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Effect on fatigue performance of shot peened components: An analysis using DOE technique
International Journal of Fatigue 31 (2009) 693–702
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International Journal of Fatigue journal homepage: www.elsevier.com/locate/ijfatigue
Effect on fatigue performance of shot peened components: An analysis using DOE technique S.B. Mahagaonkar a,*, P.K. Brahmankar b, C.Y. Seemikeri a a b
Mechanical Department, Dr. BATU, Lonere (MS) 404 103, India R&D, Dr. BATU, Lonere (MS) 404 103, India
a r t i c l e
i n f o
Article history: Received 8 June 2007 Received in revised form 15 January 2008 Accepted 8 March 2008 Available online 24 March 2008 Keywords: Fatigue Surface hardness Shot peening parameters DOE ANOVA
a b s t r a c t Shot peening is widely used to improve the fatigue properties of components and structures. Residual stresses, surface roughness and work hardening are the main effects induced in the superficial layer from shot peening, which depend on the correct choice of the peening parameters. Compressive stresses are beneficial in increasing resistance to fatigue failures, corrosion fatigue, stress corrosion cracking, hydrogen assisted cracking, fretting, galling and erosion. In this paper design of experiment (DOE) technique was used in carrying out test, using an air blast type shot peening machine. This investigation examines the effect of process parameters such as pressure, shot size, nozzle distance and the exposure time on the fatigue performance of AISI 1045 and 316L material. After going through confirmation test the analysis reveals the right combination of the parameters for better process control. An ANOVA was carried out to identify significant peening parameters. Expressions correlating fatigue life and the process parameters for both materials were developed, which are useful in predicting fatigue life. This technique could prove beneficial in industries for reduction of performance variation and cost and to increase productivity. Ó 2008 Elsevier Ltd. All rights reserved.
1. Introduction Beneficial manufacturing processes include surface hardening as it induces residual compressive stress into the surface. Honing, polishing and burnishing are surface enhancing processes that remove defects and stress raisers from manufacturing operations. Surface rolling induces compressive stress but is primarily limited to cylindrical geometries. Shot peening has no geometry limitations and produces results that is usually the most economical. Shot peening, the state-of-the-art technology has potential application in the engineering field from earth to space technologies. Compared with the other advanced mechanical treatment technology like, laser shot peening (LSP) and low plasticity burnishing (LPB), which are more expensive and time consuming, shot peening process (SP) has got diversified application in the automobile, marine and aerospace vehicles in the race of high technology [1]. The surface modifications produced by the shot peening treatment are (a) roughening of the surface; (b) an increased, near-surface dislocation density (strain hardening); and (c) the development of a characteristic profile of residual stresses [2,3]. Shot peening (SP) is a cold-working process that hardens the surface of a metallic component by bombarding it with a stream * Corresponding author. Tel.: +91 23 52225807; fax: +91 23 52222435. E-mail addresses: [email protected] (S.B. Mahagaonkar), [email protected] (P.K. Brahmankar), [email protected] (C.Y. Seemikeri). 0142-1123/$ - see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijfatigue.2008.03.020
of small particles called shots. SP is viewed as a process involving multiple and progressively repeated impact. The indentation at each point of impact is the result of local plastic deformation. The mechanism of creation of compressive residual stress is the result of the superposition of the residual stress produced by the surrounding shots [4,5]. As the deformed regions tend to expand, they are restrained by adjacent, deeper metal that was not plastically deformed by the shot impact. Since the plastically deformed surface layer seeks to occupy more space it is compressively strained. This compressively stressed layer is extremely effective in preventing premature failure under conditions of cyclic loading since the fatigue failure generally propagates from the free surface of a target and starts in a zone that is subjected to tensile stresses. This phenomenon was fully explained by several researchers [6–8]. Low surface roughness increases fatigue strength as a result of higher dislocation densities near the surface due to the increase in surface hardness [9]. An increase in microhardness and surface roughness increases with increase in shot size and the peening intensity [10–12]. Fatigue properties depends on various factors such as work hardening due to the cold work, compressive residual stress, surface topography and various other local fatigue properties. Residual stresses, surface roughness and work hardening can be identified as the main effects induced in the surface layers of the material, which depend on the correct choice of the peening parameters. So far several authors have used one-factor-at-a-time approach in analyzing fatigue life behavior with the different
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peening parameters such as peening intensity [10], types of shot [13], shot size [14], shot velocity [15] and the impact angle [16]. Few authors were used design of experiment (DOE) technique with specialized single balled controlled shot peening machine [17] and some investigations have been made into the design for robust fatigue performance with the aid of simulation technique [18]. Most of the studies are made on precision-machined steels with high strength to weight ratio; such steels are typically used for various components in aircraft, turbine, and defense equipment. It is noted that hardly any shot peening studies have been made for fatigue performance of conventional materials using full factorial experiments. It is therefore, necessary to carry out comprehensive investigations, using 2k full factorial DOE to evaluate the interaction effect of process parameters such as pressure, shot size, exposure time and the nozzle distance on the fatigue life of AISI 1045 and 316L material. Mathematical models from the test results were predicted, which is useful for the quantification of fatigue life. 2. Experimental analysis Experiments were carried out to investigate the effect of SP parameters on fatigue performance of the work material. The selection of work material, SP parameters and design of experiments are given below. 2.1. Selection of material The shot peening process is one of the frontier surface enhancement technology, it aids in assuring satisfactory fatigue life and reliability of in the automotive components. The AISI 1045 material serves this purpose since its cost is less in comparison with other high strength materials. The materials selected for present investigations are AISI 316L and 1045. The grade 316L is the low carbon version of 316 and is usually regarded as ‘‘marine grade steel”. It is extensively used in the marine applications, where the parts are havocked of corrosive environment. It is also used in biomaterial applications. These materials were selected since they are widely used in marine and automobile applications. AISI 1045 steel consist of 70% pearlite and 30% ferrite with an average grain size of 25 lm (Fig. 1). The type AISI 316L materials have a fine austenite grain size with precipitate-free grain boundaries. The grain size is in the range of 30–50 lm (Fig. 2). Shot peen-
Fig. 1. AISI 1045 core material microstructure.
Fig. 2. AISI 316L core material microstructure.
ing on these materials increases dislocation density near the surface, which in turn reduces grain size. Figs. 3 and 4 show the near surface microstructure for shot peened AISI 1045 and 316L material, respectively. Since AISI 1045 is more ductile, the plastic deformation on this material will be more. Because of the effect of more cold work, it has got finer grain size as compared with 316L material. AISI 316L steel does not harden in response to heat treatments, but it can be hardened by cold working. Cold working is capable of transforming metastable austenite into martensite, the strain energy being supplied by the plastic deformation. However, it is observed that additional nickel and molybdenum in this steel impart greater austenitic stability, so that extensive plastic deformation at room temperature leaves the austenite untransformed [19,20]. If austenitic steel is transformed to a two-phase martensite and austenite structure, most of its physical, chemical and mechanical properties get affected. In that case, the ultimate tensile strength and hardness increase whereas ductility and toughness decrease [20,21]. Fatigue performance also gets affected. Shot peening on such materials increase dislocation density on the
Fig. 3. AISI 1045 near surface microstructure.
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ated, in most cases, after peening is complete. The variables that can be controlled and adjusted to obtain the desired values of intensity, saturation and coverage are air pressure, shot mass flow rate, nozzle type, feed rate of the nozzle along workpiece, distance of the nozzle from workpiece and the workpiece table speed. Since some parameters such as velocity, intensity and the coverage are difficult to control, controllable influential parameters such as pressure, shot size, nozzle distance and exposure factors were considered in the present investigation. Among the SP media, heat treated steel shots are more advantageous than the other types. Steel shot is more expensive initially than chilled iron; however, the brittle nature of chilled iron causes it to break up very rapidly and, in fact, it has but one fourth to one sixth the life of steel shot. Steel shot is therefore much cheaper in the long run; it is cleaner to handle and causes much less wear on cabinet walls, wheels, nozzles and fixtures [22]. Cut wire shots are another media used for peening; however specifications for peening steel parts requires round steel shots. Hence, for the present investigation heat-treated steel shots S-390 and S-660 having shot diameters 1.85 mm and 1 mm respectively were selected. The selection is based on ‘‘MIL-S-13165B” specifications and the surface conditions of the specimen. According to the test certificates from the manufacturer, the shots were tested and sieve analysis was done as per IS 4606 of 1983 (Table 2).
