ME

1
MEÐUNARODNO SAVJETOVANJE PTOIZVODNOG
STROJARSTVACIM-2005. LUMBARDA,
lipanj,2005.ABOUT APPLICATION AND OPTIMAL
SHOT-PEENING PARAMETER SELECTION ON THE MATERIALS
PROCESSING IN NEW FORMS VEHICLES PRODUCTION

• Prof. dr. sc. R.Markovina, University of Split,
  FESB, R. Boškovica bb, 21000 Split

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INTRODUCTION

• 1. The shot- peening process is one of very
  important technological process, which will be
  significantly used in the new generation and
  super high speed vehicles production in the
  following reasons
• increasing of materials fatigue life in
  exploitation,
• elimination of micro-corrosion and
  strength-corrosion,
• decontamination of elements after machining and
  assuring a good adhesion of paint film,
• peen-forming a small curved contours of thin
  plates etc.

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• 2. In the production of new generation
  vehicles, except materials used today also will
  be used
• Al-alloys 5454 (Al Mg 2,5Mn), 5083 (AlMg4,5Mn),
  6063(AlMgSi0,5), 6353 (AlMgSi1) 1 - Al-Li
  alloys (8090) 3.
• Their characteristics are corrosion resistance,
  good welding, small density (1,8-2,4 kg/dm3), and
  relatively good strength (200-350 N/mm2).
• But the others will be used too, as
• honey-comb structures (different shapes and
  profiles),
• non-metal materials ( composite materials,
  polyamides, acrylic glass, textolite, high
  loading capacity glues, modern packing materials,
  protection paints based on plastic and artificial
  fibers, etc.)

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• different types high tensile steels
• - no corrosive austenitic steels,
• - no corrosive martensitic steels,
• - law alloyed chromium-molybdenum steels,
• - law alloyed chromium-molybdenum-nickel
• steels, and
• - chromium-molybdenum-vanadium steels
• with the strength 700 2000 N/mm2).

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THE SHOT PEENING PROCESS APPLICATION IN THE
PRODUCTION OF NEW GENERATION VESSELS

• The controlled shot-peenning process is present
  at the Figure 1.

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Each of enumerable materials will have an
important application in modern shipbuilding,
partially those on the ships parts which will
be exposing on dynamical loading,
from which the most significant are

• - the main engine seating in engine room,
• seating of auxiliary engines and devices
• fore peak and after peak structure,
• - hatches and hatch covers with coamings (
  Fig.2),
• - seating of decks engines and cargo gears,
• - shaft brackets, shaft bossing, stabilizers,
• different types of springs and dampers,
• - important welded parts, etc

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• And also the mechanical components
• - with gears, axes, changeable sections,
• loading panels, integral plates, loading bars and
  girders, etc.
• According to experience and to the researches,
  their fatigue life could be
• increased from 25 up to 70, 3 depending on
  different parameters influences.

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Some of new form vehicles, which in the next time
would be produced in Croatian shipbuilding

MORSKI MINIBUS - sea bus (60 passangers)
TRILLENIUM 8000-sea car (4
passangers) with a speed of 25-28 knots, monohull
with a
speed of 22-25 knots, small trimaran,
GLIDING WING Spalato- fast speed car-ferry
Computer simulation of
BRACERA II - fast speed vehicles for 20
passengers, with a speed of 120 knots,
ekranoplan, with a speed of 60-80 knots, and
with WIG-effect 125 knots, catamaran or
trimaran,

