.11.22 IMMS LAB. Kyungpook National University. CONTENTS. Introduction Objectives of this work Die casting process of Al Alloy. Process optimization using Taguchi methods

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DIE CASTING PROCESS OPTIMIZATION OF -MPI MANIFOLD USING TAGUCHI METHOD

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  1. DIE CASTING PROCESS OPTIMIZATION OF -MPI MANIFOLD USING TAGUCHI METHOD NATARAJAN U 2008.11.22 IMMS LAB. Kyungpook National University

  2. CONTENTS • Introduction • Objectives of this work • Die casting process of Al Alloy. • Process optimization using Taguchi methods • ANOVA to interpret Taguchi experiments • Process Capability study • Results • Proposed work

  3. INTRODUCTION • TAGUCHI’S DOE is a statistical method for optimizing any process. • This work reports the basis of optimizing the DIE CASTING process. • The material used to form an automobile MANIFOLD is Aluminium alloy.

  4. OBJECTIVES OF THIS WORK • To satisfy the customer requirements. • To reduce the rejection rate. • To increase the productivity.

  5. GRAVITY DIE CASTING ( AL)

  6. Steps in TAGUCHI’S DOE • Selecting significant process parameters. • Selection of OA (Orthogonal Array) • Levels for process parameters. • Experimental analysis. • Results.

  7. QUALITY CHARACTERISTIC(OUTPUT) • Casting density is the quality characteristic ( output ) • Casting density relates to porosity, shrinkage, micro voids etc.

  8. CAUSE and EFFECT DIAGRAM

  9. SELECTED PROCESS PARAMETERS • Metal temperature in ˚c Range :720 to 760. • Die pre-heat temperature in ˚c Range : 200 to 215. • Setting time in sec Range : 95 to 115.

  10. LEVELS OF PROCESS PARAMETERS • Parameter A 1) 720 2) 740 3) 760. • Parameter B 1) 200 2) 207 3) 215. • Parameter C 1) 95 2)105 3)115.

  11. CONSTANT PARAMETERS • Job : Automobile Manifold • Material : Aluminium alloy • Composition : Al + Mg(0-0.5%) +Cu(2.0-4.0%) + Si(7.0-10.0%) +Mn(0-0.5%)

  12. INTERACTIONS • AXB • BXC • AXC

  13. DEGREES OF FREEDOM (DOF) For 3 parameters each at three levels:[ 2+2+2] For three interactions:[ 4 + 4 + 4] Required DOF=18 [2+2+2+4+4+4)] .

  14. ORTHOGONAL ARRAY SELECTION The number of DOF for OA should be greater than or equal to the number of DOF required Hence, L27 OA hasbeen selected

  15. L27 ORTHOGONAL ARRAY

  16. Contd….

  17. PHOTOGRAPHIC VIEW OF TEST PIECE

  18. A VIEW WORK-PIECE WITH CORE

  19. S/N RATIO • S/N ratio (db) = -10 log [ 1/n∑ ni=1 (1/Di2)] ( FOR HIGHER-THE-BETTER TYPE ) where Di is the response value for a trial condition repeated n times.

  20. CASTING DENSTIY VALUES AND S/N RATIO

  21. Average values of casting density at different levels

  22. Average values of S/N ratios at different levels

  23. AVERAGE VALUES OF CASTING DENSITY FOR A - FACTOR

  24. AVERAGE VALUES OF CASTING DENSITY FOR B - FACTOR

  25. AVERAGE VALUES OF CASTING DENSITY FOR C- FACTOR

  26. AVERAGE VALUES OF S/N RATIO FOR A - FACTOR

  27. AVERAGE VALUES OF S/N RATIO FOR B - FACTOR

  28. AVERAGE VALUES OF S/N RATIO FOR C - FACTOR

  29. Optimal points • Metal temperature : A3 • Die pre-heat temperature : B3 • Setting time : C1

  30. PREDICTED CAST DENSITY AT THE OPTIMAL CONDITION Predicted Optimum (U) = T’ + ( A3’ - T’ ) + (B3’ - T’ ) + (C1’ - T’ ) Where T’ is the Overall mean of all the observations in data and , A3’ , B3’, C1’ are the mean value of the observations due to the factors A3, B3 and C1 respectively Predicted cast density at the optimal condition = 2.646 g / cc

  31. ANOVA FOR CASTING DENSITY

  32. ANOVA FOR S/N RATIO

  33. ESTIMATION OF SUM OF SQUARES (SS) • SST = SSF + SSE • DFT = DFF + DFE where SST = Total sum of squares SSF = Sum of squares due to factors SSE = Sum of squares due to error DFT = Total degree of freedom DFF = Degree of freedom due to factors DFE = Degree of freedom due to error

  34. ESTIMATION OF SUM OF SQUARES (SS) • SST = (2.6352+ 2.6372 + 2.6402 + . . . ……+ 2.6512) - ( T )2/81 SST = 2.64428E-04 • SSA = [(A1-A2)2 + (A2-A3)2 + (A3-A1)2] / nr Where n is the no of experiments in OA and r is the no of replications SSA = 2.9417E-05 Similarly, sum of squares for all the factors are estimated.

  35. PROCESS CAPABILITY STUDY Confidence Interval (CI) = 0.04112 The 95% CI of the predicted optimum is, x-0.04112 < µ < x+0.04112 X=2.648g/cc Upper limit = 2.6522g/cc Lower limit = 2.6438g/cc

  36. Process Capability Study Test Results

  37. Process Capability index(Ppk) [(UCL-X’)/6S or (X’-LCL)/6S] Ppk =1.77

  38. RESULTS 1. Metal temperature (˚C) : 760. 2. Die pre-heat temperature (˚C) : 215. 3. Setting time (sec) : 95 4. Predicted optimum casting density : 2.646 g/cc 5. Process capability index (Ppk) :1.77

  39. PROPOSED WORK Multi-response optimization of parameters in Micro-EDM • INPUT PARAMETERS Peak current ( i) Ignition voltage (v) Pulse on time (ti) Pulse off time (to) • OUTPUT PARAMETERS Metal Removal Rate (MRR) Surface roughness (Ra)

  40. KEY REFERENCES • [1] J. Antony(2001), Process optimization using Taguchi methods of experimental design, Work study, MCB university press:vol.50(2),51-57 • [2] P.J. Ross, Taguchi techniques for Quality Engineering, McGraw-Hill, New York, 1988 • [3] M.S. Padke, Quality Engineering Using Robust Design, Prentice-Hall, Englewood Cliffs.NJ, 1989. • [4] G.S. Peace, Taguchi Methods: A hands-on approach, Addison-Wesley, New York, 1993. • [6] D.C. Montgomery, Design and analysis of experiments, 5th Edition, John Wiley and sons, 2001

  41. THANKS for your patience

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