Fig. 4. AISI 316L near surface microstructure.
surface, which in turn gives rise to compressive residual stresses. This in turn results in enhancement of fatigue life of the component [21]. Experimental works were conducted on turned specimens made of medium carbon steel AISI 1045 and 316L material (Fig. 5a). The initial surface hardness for the AISI 1045 and 316L specimens in terms of Vickers hardness were 187Hv and 287Hv, respectively. Initial surface roughness (Ra) for both the materials lies between 4 and 5 lm. The chemical composition for the material is as shown in Table 1. 2.2. Selection criteria for the shot peening parameters Shot peening process relies on multiple impacts of spherical media onto a surface to achieve better surface hardness and fatigue life. The various shot peening parameters are shot type and size, intensity, saturation, incidence angle, velocity and coverage. Among these parameters, only shot type and incidence angle are controlled directly. Remaining parameters are measured or evalu-
Fig. 5a. Fatigue test specimen.
2.3. Design of experiment Screening experiments were conducted so as to identify the suitable process parameters and their levels [23,24]. These experiments revealed that magnitude of pressure greater than 4 kg/cm2 caused about fourfold reduction in fatigue life compared to the unpeened component. A similar trend was observed when excessive exposure time and larger shot size were used. On the other hand, pressure less than 2 kg/cm2 was found to result in clogging of shots due to low suction of pressurized air, which, in turn, induced lesser cold work and coverage. These findings were used as the basis for selection of process parameters and their levels as shown in Table 3. The following factors were held constant: jet obliquity equal to 90° and symphonic nozzle orifice diameter of 9 mm. The design of experiment was based on full factorial design considering four factors each at two levels. In order to reduce process and product variability the 16 runs of the experiment were replicated twice. The design matrix considering two replicates is shown in Table 4. The fatigue life of the peened and unpeened, components was tested by R.R. Moore rotating-beam fatigue machine (Fig. 5b), at a constant speed of 4340 rpm and a load of 19.62 N m (200 kg cm). In order to find the fatigue life of the components, average of the two closest values of the fatigue life of the components was considered. Fatigue life of the shot peened components was calculated in terms percentage of fatigue life. Percentage of fatigue life indicates the number of times of the peened component over the unpeened
Table 1 Chemical composition of AISI 1045 and 316L material Table 2 Chemical composition of shots
Composition
Material type AISI 1045
AISI 316L
Carbon (C) Silicon (Si) Manganese (Mn) Sulphur (S) Phosphorus (P) Chromium (Cr) Molybdenum (Mo) Nickel (Ni) Ferrous (Fe)
0.43 0.26 0.78 0.033 0.028 – – – Bal.
0.03 0.75 2.0 0.03 0.045 17.0 2.9 14.0 Bal.
Composition
Carbon (C) Silicon (Si) Manganese (Mn) Sulphur (S) Phosphorus (P) Density (kg/m3) Hardness (Hv)
Shot type S-390
S-660
0.94 0.75 0.81 0.042 0.047 7350 450
0.91 0.7 0.77 0.044 0.047 7320 450
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Table 3 Factor levels for the experiment
Table 5 Estimates of main and interaction factors
Factors 2
P: Pressure (kg/cm ) S: Shot type and shot size (mm) T: Exposure time (s) D: Nozzle distance (mm)
Lower level 1
Higher level 2
2 S-390, 1 mm 80 80
4 S-660, 1.85 mm 160 100
Table 4 Full factorial design matrix Experiment no.
P
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2
S
1 1 1 1 2 2 2 2 1 1 1 1 2 2 2 2
D
1 1 2 2 1 1 2 2 1 1 2 2 1 1 2 2
T
1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2
Main factors
Effects Fatigue life for AISI 1045 material
Fatigue life for 316L material
P S D T
9.959 10.130 37.912 23.764
0.602 23.673 13.533 10.998
Two-way interaction factors
Two-way interaction effects Estimates for AISI 1045 material
Estimates for 316L material
P–S P–D P–T S–D S–T D–T
9.530 31.559 71.944 31.004 38.530 44.746
43.290 46.303 31.098 63.791 73.746 27.561
Three-way interactions
Three-way interaction effects
Average response of replications (Y) Fatigue life in % (AISI 1045)
Fatigue life in % (316L)
249.588 401.236 418.269 442.72 264.973 392.308 417.857 307.143 361.813 421.016 388.187 211.951 432.967 178.709 415.659 404.121
462.254 398.245 214.912 424.844 344.332 388.644 412.105 302.271 344.148 472.354 375.542 352.408 428.458 165.714 412.256 401.546
Estimates for AISI 1045 material PSD PST PDT SDT
66.655 1.339 46.566 45.913
Four-way interactions
13.255 20.885 2.388 3.089
Four-way interaction effects Estimates for AISI 1045 material
PSDT Responses
Estimates for 316L material
73.626 AISI 1045 material
Maximum and minimum responses (Y) 356.782 Yaverage 387.534 Ymaximum 326.030 Yminimum
Estimates for 316L material 103.933 316L material 368.752 382.157 355.347
3. Statistical analysis
Fig. 5b. Fatigue testing equipment.
The estimated values of the main and interaction effects are given in Table 5. These values were then plotted in decreasing order of importance in the form of Pareto charts (Figs. 6 and 7) which help in testing the statistical significance of the above effects. Graphical displays such as Pareto chart and normal probability plots (Figs. 8 and 9), respectively, were be used to verify the significance of the factors and interactions. The Pareto chart show each of the estimated effects in decreasing order of magnitude. The length of each bar is proportional to the standardized effect divided
component. If Np is the fatigue life for peened component in cycles and Nu is the fatigue life for unpeened component, then percentage for fatigue life is given by FL ¼ ðN p =N u Þ100 As per the guidelines given by Champaine [23], the exposure time to achieve desired peening coverage for the material were determined by 10-magnifying lenses. Almen strips were not used since Almen strip saturation time can be misleading due to the surface hardness difference between the Almen strip and the peening material [25,26]. The averages of replications of the percentage of fatigue life values for each trial are tabulated as shown in Table 4. Table 5 shows the estimated effects for main factors and their interaction effects. These values were calculated based on the method as given by Lochner and Matar [27].
Fig. 6. Pareto chart for AISI 1045 material.
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grees of freedom) are compared with the theoretical extreme values for the F distribution [27,28]. In ANOVA, the meaning of 5% significance level means one in twenty and 1% means one in hundred. This indicates that the parameters falling in 1% significance level is most dominant factor and 5% significance level is the next dominant factor. The factors that are not falling either 1% or 5% are not significant factors. 4.1. ANOVA for fatigue life on AISI 1045 material
Fig. 7. Pareto chart for 316L material.
From ANOVA (Table 6), it can be seen that the most dominating factor among the main factors is the nozzle distance (D), since it has got higher value of F statistics. The next dominating parameter is the exposure time (T) and the least effecting factors are shot size (S) and pressure (P). Among the two-way interactions, the interaction between pressure and the exposure time (P–T) is morea significant and the next interaction effect in the decreasing order are D– T, S–T, P–D, S–D and P–S. 4.2. ANOVA for fatigue life of 316L material From the ANOVA results for 316L (Table 7), it can be seen that the most dominating factors among the main factors is the shot size and the effect of pressure is very negligent as its p-value is Table 6 Analysis of variance for fatigue life for AISI 1045
Fig. 8. Normal probability plot for AISI 1045 material.
Source
DF
Seq SS
Adj SS
Adj MS
F
p-Value
P S D T PS PD PT SD ST DT PSD PST PDT SDT PSDT
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
793 821 11,499 4518 3961 7968 41,407 7710 11,877 16,017 35,543 14 17,347 16,864 43,367
793 821 11,499 4518 3961 7968 41,407 7710 11,877 16,017 35,543 14 17,347 16,864 43,367
793 821 11,499 4518 3961 7968 41,407 7710 11,877 16,017 35,543 14 17,347 16,864 43,367
173.93 179.98 2520.69 990.35 868.41 1746.65 9077.11 1690.08 2603.54 3511.27 7791.66 3.15 3802.75 3696.93 9506.70
0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.095 0.000 0.000 0.000
Error Total
16 31
73 219,779
73
5
S = 2.13581; R2 = 99.97%; R2 (adj) = 99.94%.