FAROP, fast ship with the superstructure on
the stable amortizing field, with speed of 35-50
knots, monohull, catamaran or trimaran, Figure
5 Some of new generation vehicles projects when
the shot-peening process has to be used
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3. AN OPTIMAL SHOT-PEENING PARAMETERS SELECTION
BY SHORT PROCEDURE OF EXPERIMENT'S PLAN
From experience, it is evident that some of
parameters could be unchangeable, by which a good
production results were obtained, like -shots
mass, -metallurgical characteristics, -coverage
by shot jet, -nozzle diameter, -exposition
time, -shots flow quantity, and as changeable
parameters in experiments plan usually are -air
pressure (p), -nozzle distance from shot-peened
element (h), and -angle of nozzle positioning to
shot-peened element (a).
Table 1 Envisaged domain of parameters
selection 3
Parameter Domain of characteristic parameters values Domain of characteristic parameters values Domain of characteristic parameters values
Parameter minimal midium maximal
px1 1 bar 1,5 bars 2 bars
hx2 200 mm 300 mm 400 mm
?x3 45 60 75
Factors plan characteristics -1 0 1
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The process is with 3 influence factors, and
examined on the base of completely orthogonal
plan 2k23......................................
..................................................
.......................( 1 ) with a triple
experiment repeating in the all plan point, and
by the selected mathematical model form y b0
b1x1 b2x2 b3x3 b12 x1x2 b13x1x3
b23x2x3 b123x1x2x3..................( 2 ) In
Table 2 the correlation of selected parameters
and plan matrices is presented Table 2 The
correlation of parameters and plan matrices
Plan points (Number of samples) Plan matrices Plan matrices Plan matrices
Plan points (Number of samples) x0 x 1 x 2 x 3 x 1x 2 x 1x 3 x 2x 3 x 12x 3 x0 x 1 x 2 x 3 x 1x 2 x 1x 3 x 2x 3 x 12x 3 x0 x 1 x 2 x 3 x 1x 2 x 1x 3 x 2x 3 x 12x 3
1 2 3 4 5 6 7 8 1 -1 -1 -1 1 1 1 -1 1 1 -1 -1 -1 -1 1 1 1 -1 1 -1 -1 1 -1 1 1 1 1 -1 1 -1 -1 -1 1 -1 -1 1 1 -1 -1 1 1 1 -1 1 -1 1 -1 -1 1 -1 1 1 -1 -1 1 -1 1 1 1 1 1 1 1 1 1 -1 -1 -1 1 1 1 -1 1 1 -1 -1 -1 -1 1 1 1 -1 1 -1 -1 1 -1 1 1 1 1 -1 1 -1 -1 -1 1 -1 -1 1 1 -1 -1 1 1 1 -1 1 -1 1 -1 -1 1 -1 1 1 -1 -1 1 -1 1 1 1 1 1 1 1 1 1 -1 -1 -1 1 1 1 -1 1 1 -1 -1 -1 -1 1 1 1 -1 1 -1 -1 1 -1 1 1 1 1 -1 1 -1 -1 -1 1 -1 -1 1 1 -1 -1 1 1 1 -1 1 -1 1 -1 -1 1 -1 1 1 -1 -1 1 -1 1 1 1 1 1 1 1 1
p h a Base level 1,5 300 60 Interval of variation 0,5 100 15 Upper level 2,0 400 75 Lower level 1,0 200 45 p h a Base level 1,5 300 60 Interval of variation 0,5 100 15 Upper level 2,0 400 75 Lower level 1,0 200 45 xoi woi xgi xdi

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Based on that, the experiments parameters
selected 3, for the first series of examine and
for each of examined material Sample 1 p
1bar h 200mm a 45 min. no.
of samples 5 Sample 2 p 2bar h
200mm a 45 min. no. of samples
5 Sample 3 p 1bar h 400mm a
45 min. no. of samples 5 Sample 4 p
2bar h 400mm a 45 min. no.
of samples 5 Sample 5 p 1bar h
200mm a 75 min. no. of samples
5 Sample 6 p 2bar h 200mm a
75 min. no. of samples 5 Sample 7 p
1bar h 400mm a 75 min. no.
of samples 5 Sample 8 p 2bar h
400mm a 75 min. no. of samples
5 Codification of parameters is by equation of
transformation based on parameters presents on
tables 3 and 4 Table 3 The codification of
parameters
Factor Symbol Level Level
Factor Symbol Lower Higher
A B C p h a 1 200 45 2 400 75
Table 4 Combination of factors level with a
triple experiment
Factors level X1(A) Ai(A) X2(B) Bj(B) X3(C) Ck(C)
(1) A B AB C AC BC ABC - - - - 1 2 1 2 1 2 1 2 - - - - 200 200 400 400 200 200 400 400 - - - - 45 45 45 45 75 75 75 75
A total number of experiment samples is given by
equation NEu r x mn (23) x 23 40
..................................................
.......................( 3 ) where are r
number of repeating m number of levels
n number of factors,
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from which are NEs 2 x 23
16...........................for static
examining, NEd 3 x 23 24.....................
..... for dynamic examining. The transformation
of independents variables (X1, X 2 and X 3 ) at
non-dimensional is given by equation Xi
. ...............................................
..................................................
.( 4 ) where are Xi natural factor values
(X1, X 2, X 3 ) Xio values of i-th
factor at zero level Xi variation of i-th
factor interval
The parameters selection realized by random
selection method and optimal parameters for each
of examined material is selected by the first
sample highest dynamic operating life criteria,
which will be used as optimal in later
examining, because the samples have different
thickness and the first sample thickness is using
as roughly equivalent middle thickness of all
examined samples. The influence probability all
of process parameters, for thickness above and
below the first one will be the same. (That is
concerns a global thickness division like thin
plates from 1 to 4 mm middle thickness plates
from 4 to 7 mm, and thick plate over 7 mm of
thickness). Than the first series of static
examines starts in order to obtain the best
results of Rm Rp0,2 A5 and HB, as well as the
first series of dynamic examination, controlling
the shot-peening intensity (I), to elect the best
parameters results. Than follows a statistic
analysis of obtained results, by one of
statistic analysis software, to obtain variance
analyzed and regression analysis, and for each
factors level, in Table 4, associated
coefficient. By transformation of independent
variables, by equation (4), it is obtained
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X10
X 20
X 30
The parameters values are obtained by the
principal orthogonal plan examine relation
(5) bi
..................................................
..........................(5) for i 1,2,...N
where is N 2k 23 8. The transformation
equations look like X1
X2
...............................(6)
X3
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Using obtained middle values n from dynamic
examine results, f or all eight samples, and by
the combination of factors levels from Table 4,
the values of detached parameters can be
calculated
In given example only remained the coefficients
,
and
).
-
Y
(2p-3)
(2p-3)(0,01h-3)
(0,07
)..............(7)
Than it is useful to arrange the equation by
factors p, h,
, ph, p
, h
and ph
, with appropriate coefficients
- 9,415 h
Y-34732,8 54649,2 p 317,49 h 2824,48
-211,66 ph 1882,99 p
6,2766 ph
)
Based on results in Table 4, the appropriateness
of selected model for different combination of
parameters level calculates
(Example Y(1)50095,85 Y(A)34167,90
Y(B)43016,25 Y(AB)41245,70 Y(C)59510,15
Y(AC)24752,10 Y(BC)33600,15 and
Y(ABC)50659,10 ) 3.
.
For numerical degree of freedom
fEn(r-1)8(3-1)16.............................
..............................................(8)
and accepted level of significance
5.............................................
..................................................
.(9)
the tabular value, read by Students division,
is
tt1,75...........................................
..................................................
.....(10)
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Fig 6 Graphic presentation results of
different parameters changing ( h, a and p )
depending on dynamical sample endurance
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In the Figure 6 the diagrams present the results
of relations number of cycles n with changing
the nozzle distance from shoot-peened element h,
angle of nozzle positioning to shot-peened
element (a), and air pressure (p) on the
examined sample dynamic endurance.
For the evaluation of the correct model the
Fisher criteria can be useful, and the
dispersion is obtained as a square of difference
between measured and theoretic values of function
(y) F
..................................................
..........................................(11) W
here is Sad2
..................................................
.........................(12) Example
fadN-(K1)-n(r-1)24-(31)-8(3-1) 4 r 3
(number of reiteration)
S(y)2-(dispersion of residue obtained as middle
square residue deviation)78737000, and Sad2
168095593,2 Obtained values insert in Fisher
criteria equation (11) for obtain Fr Fr
2,1384 In the Table for Fisher criteria 5,
for fad4 f(E)16 and
5, can be read the Table
value Ft 3,01
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As the Frlt Ft (2,1384lt3,01), it can be concluded
that mathematical model is CORRECT and that is
APPLICABLE.
And finally, by retrograde method all optimal
process parameters can be obtained, by the same
calculation method.( In this case h 200mm
75 and p 0,6 bars ).

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4. CONCLUSION

• It can be concluded that
• shot peening process will play a significant
  role in modern shipbuilding tomorrow, especially
  in the production of fast ships and super-high
  speed vessels,
• the new materials, modern (aircraft)
  technologies and the great dynamic loading of
  construction parts would be expected.
• as the successful application of shot - peening
  process depends on a great number of different
  parameters, the short procedure of its selection
  by experimental plan, presented in this paper,
  can be very useful for new researcher and
  technologist in modern shipbuilding.

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