Table 7 Analysis of variance for fatigue life for 316L
Fig. 9. Normal probability plot for 316L material.
by its standard error. The bars which are extending beyond 5%, indicates statistically significant at the 95% confidence level. 4. ANOVA for fatigue performance Analysis of variance (ANOVA) is used to judge whether or not the experimentally found significant factors are statistically significant. In the present investigation, MINITAB (statistical software) was used to analyze the significance of factors. The significance can also be judged by calculating F- or p-values. Furthermore, the calculated F-values (product of the square of the effect and the de-
Source
DF
Seq SS
Adj SS
Adj MS
F
p-Value
P S D T PS PD PT SD ST DT PSD PST PDT SDT PSDT
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
3 4483 1465 968 873 17,151 7737 32,554 43,508 6077 1406 3490 46 76 86,416
3 4483 1465 968 873 17,151 7737 32,554 43,508 6077 1406 3490 46 76 86,416
3 4483 1465 968 873 17,151 7737 32,554 43,508 6077 1406 3490 46 76 86,416
0.58 893.57 292.03 192.86 174.02 3418.58 1542.04 6488.56 8671.93 1211.23 280.15 695.52 9.09 15.22 17224.17
0.458 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.008 0.001 0.000
Error Total
16 31
80 206,332
80
5
S = 2.23990; R2 = 99.96%; R2 (adj) = 99.92%.
S.B. Mahagaonkar et al. / International Journal of Fatigue 31 (2009) 693–702
tion effect of T–D, S–P, D–S, D–P, T–P and T–S, were plotted separately as shown in Figs. 12–17. These plots were plotted based on the data from Table 4 considering the average value of each factor at their higher and lower levels. The maximum and minimum response values for the fatigue life for both the materials were calculated by adding the individual contribution of the main factors to the grand mean (Table 5).
Lower level-1 400.000 T
360.000
PST PST
PS PD PS
T
PT
PS
S
D
320.000
D 7%
T 4%
PS 2%
SDT 8%
PD 6%
PDT
PSD
PSDT
Fig. 11a. Graphical display of effect on AISI 1045.
440.000 PSDT
420.000
Fatigue Life in %
P S 2% 2%
SDT
ST
Main with interaction factors
SD
PSDT 14%
DT
SD
T
PT
D
ST
S
SD
P
PD
340.000
300.000
SDT
DT
PD
SDT
S
PSDT
P
PDT
PST
380.000
PSDT
PSD
PT ST SD
D
P
% of Fatigue life
Figs. 10a and 10b shows the contribution of main and other interaction factors. The graphical representation in Figs. 11a and 11b give the estimates for all the factors at their lower and higher levels. Figs. 10a and 10b show the effects of four main factors (P – pressure, S–shot size, T–exposure time and D–nozzle distance), as well as their two-, three-, and four-way interactions on the fatigue performance. In both the cases the contribution of pressure has the least significant effect on the fatigue life; however contribution of shot size and nozzle distance is more significant in case of 316L material when compared to the AISI 1045 material. The effect of nozzle distance is more predominant in case of AISI 1045 material. The interaction effect between P and S on the fatigue life is negligible in case of AISI 1045 material, but in case of 316L it is almost five times more than that of AISI 1045 material. The most dominating two-way interaction effect for AISI 1045 is P–T, but in case of 316L is S–T. For the purpose of analyzing the effects of main factors and interaction effects on the surface hardness, the two-way interac-
Higher level-2
PDT
5. Results and discussion
PSD
greater than 0.05. Among the two-way interactions, the interaction between shot size and the exposure time (S–T) is the most significant. The next interaction effects in the decreasing order are S–D, P–D, P–T and D–T. The results from the ANOVA, predicts that all the main and interaction factors are statistically significant, since the p-values for these parameters are less than 0.05 and these values proves equally the same results, with the analysis brought out by Pareto chart and normal probability chart.
DT
698
PD
400.000
PT
S D
380.000 P
T
DT PSD
PS
PST PDT
P
360.000
S
D
T
DT
PT
340.000
PSD
PST
SDT SDT
PDT
PD SD
PS
320.000
PDT 9%
ST
ST PSDT
P ST
S DT
D PSD
SD 6%
ST 7%
DT 8%
T PST
PS PDT
PD SDT
Main with Interaction Factors Lower level-1
PT PS
SD
S 5%
D T 3% 2%
0% PST 4%
500.000
PS 9%
PD 10%
Fatigue life in %
SDT PDT 1%
P 0%
Higher level-2
Fig. 11b. Graphical display of effect on 316L.
Fig. 10a. Effects on fatigue life on AISI 1045.
PSDT 22%
T PS PD
PT 13%
PT SD ST D T PS D PS T PD T SD PS T D T
PSD 12%
P S D
300.000 PST 0%
400.000 300.000
Nozzle Distance 1 Nozzle Distance 2
200.000 2
1
Exposure Time
PSD 3%
PT 7%
DT 6%
SD 13%
ST 15%
P PD PSD
S PT PST
D SD PDT
T ST SDT
PS DT PSDT
Fig. 10b. Effects on fatigue life on 316L.
Nozzle Distance 1
327.335
348.317
Nozzle Distance 2
409.993
341.484
Fig. 12a. Interaction effect between T and D for AISI 1045.
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450.00
394.80
400.00
370.27
350.00
356.24
353.70
300.00
Fatigue Life in%
Fatigue Life in %
450.00
250.00 200.00
1
419.25
350.00
341.93 331.79
300.00 250.00 200.00
2
1
2
Exposure Time 394.80
Nozzle Distance 1 Nozzle Distance 2
Nozzle Distance : D
356.24
353.70
382.04
400.00
370.27
Shot Size 1
419.25
341.93
Shot Size 2
331.79
382.04
Shot Size 1
Nozzle Distance 1
Shot Size 2
Nozzle Distance 2 Fig. 14b. Interaction effect between D and S for 316L.
450.000
400.000 380.000 Pressure 1
360.000
Pressure 2
340.000 320.000
1
2
400.000
Fatigue life in%
Fatigue Life in %
Fig. 12b. Interaction effect between T and D for 316L.
Pressure 1 Pressure 2
350.000 300.000 250.000 200.000
S : Shot Size Pressure 1
377.953
345.570
Pressure 2
345.742
357.864
1
2 Nozzle Distance:D
Pressure 1
327.026
396.497
Pressure 2
348.626
354.980
Fig. 13a. Interaction effect between S and P for AISI 1045. Fig. 15a. Interaction effect between D and P for AISI 1045.
390.00 386.11 370.00
375.06
450.00
361.84
360.00 350.00
Fatigue Life in%
Fatigue Life in %
380.00
351.99
340.00 330.00
1
2
400.00
398.37
385.44
352.67
338.53
350.00 300.00 250.00 200.00 1
2
S : Shot Size 375.06
361.84
Pressure 1
398.37
338.53
Pressure 2
386.11
351.99
Pressure 2
352.67
385.44
Pressure 1
Pressure 1
Pressure 2
Pressure 2
Fig. 13b. Interaction effect between S and P for 316L.
Fig. 15b. Interaction effect between D and P for 316L.
400.000
500.000
Shot Size 1
300.000 200.000
Shot Size 2 1
2
Fatigue life in%
Fatigue life in%
Nozzle Distance:D
Pressure 1
400.000
Pressure 1
300.000
Pressure 2
200.000
Nozzle Distance : D
1
2 Exposure Time
Shot Size 1
358.413
365.282
Pressure 1
337.672
385.852
Shot Size 2
317.239
386.195
Pressure 2
399.657
303.949
Fig. 14a. Interaction effect between D and S for AISI 1045.
Fig. 16a. Interaction effect between T and P for AISI 1045.
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369.231
Confirmation tests were carried out by setting parameters D at higher level and all other factors at their lower levels and maximum fatigue life was found to be in the range of 387.534–442.72. In analyzing the interaction effect on fatigue life, from Fig. 14a, it was found that for lower nozzle distance fatigue life increased with a decrease in shot size. However, it decreased with an increase in the nozzle distance. The two line segments are not parallel; which indicates presence of strong interaction effect between shot size and nozzle distance. From Fig. 12a, it was observed that keeping the exposure time constant, the fatigue life increased with an increase in the nozzle distance. For lower level of pressure, fatigue life increased with an increase in the pressure. However, by doubling the exposure time, it was found to decrease (Fig. 16a). The line segments in Figs. 12a–17a are not parallel, which indicates the presence of strong interaction effect between T–D, S–P, D–S, D–P, T–P and T–S. However, it is interesting to note that with the use of smaller shot size, the fatigue life increased with a decrease in pressure. But with the larger size shot, it increased with an increase in pressure (Fig. 13a). Again for the lower nozzle distance, fatigue life increased with a decrease in pressure; but at larger distance it increased with an increase in pressure (Fig. 15a).
354.464
5.2. Effect of fatigue life on 316L material
Fatigue Life in%
400.00
390.10
380.00
378.50
360.00 358.40
340.00 320.00
348.01 1
2 Exposure Time
Pressure 1
358.40
378.50
Pressure 2
390.10
348.01
Pressure 1
Pressure 2
Fig. 16b. Interaction effect between T and P for 316L.
Exposure Time 1
Exposure Time 2
400.000 382.864
Fatigue Life in%
380.000 360.000 340.000
320.570
320.000 300.000
Exposure Time 1 Exposure Time 2
1
2
354.464
382.864
369.231
320.570
Fig. 17a. Interaction effect between T and S for AISI 1045.
Shot Size 1
Shot Size 2
Fatigue Life in%
450.00 399.29
400.00 350.00
411.96
349.21
314.54
300.00 250.00
1
2 Exposure Time
Shot Size 1
349.21
411.96
Shot Size 2
399.29
314.54
Fig. 17b. Interaction effect between T and S for 316L.
5.1. Effect of fatigue life on AISI 1045 material The maximum value of fatigue life from Table 4 is 442.72, which occurred when pressure (P) and shot size (S) at lower level with the other parameters nozzle distance (D) and exposure time (T) at higher levels. Considering Fig. 11a, factors P and S can be set to their lower levels, since the same conclusion can be drawn after considering the two-way interaction effects of these factors P–D, P–T, P–S, S–D and S–T. Similarly, factor D can be set to the higher level, but the factor T should be set to its lower level, since the interaction effects P–T and D–T are more significant.
The maximum value of fatigue life from Table 4 is 472.354, which occurred when pressure (P) and exposure time (T) were at higher levels and shot size (S) and nozzle distance (D) were at lower levels. From Fig. 11b, the sole effect of pressure alone is negligible; one has to consider the two-way interaction effects between P–D, P–S and P–T in setting the level for pressure. Since the interaction effect between P and D is more dominant than other, it is suggested that pressure be set at higher level. Similarly the nozzle distance can be set to its higher value. Considering the main effects of the shot size and exposure time, and also interaction effect between S and T, they could be set to their lower level in order to maximize the fatigue performance. Confirmation tests were carried out by setting parameters P and D at higher levels and other two factors at their lower levels. The maximum fatigue life was found to be in the range of 382.157–472.354. From Fig. 14b, it was found that for lower nozzle distance, fatigue life increased with a decrease in shot size; however it decreased with an increase in the nozzle distance. The two line segments are not parallel; which indicates the presence of strong interaction effect between shot size and nozzle distance. From Figs. 12a and 12b, it was observed that keeping the exposure time constant, the fatigue life increased with an increase in nozzle distance. For lower level of pressure, fatigue life increased with in increase in the pressure. However, by doubling the exposure time it was found to decrease (Fig. 16b). In the case of 316L material, all two-way interactions indicate the presence of strong interaction effects (Figs. 12b–17b). Fatigue life increased with an increase in the shot size. But with smaller shot size, it increased with an increase in the pressure (Fig. 13b). This is an opposite effect compared to that of AISI 1045 material. 6. Regression analysis for the fatigue life Correlations for the fatigue life of both the materials were obtained by developing regression models using Analyze-it software. For this analysis, a log transformed response variable and process parameters were assumed and are tabulated as shown in Tables 8 and 9. For better curve fitting, following model was assumed: lnðYÞ ¼ b0 þ b1 lnðPÞ þ b2 lnðSÞ þ b3 lnðDÞ þ b4 lnðTÞ
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S.B. Mahagaonkar et al. / International Journal of Fatigue 31 (2009) 693–702 Table 8 Log transformed design matrix
Table 11 Coefficients and intercepts for AISI 316L material
Trial no.
P
ln(P)
S
ln(S)
D
ln(D)
T
ln(T)
Term
Coefficient
SE
p
95% CI of coefficient
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4
0.6931 0.6931 0.6931 0.6931 0.6931 0.6931 0.6931 0.6931 1.3862 1.3862 1.3862 1.3862 1.3862 1.3862 1.3862 1.3862
1 1 1 1 1.85 1.85 1.85 1.85 1 1 1 1 1.85 1.85 1.85 1.85
0 0 0 0 0.6151 0.6151 0.6151 0.6151 0 0 0 0 0.6151 0.6151 0.6151 0.6151
80 80 100 100 80 80 100 100 80 80 100 100 80 80 100 100
4.3820 4.3820 4.6051 4.6051 4.3820 4.3820 4.6051 4.6051 4.3820 4.3820 4.6051 4.6051 4.3820 4.3820 4.6051 4.6051
80 160 80 160 80 160 80 160 80 160 80 160 80 160 80 160
4.3820 5.0751 4.3820 5.0751 4.3820 5.0751 4.3820 5.0751 4.3820 5.0751 4.3820 5.0751 4.3820 5.0751 4.3820 5.0751
Intercept ln(P) ln(S) ln(D) ln(T)
6.5924 0.0185 0.1245 0.0740 0.0685
3.4153 0.2310 0.2603 0.7177 0.2310
0.0798 0.9376 0.6418 0.9198 0.7725
0.9246 0.5270 0.6975 1.6535 0.5770
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
6.2. Quantification of fatigue life for 316L material Similarly, the analysis from the results of Table 11 yields the following correlation between fatigue life (FL) and the peening parameters: lnðFLÞ ¼ 6:5924 0:0185 lnðPÞ 0:1245 lnðSÞ 0:074 lnðDÞ 0:0685 lnðTÞ
Fatigue life in percentage for 316L
AISI 1045 material
316L material
FL
ln(FL)
FL
ln(FL)
249.588 401.236 418.269 442.72 264.973 392.308 417.857 307.143 361.813 421.016 388.187 211.951 432.967 178.709 415.659 404.121
5.519812 5.99455 6.036125 6.092938 5.579628 5.972047 6.035139 5.727313 5.891128 6.042671 5.961487 5.356355 6.070662 5.185759 6.029865 6.001714
462.254 398.245 214.912 424.844 344.332 388.644 412.105 302.271 344.148 472.354 375.542 352.408 428.458 165.714 412.256 401.546
6.136115 5.987067 5.370229 6.051722 5.841606 5.962664 6.021278 5.711324 5.841072 6.157729 5.92837 5.86479 6.060193 5.110263 6.021645 5.995322
Table 10 Coefficients and intercepts for AISI 1045 material Term
Coefficient
SE
p
95% CI of coefficient
Intercept ln(P) ln(S) ln(D) ln(T)
4.1016 0.0754 0.0595 0.5516 0.1353
3.3541 0.2269 0.2557 0.7048 0.2269
0.2469 0.7460 0.8202 0.4504 0.5629
3.2808 0.5748 0.6222 0.9997 0.6347
to to to to to
11.4839 0.4240 0.5032 2.1029 0.3641
where b1, b2, b3 and b4 are the regression coefficients to be determined and Y is the fatigue life. 6.1. Quantification of fatigue life for AISI 1045 material The analysis that results from Table 10 yield the following correlation between the fatigue life and the peening parameters: lnðFLÞ ¼ 4:1016 0:0754 lnðPÞ 0:0595 lnðSÞ þ 0:5516 lnðDÞ 0:1353 lnðTÞ The above equation in an exponential form can be expressed as follows: Fatigue life in percentage for AISI 1045 ðFL1 Þ ¼ 60:44ðPÞ0:075 ðSÞ0:059 ðDÞ0:551 ðTÞ0:13
14.1095 0.4900 0.4484 1.5056 0.4401
The above equation in an exponential form can be expressed as follows:
Table 9 Log transformed response table for both materials Trial no.
to to to to to
ð1Þ
ðFL2 Þ ¼ 729:53ðPÞ0:018 ðSÞ0:124 ðDÞ0:074 ðTÞ0:069
ð2Þ
The resulting regression equations (1) and (2) yield approximate values for both the materials. However, they would serve as a useful guide for selecting proper values of process parameters for the above materials so as to obtain desired fatigue life of the component. 7. Concluding remarks To summarise, this study has, thus, brought out the effect of SP parameters on the fatigue performance of AISI 1045 and 316L material. It is interesting to note that with the use of larger shot size in case of 316L material, the fatigue life increases with a decrease in pressure, but with smaller shot size it increases with an increase in pressure. This is opposite to that of AISI 1045 material. This behaviour can be attributed to the deviation in the deformation characteristics of the peening materials. Effect of shot peening parameters, viz. pressure (P), shot size (S), exposure time (T) and nozzle distance (D) and their interactions on fatigue performance was studied using ANOVA. It was found that the process parameters that have influence on fatigue performance of AISI 1045 in decreasing order of significance are nozzle distance, exposure time, shot size and pressure. For 316L material, the order is shot size, nozzle distance, exposure time and pressure. Regression models correlating fatigue performance with process parameters have also been obtained. These equations would serve as a useful guide for setting proper values of process parameters so as to obtain desired fatigue life of the component. References [1] Brahmankar PK, Mahagaonkar SB, Seemikeri CY. Shot peening: state-of-theart. In: Proceedings of the international conference on advances in materials and material processing. 2006. p. 296–303. [2] Curtisa S, De los Rios ER, Rodopoulos CA, Levers A. Analysis of the effects of controlled shot peening on fatigue damage of high strength aluminium alloys. Int J Fatigue 2003;25:59–66. [3] O’Hara P. Super finishing and shot peening of surfaces to optimize roughness and stress. In: Brebbia CA, Kenny JM, editors. Surface treatment IV. Wessex: WIT Press; 1999. p. 321–30. [4] Kobayashi M, Matsui T, Murakami Y. Mechanism of creation of compressive residual stress by shot peening. Int J Fatigue 1998;20(5):351–7. [5] Al-Obaid YF. Shot peening mechanics: experimental and theoretical analysis. Mech Mater 1995;19:251–60. [6] Martin U, Altenberger I, Scholtes B, Kremmer K, Oettel H. Cyclic deformation and near surface microstructures of normalized shot peened steel SAE 1045. Mater Sci Eng A 1998;246:69–80.
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[7] Wagner L, Liitjering G. Influence of shot peening on the fatigue behavior of Tialloys. In: Shot peening. Oxford: Pergamon Press; 1981. p. 453–60. [8] Chou HC. The effect of surface plastic deformation on fatigue strength and its mechanism. In: International conference in shot peening – 1. 1981. [9] Wagner L, Mueller C. Effect of shot peening on fatigue behavior in Al-alloys. Mater Manuf Processes 1992;7(3):423–40. [10] Dorr T, Hilpert M, Beckmerhagan P, Kiefer A, Wagner L. Influence of shot peening on fatigue performance of high-strength aluminum and magnesium alloys. In: International conference in shot peening – 7. 1999. p. 153–60. [11] Obata M, Sudo A. Effect of shot peening on residual stress and stress corrosion cracking for cold worked austenitic stainless steel. In: International conference in shot peening – 5. 1993. [12] Hanyuda T, Nakamura S, Endo T, Shimizu H. Effect of shot peening on fatigue strength of titanium alloy. In: International conference in shot peening – 5. 1993. p. 116–25. [13] Sharp PK, Clark G. The effect of peening on the fatigue life of 7050 aluminium alloy. DSTO Aeronautical and Maritime Research Laboratory; 2001. [14] Michihiko M, Takanori N, Norio K, Setsuo T, Etsuichi N. Effect of shot peening on fatigue strength of 18% Ni maraging steel. JSME Int J A 2001;44(2):301–8. [15] Ito T, Mizuno T, Takahashi T, Kurosaki J. Peening characteristics of cemented carbide peening shot and life improvement of cold forging die. In: International conference in shot peening – 7. 1999. p. 371–77. [16] Ferrari. The relationship between peening intensity and metal erosion rate with respect to nozzle angle. In: International conference in shot peening – 2. p. 269–70. [17] Neema ML, Pandey PC. A study of controlled peening parameters on the properties of machined surfaces. In: International conference in shot peening – 1. 1981. p. 201–8.
[18] Marcos E, Ivan M, Kosukie I, Drew VN. Robust design for fatigue performance: shot peening. In: Proceedings of ASME design engineering technical conferences and computers in engineering conference, Irvine, CA. 1996. p. 1–9. [19] Bronzino JD. Metallic biomaterials. The biomedical engineering handbook. 2nd ed. New York: Springer; 2000. p. 37.1–37.3, ISBN 3540663517. [20] Ratner BD. Biomaterials science: an introduction to materials in medicine. New York: Academic Press; 2004. p. 141–3, ISBN 0125824637. [21] Kirk D, Payne NJ. Transformations induced in austenitic stainless steels by shot peening. In: International conference in shot peening – 7, Warsaw, Poland. 1999. p. 15–22. [22] George L. The story of shot peening. ASNE J 1957:653–66. [23] Mahagaonkar SB, Seemikeri CY. Effect of shot peening parameters on AISI 1045 material. In: Proceedings of the national conference [ETA-2005] at Saurashtra University, Rajkot; 2006. [24] Mahagaonkar SB, Brahmankar PK, Seemikeri CY. A study of interaction effects of shot peening on surface roughness by using Taguchi technique. In: Proceedings of the PCEA – IFToMM Int Conference – PICA 2006 PCE&A, Nagpur, India; 2006. [25] Champaigne J. Controlled shot peening. 2nd ed. The Shot Peener; 1989. [26] Cammet J. Quality assurance of shot peening by automated surface and subsurface residual stress measurement. The Shot Peener 2001;15(3):7–8. [27] Lochner RH, Matar JE. Designing for quality – an introduction to the best of Taguchi and Western methods of statistical experimental design. London: Chapman and Hall; 1990. [28] Montgomery DC. Design and analysis of experiments. 5th ed. New York: John Wiley & Sons; 2003. p. 3–5, ISBN 9971513293.
Contents lists available at ScienceDirect
International Journal of Fatigue journal homepage: www.elsevier.com/locate/ijfatigue
Effect on fatigue performance of shot peened components: An analysis using DOE technique S.B. Mahagaonkar a,*, P.K. Brahmankar b, C.Y. Seemikeri a a b
Mechanical Department, Dr. BATU, Lonere (MS) 404 103, India R&D, Dr. BATU, Lonere (MS) 404 103, India
a r t i c l e
i n f o
Article history: Received 8 June 2007 Received in revised form 15 January 2008 Accepted 8 March 2008 Available online 24 March 2008 Keywords: Fatigue Surface hardness Shot peening parameters DOE ANOVA
a b s t r a c t Shot peening is widely used to improve the fatigue properties of components and structures. Residual stresses, surface roughness and work hardening are the main effects induced in the superficial layer from shot peening, which depend on the correct choice of the peening parameters. Compressive stresses are beneficial in increasing resistance to fatigue failures, corrosion fatigue, stress corrosion cracking, hydrogen assisted cracking, fretting, galling and erosion. In this paper design of experiment (DOE) technique was used in carrying out test, using an air blast type shot peening machine. This investigation examines the effect of process parameters such as pressure, shot size, nozzle distance and the exposure time on the fatigue performance of AISI 1045 and 316L material. After going through confirmation test the analysis reveals the right combination of the parameters for better process control. An ANOVA was carried out to identify significant peening parameters. Expressions correlating fatigue life and the process parameters for both materials were developed, which are useful in predicting fatigue life. This technique could prove beneficial in industries for reduction of performance variation and cost and to increase productivity. Ó 2008 Elsevier Ltd. All rights reserved.
1. Introduction Beneficial manufacturing processes include surface hardening as it induces residual compressive stress into the surface. Honing, polishing and burnishing are surface enhancing processes that remove defects and stress raisers from manufacturing operations. Surface rolling induces compressive stress but is primarily limited to cylindrical geometries. Shot peening has no geometry limitations and produces results that is usually the most economical. Shot peening, the state-of-the-art technology has potential application in the engineering field from earth to space technologies. Compared with the other advanced mechanical treatment technology like, laser shot peening (LSP) and low plasticity burnishing (LPB), which are more expensive and time consuming, shot peening process (SP) has got diversified application in the automobile, marine and aerospace vehicles in the race of high technology [1]. The surface modifications produced by the shot peening treatment are (a) roughening of the surface; (b) an increased, near-surface dislocation density (strain hardening); and (c) the development of a characteristic profile of residual stresses [2,3]. Shot peening (SP) is a cold-working process that hardens the surface of a metallic component by bombarding it with a stream * Corresponding author. Tel.: +91 23 52225807; fax: +91 23 52222435. E-mail addresses: [email protected] (S.B. Mahagaonkar), [email protected] (P.K. Brahmankar), [email protected] (C.Y. Seemikeri). 0142-1123/$ - see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijfatigue.2008.03.020
of small particles called shots. SP is viewed as a process involving multiple and progressively repeated impact. The indentation at each point of impact is the result of local plastic deformation. The mechanism of creation of compressive residual stress is the result of the superposition of the residual stress produced by the surrounding shots [4,5]. As the deformed regions tend to expand, they are restrained by adjacent, deeper metal that was not plastically deformed by the shot impact. Since the plastically deformed surface layer seeks to occupy more space it is compressively strained. This compressively stressed layer is extremely effective in preventing premature failure under conditions of cyclic loading since the fatigue failure generally propagates from the free surface of a target and starts in a zone that is subjected to tensile stresses. This phenomenon was fully explained by several researchers [6–8]. Low surface roughness increases fatigue strength as a result of higher dislocation densities near the surface due to the increase in surface hardness [9]. An increase in microhardness and surface roughness increases with increase in shot size and the peening intensity [10–12]. Fatigue properties depends on various factors such as work hardening due to the cold work, compressive residual stress, surface topography and various other local fatigue properties. Residual stresses, surface roughness and work hardening can be identified as the main effects induced in the surface layers of the material, which depend on the correct choice of the peening parameters. So far several authors have used one-factor-at-a-time approach in analyzing fatigue life behavior with the different
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peening parameters such as peening intensity [10], types of shot [13], shot size [14], shot velocity [15] and the impact angle [16]. Few authors were used design of experiment (DOE) technique with specialized single balled controlled shot peening machine [17] and some investigations have been made into the design for robust fatigue performance with the aid of simulation technique [18]. Most of the studies are made on precision-machined steels with high strength to weight ratio; such steels are typically used for various components in aircraft, turbine, and defense equipment. It is noted that hardly any shot peening studies have been made for fatigue performance of conventional materials using full factorial experiments. It is therefore, necessary to carry out comprehensive investigations, using 2k full factorial DOE to evaluate the interaction effect of process parameters such as pressure, shot size, exposure time and the nozzle distance on the fatigue life of AISI 1045 and 316L material. Mathematical models from the test results were predicted, which is useful for the quantification of fatigue life. 2. Experimental analysis Experiments were carried out to investigate the effect of SP parameters on fatigue performance of the work material. The selection of work material, SP parameters and design of experiments are given below. 2.1. Selection of material The shot peening process is one of the frontier surface enhancement technology, it aids in assuring satisfactory fatigue life and reliability of in the automotive components. The AISI 1045 material serves this purpose since its cost is less in comparison with other high strength materials. The materials selected for present investigations are AISI 316L and 1045. The grade 316L is the low carbon version of 316 and is usually regarded as ‘‘marine grade steel”. It is extensively used in the marine applications, where the parts are havocked of corrosive environment. It is also used in biomaterial applications. These materials were selected since they are widely used in marine and automobile applications. AISI 1045 steel consist of 70% pearlite and 30% ferrite with an average grain size of 25 lm (Fig. 1). The type AISI 316L materials have a fine austenite grain size with precipitate-free grain boundaries. The grain size is in the range of 30–50 lm (Fig. 2). Shot peen-
Fig. 1. AISI 1045 core material microstructure.
Fig. 2. AISI 316L core material microstructure.
ing on these materials increases dislocation density near the surface, which in turn reduces grain size. Figs. 3 and 4 show the near surface microstructure for shot peened AISI 1045 and 316L material, respectively. Since AISI 1045 is more ductile, the plastic deformation on this material will be more. Because of the effect of more cold work, it has got finer grain size as compared with 316L material. AISI 316L steel does not harden in response to heat treatments, but it can be hardened by cold working. Cold working is capable of transforming metastable austenite into martensite, the strain energy being supplied by the plastic deformation. However, it is observed that additional nickel and molybdenum in this steel impart greater austenitic stability, so that extensive plastic deformation at room temperature leaves the austenite untransformed [19,20]. If austenitic steel is transformed to a two-phase martensite and austenite structure, most of its physical, chemical and mechanical properties get affected. In that case, the ultimate tensile strength and hardness increase whereas ductility and toughness decrease [20,21]. Fatigue performance also gets affected. Shot peening on such materials increase dislocation density on the
Fig. 3. AISI 1045 near surface microstructure.
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ated, in most cases, after peening is complete. The variables that can be controlled and adjusted to obtain the desired values of intensity, saturation and coverage are air pressure, shot mass flow rate, nozzle type, feed rate of the nozzle along workpiece, distance of the nozzle from workpiece and the workpiece table speed. Since some parameters such as velocity, intensity and the coverage are difficult to control, controllable influential parameters such as pressure, shot size, nozzle distance and exposure factors were considered in the present investigation. Among the SP media, heat treated steel shots are more advantageous than the other types. Steel shot is more expensive initially than chilled iron; however, the brittle nature of chilled iron causes it to break up very rapidly and, in fact, it has but one fourth to one sixth the life of steel shot. Steel shot is therefore much cheaper in the long run; it is cleaner to handle and causes much less wear on cabinet walls, wheels, nozzles and fixtures [22]. Cut wire shots are another media used for peening; however specifications for peening steel parts requires round steel shots. Hence, for the present investigation heat-treated steel shots S-390 and S-660 having shot diameters 1.85 mm and 1 mm respectively were selected. The selection is based on ‘‘MIL-S-13165B” specifications and the surface conditions of the specimen. According to the test certificates from the manufacturer, the shots were tested and sieve analysis was done as per IS 4606 of 1983 (Table 2).
Fig. 4. AISI 316L near surface microstructure.
surface, which in turn gives rise to compressive residual stresses. This in turn results in enhancement of fatigue life of the component [21]. Experimental works were conducted on turned specimens made of medium carbon steel AISI 1045 and 316L material (Fig. 5a). The initial surface hardness for the AISI 1045 and 316L specimens in terms of Vickers hardness were 187Hv and 287Hv, respectively. Initial surface roughness (Ra) for both the materials lies between 4 and 5 lm. The chemical composition for the material is as shown in Table 1. 2.2. Selection criteria for the shot peening parameters Shot peening process relies on multiple impacts of spherical media onto a surface to achieve better surface hardness and fatigue life. The various shot peening parameters are shot type and size, intensity, saturation, incidence angle, velocity and coverage. Among these parameters, only shot type and incidence angle are controlled directly. Remaining parameters are measured or evalu-
Fig. 5a. Fatigue test specimen.
2.3. Design of experiment Screening experiments were conducted so as to identify the suitable process parameters and their levels [23,24]. These experiments revealed that magnitude of pressure greater than 4 kg/cm2 caused about fourfold reduction in fatigue life compared to the unpeened component. A similar trend was observed when excessive exposure time and larger shot size were used. On the other hand, pressure less than 2 kg/cm2 was found to result in clogging of shots due to low suction of pressurized air, which, in turn, induced lesser cold work and coverage. These findings were used as the basis for selection of process parameters and their levels as shown in Table 3. The following factors were held constant: jet obliquity equal to 90° and symphonic nozzle orifice diameter of 9 mm. The design of experiment was based on full factorial design considering four factors each at two levels. In order to reduce process and product variability the 16 runs of the experiment were replicated twice. The design matrix considering two replicates is shown in Table 4. The fatigue life of the peened and unpeened, components was tested by R.R. Moore rotating-beam fatigue machine (Fig. 5b), at a constant speed of 4340 rpm and a load of 19.62 N m (200 kg cm). In order to find the fatigue life of the components, average of the two closest values of the fatigue life of the components was considered. Fatigue life of the shot peened components was calculated in terms percentage of fatigue life. Percentage of fatigue life indicates the number of times of the peened component over the unpeened
Table 1 Chemical composition of AISI 1045 and 316L material Table 2 Chemical composition of shots
Composition
Material type AISI 1045
AISI 316L
Carbon (C) Silicon (Si) Manganese (Mn) Sulphur (S) Phosphorus (P) Chromium (Cr) Molybdenum (Mo) Nickel (Ni) Ferrous (Fe)
0.43 0.26 0.78 0.033 0.028 – – – Bal.
0.03 0.75 2.0 0.03 0.045 17.0 2.9 14.0 Bal.
Composition
Carbon (C) Silicon (Si) Manganese (Mn) Sulphur (S) Phosphorus (P) Density (kg/m3) Hardness (Hv)
Shot type S-390
S-660
0.94 0.75 0.81 0.042 0.047 7350 450
0.91 0.7 0.77 0.044 0.047 7320 450
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Table 3 Factor levels for the experiment
Table 5 Estimates of main and interaction factors
Factors 2
P: Pressure (kg/cm ) S: Shot type and shot size (mm) T: Exposure time (s) D: Nozzle distance (mm)
Lower level 1
Higher level 2
2 S-390, 1 mm 80 80
4 S-660, 1.85 mm 160 100
Table 4 Full factorial design matrix Experiment no.
P
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2
S
1 1 1 1 2 2 2 2 1 1 1 1 2 2 2 2
D
1 1 2 2 1 1 2 2 1 1 2 2 1 1 2 2
T
1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2
Main factors
Effects Fatigue life for AISI 1045 material
Fatigue life for 316L material
P S D T
9.959 10.130 37.912 23.764
0.602 23.673 13.533 10.998
Two-way interaction factors
Two-way interaction effects Estimates for AISI 1045 material
Estimates for 316L material
P–S P–D P–T S–D S–T D–T
9.530 31.559 71.944 31.004 38.530 44.746
43.290 46.303 31.098 63.791 73.746 27.561
Three-way interactions
Three-way interaction effects
Average response of replications (Y) Fatigue life in % (AISI 1045)
Fatigue life in % (316L)
249.588 401.236 418.269 442.72 264.973 392.308 417.857 307.143 361.813 421.016 388.187 211.951 432.967 178.709 415.659 404.121
462.254 398.245 214.912 424.844 344.332 388.644 412.105 302.271 344.148 472.354 375.542 352.408 428.458 165.714 412.256 401.546
Estimates for AISI 1045 material PSD PST PDT SDT
66.655 1.339 46.566 45.913
Four-way interactions
13.255 20.885 2.388 3.089
Four-way interaction effects Estimates for AISI 1045 material
PSDT Responses
Estimates for 316L material
73.626 AISI 1045 material
Maximum and minimum responses (Y) 356.782 Yaverage 387.534 Ymaximum 326.030 Yminimum
Estimates for 316L material 103.933 316L material 368.752 382.157 355.347
3. Statistical analysis
Fig. 5b. Fatigue testing equipment.
The estimated values of the main and interaction effects are given in Table 5. These values were then plotted in decreasing order of importance in the form of Pareto charts (Figs. 6 and 7) which help in testing the statistical significance of the above effects. Graphical displays such as Pareto chart and normal probability plots (Figs. 8 and 9), respectively, were be used to verify the significance of the factors and interactions. The Pareto chart show each of the estimated effects in decreasing order of magnitude. The length of each bar is proportional to the standardized effect divided
component. If Np is the fatigue life for peened component in cycles and Nu is the fatigue life for unpeened component, then percentage for fatigue life is given by FL ¼ ðN p =N u Þ100 As per the guidelines given by Champaine [23], the exposure time to achieve desired peening coverage for the material were determined by 10-magnifying lenses. Almen strips were not used since Almen strip saturation time can be misleading due to the surface hardness difference between the Almen strip and the peening material [25,26]. The averages of replications of the percentage of fatigue life values for each trial are tabulated as shown in Table 4. Table 5 shows the estimated effects for main factors and their interaction effects. These values were calculated based on the method as given by Lochner and Matar [27].
Fig. 6. Pareto chart for AISI 1045 material.
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grees of freedom) are compared with the theoretical extreme values for the F distribution [27,28]. In ANOVA, the meaning of 5% significance level means one in twenty and 1% means one in hundred. This indicates that the parameters falling in 1% significance level is most dominant factor and 5% significance level is the next dominant factor. The factors that are not falling either 1% or 5% are not significant factors. 4.1. ANOVA for fatigue life on AISI 1045 material
Fig. 7. Pareto chart for 316L material.
From ANOVA (Table 6), it can be seen that the most dominating factor among the main factors is the nozzle distance (D), since it has got higher value of F statistics. The next dominating parameter is the exposure time (T) and the least effecting factors are shot size (S) and pressure (P). Among the two-way interactions, the interaction between pressure and the exposure time (P–T) is morea significant and the next interaction effect in the decreasing order are D– T, S–T, P–D, S–D and P–S. 4.2. ANOVA for fatigue life of 316L material From the ANOVA results for 316L (Table 7), it can be seen that the most dominating factors among the main factors is the shot size and the effect of pressure is very negligent as its p-value is Table 6 Analysis of variance for fatigue life for AISI 1045
Fig. 8. Normal probability plot for AISI 1045 material.
Source
DF
Seq SS
Adj SS
Adj MS
F
p-Value
P S D T PS PD PT SD ST DT PSD PST PDT SDT PSDT
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
793 821 11,499 4518 3961 7968 41,407 7710 11,877 16,017 35,543 14 17,347 16,864 43,367
793 821 11,499 4518 3961 7968 41,407 7710 11,877 16,017 35,543 14 17,347 16,864 43,367
793 821 11,499 4518 3961 7968 41,407 7710 11,877 16,017 35,543 14 17,347 16,864 43,367
173.93 179.98 2520.69 990.35 868.41 1746.65 9077.11 1690.08 2603.54 3511.27 7791.66 3.15 3802.75 3696.93 9506.70
0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.095 0.000 0.000 0.000
Error Total
16 31
73 219,779
73
5
S = 2.13581; R2 = 99.97%; R2 (adj) = 99.94%.
Table 7 Analysis of variance for fatigue life for 316L
Fig. 9. Normal probability plot for 316L material.
by its standard error. The bars which are extending beyond 5%, indicates statistically significant at the 95% confidence level. 4. ANOVA for fatigue performance Analysis of variance (ANOVA) is used to judge whether or not the experimentally found significant factors are statistically significant. In the present investigation, MINITAB (statistical software) was used to analyze the significance of factors. The significance can also be judged by calculating F- or p-values. Furthermore, the calculated F-values (product of the square of the effect and the de-
Source
DF
Seq SS
Adj SS
Adj MS
F
p-Value
P S D T PS PD PT SD ST DT PSD PST PDT SDT PSDT
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
3 4483 1465 968 873 17,151 7737 32,554 43,508 6077 1406 3490 46 76 86,416
3 4483 1465 968 873 17,151 7737 32,554 43,508 6077 1406 3490 46 76 86,416
3 4483 1465 968 873 17,151 7737 32,554 43,508 6077 1406 3490 46 76 86,416
0.58 893.57 292.03 192.86 174.02 3418.58 1542.04 6488.56 8671.93 1211.23 280.15 695.52 9.09 15.22 17224.17
0.458 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.008 0.001 0.000
Error Total
16 31
80 206,332
80
5
S = 2.23990; R2 = 99.96%; R2 (adj) = 99.92%.
S.B. Mahagaonkar et al. / International Journal of Fatigue 31 (2009) 693–702
tion effect of T–D, S–P, D–S, D–P, T–P and T–S, were plotted separately as shown in Figs. 12–17. These plots were plotted based on the data from Table 4 considering the average value of each factor at their higher and lower levels. The maximum and minimum response values for the fatigue life for both the materials were calculated by adding the individual contribution of the main factors to the grand mean (Table 5).
Lower level-1 400.000 T
360.000
PST PST
PS PD PS
T
PT
PS
S
D
320.000
D 7%
T 4%
PS 2%
SDT 8%
PD 6%
PDT
PSD
PSDT
Fig. 11a. Graphical display of effect on AISI 1045.
440.000 PSDT
420.000
Fatigue Life in %
P S 2% 2%
SDT
ST
Main with interaction factors
SD
PSDT 14%
DT
SD
T
PT
D
ST
S
SD
P
PD
340.000
300.000
SDT
DT
PD
SDT
S
PSDT
P
PDT
PST
380.000
PSDT
PSD
PT ST SD
D
P
% of Fatigue life
Figs. 10a and 10b shows the contribution of main and other interaction factors. The graphical representation in Figs. 11a and 11b give the estimates for all the factors at their lower and higher levels. Figs. 10a and 10b show the effects of four main factors (P – pressure, S–shot size, T–exposure time and D–nozzle distance), as well as their two-, three-, and four-way interactions on the fatigue performance. In both the cases the contribution of pressure has the least significant effect on the fatigue life; however contribution of shot size and nozzle distance is more significant in case of 316L material when compared to the AISI 1045 material. The effect of nozzle distance is more predominant in case of AISI 1045 material. The interaction effect between P and S on the fatigue life is negligible in case of AISI 1045 material, but in case of 316L it is almost five times more than that of AISI 1045 material. The most dominating two-way interaction effect for AISI 1045 is P–T, but in case of 316L is S–T. For the purpose of analyzing the effects of main factors and interaction effects on the surface hardness, the two-way interac-
Higher level-2
PDT
5. Results and discussion
PSD
greater than 0.05. Among the two-way interactions, the interaction between shot size and the exposure time (S–T) is the most significant. The next interaction effects in the decreasing order are S–D, P–D, P–T and D–T. The results from the ANOVA, predicts that all the main and interaction factors are statistically significant, since the p-values for these parameters are less than 0.05 and these values proves equally the same results, with the analysis brought out by Pareto chart and normal probability chart.
DT
698
PD
400.000
PT
S D
380.000 P
T
DT PSD
PS
PST PDT
P
360.000
S
D
T
DT
PT
340.000
PSD
PST
SDT SDT
PDT
PD SD
PS
320.000
PDT 9%
ST
ST PSDT
P ST
S DT
D PSD
SD 6%
ST 7%
DT 8%
T PST
PS PDT
PD SDT
Main with Interaction Factors Lower level-1
PT PS
SD
S 5%
D T 3% 2%
0% PST 4%
500.000
PS 9%
PD 10%
Fatigue life in %
SDT PDT 1%
P 0%
Higher level-2
Fig. 11b. Graphical display of effect on 316L.
Fig. 10a. Effects on fatigue life on AISI 1045.
PSDT 22%
T PS PD
PT 13%
PT SD ST D T PS D PS T PD T SD PS T D T
PSD 12%
P S D
300.000 PST 0%
400.000 300.000
Nozzle Distance 1 Nozzle Distance 2
200.000 2
1
Exposure Time
PSD 3%
PT 7%
DT 6%
SD 13%
ST 15%
P PD PSD
S PT PST
D SD PDT
T ST SDT
PS DT PSDT
Fig. 10b. Effects on fatigue life on 316L.
Nozzle Distance 1
327.335
348.317
Nozzle Distance 2
409.993
341.484
Fig. 12a. Interaction effect between T and D for AISI 1045.
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S.B. Mahagaonkar et al. / International Journal of Fatigue 31 (2009) 693–702
450.00
394.80
400.00
370.27
350.00
356.24
353.70
300.00
Fatigue Life in%
Fatigue Life in %
450.00
250.00 200.00
1
419.25
350.00
341.93 331.79
300.00 250.00 200.00
2
1
2
Exposure Time 394.80
Nozzle Distance 1 Nozzle Distance 2
Nozzle Distance : D
356.24
353.70
382.04
400.00
370.27
Shot Size 1
419.25
341.93
Shot Size 2
331.79
382.04
Shot Size 1
Nozzle Distance 1
Shot Size 2
Nozzle Distance 2 Fig. 14b. Interaction effect between D and S for 316L.
450.000
400.000 380.000 Pressure 1
360.000
Pressure 2
340.000 320.000
1
2
400.000
Fatigue life in%
Fatigue Life in %
Fig. 12b. Interaction effect between T and D for 316L.
Pressure 1 Pressure 2
350.000 300.000 250.000 200.000
S : Shot Size Pressure 1
377.953
345.570
Pressure 2
345.742
357.864
1
2 Nozzle Distance:D
Pressure 1
327.026
396.497
Pressure 2
348.626
354.980
Fig. 13a. Interaction effect between S and P for AISI 1045. Fig. 15a. Interaction effect between D and P for AISI 1045.
390.00 386.11 370.00
375.06
450.00
361.84
360.00 350.00
Fatigue Life in%
Fatigue Life in %
380.00
351.99
340.00 330.00
1
2
400.00
398.37
385.44
352.67
338.53
350.00 300.00 250.00 200.00 1
2
S : Shot Size 375.06
361.84
Pressure 1
398.37
338.53
Pressure 2
386.11
351.99
Pressure 2
352.67
385.44
Pressure 1
Pressure 1
Pressure 2
Pressure 2
Fig. 13b. Interaction effect between S and P for 316L.
Fig. 15b. Interaction effect between D and P for 316L.
400.000
500.000
Shot Size 1
300.000 200.000
Shot Size 2 1
2
Fatigue life in%
Fatigue life in%
Nozzle Distance:D
Pressure 1
400.000
Pressure 1
300.000
Pressure 2
200.000
Nozzle Distance : D
1
2 Exposure Time
Shot Size 1
358.413
365.282
Pressure 1
337.672
385.852
Shot Size 2
317.239
386.195
Pressure 2
399.657
303.949
Fig. 14a. Interaction effect between D and S for AISI 1045.
Fig. 16a. Interaction effect between T and P for AISI 1045.
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S.B. Mahagaonkar et al. / International Journal of Fatigue 31 (2009) 693–702
369.231
Confirmation tests were carried out by setting parameters D at higher level and all other factors at their lower levels and maximum fatigue life was found to be in the range of 387.534–442.72. In analyzing the interaction effect on fatigue life, from Fig. 14a, it was found that for lower nozzle distance fatigue life increased with a decrease in shot size. However, it decreased with an increase in the nozzle distance. The two line segments are not parallel; which indicates presence of strong interaction effect between shot size and nozzle distance. From Fig. 12a, it was observed that keeping the exposure time constant, the fatigue life increased with an increase in the nozzle distance. For lower level of pressure, fatigue life increased with an increase in the pressure. However, by doubling the exposure time, it was found to decrease (Fig. 16a). The line segments in Figs. 12a–17a are not parallel, which indicates the presence of strong interaction effect between T–D, S–P, D–S, D–P, T–P and T–S. However, it is interesting to note that with the use of smaller shot size, the fatigue life increased with a decrease in pressure. But with the larger size shot, it increased with an increase in pressure (Fig. 13a). Again for the lower nozzle distance, fatigue life increased with a decrease in pressure; but at larger distance it increased with an increase in pressure (Fig. 15a).
354.464
5.2. Effect of fatigue life on 316L material
Fatigue Life in%
400.00
390.10
380.00
378.50
360.00 358.40
340.00 320.00
348.01 1
2 Exposure Time
Pressure 1
358.40
378.50
Pressure 2
390.10
348.01
Pressure 1
Pressure 2
Fig. 16b. Interaction effect between T and P for 316L.
Exposure Time 1
Exposure Time 2
400.000 382.864
Fatigue Life in%
380.000 360.000 340.000
320.570
320.000 300.000
Exposure Time 1 Exposure Time 2
1
2
354.464
382.864
369.231
320.570
Fig. 17a. Interaction effect between T and S for AISI 1045.
Shot Size 1
Shot Size 2
Fatigue Life in%
450.00 399.29
400.00 350.00
411.96
349.21
314.54
300.00 250.00
1
2 Exposure Time
Shot Size 1
349.21
411.96
Shot Size 2
399.29
314.54
Fig. 17b. Interaction effect between T and S for 316L.
5.1. Effect of fatigue life on AISI 1045 material The maximum value of fatigue life from Table 4 is 442.72, which occurred when pressure (P) and shot size (S) at lower level with the other parameters nozzle distance (D) and exposure time (T) at higher levels. Considering Fig. 11a, factors P and S can be set to their lower levels, since the same conclusion can be drawn after considering the two-way interaction effects of these factors P–D, P–T, P–S, S–D and S–T. Similarly, factor D can be set to the higher level, but the factor T should be set to its lower level, since the interaction effects P–T and D–T are more significant.
The maximum value of fatigue life from Table 4 is 472.354, which occurred when pressure (P) and exposure time (T) were at higher levels and shot size (S) and nozzle distance (D) were at lower levels. From Fig. 11b, the sole effect of pressure alone is negligible; one has to consider the two-way interaction effects between P–D, P–S and P–T in setting the level for pressure. Since the interaction effect between P and D is more dominant than other, it is suggested that pressure be set at higher level. Similarly the nozzle distance can be set to its higher value. Considering the main effects of the shot size and exposure time, and also interaction effect between S and T, they could be set to their lower level in order to maximize the fatigue performance. Confirmation tests were carried out by setting parameters P and D at higher levels and other two factors at their lower levels. The maximum fatigue life was found to be in the range of 382.157–472.354. From Fig. 14b, it was found that for lower nozzle distance, fatigue life increased with a decrease in shot size; however it decreased with an increase in the nozzle distance. The two line segments are not parallel; which indicates the presence of strong interaction effect between shot size and nozzle distance. From Figs. 12a and 12b, it was observed that keeping the exposure time constant, the fatigue life increased with an increase in nozzle distance. For lower level of pressure, fatigue life increased with in increase in the pressure. However, by doubling the exposure time it was found to decrease (Fig. 16b). In the case of 316L material, all two-way interactions indicate the presence of strong interaction effects (Figs. 12b–17b). Fatigue life increased with an increase in the shot size. But with smaller shot size, it increased with an increase in the pressure (Fig. 13b). This is an opposite effect compared to that of AISI 1045 material. 6. Regression analysis for the fatigue life Correlations for the fatigue life of both the materials were obtained by developing regression models using Analyze-it software. For this analysis, a log transformed response variable and process parameters were assumed and are tabulated as shown in Tables 8 and 9. For better curve fitting, following model was assumed: lnðYÞ ¼ b0 þ b1 lnðPÞ þ b2 lnðSÞ þ b3 lnðDÞ þ b4 lnðTÞ
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S.B. Mahagaonkar et al. / International Journal of Fatigue 31 (2009) 693–702 Table 8 Log transformed design matrix
Table 11 Coefficients and intercepts for AISI 316L material
Trial no.
P
ln(P)
S
ln(S)
D
ln(D)
T
ln(T)
Term
Coefficient
SE
p
95% CI of coefficient
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4
0.6931 0.6931 0.6931 0.6931 0.6931 0.6931 0.6931 0.6931 1.3862 1.3862 1.3862 1.3862 1.3862 1.3862 1.3862 1.3862
1 1 1 1 1.85 1.85 1.85 1.85 1 1 1 1 1.85 1.85 1.85 1.85
0 0 0 0 0.6151 0.6151 0.6151 0.6151 0 0 0 0 0.6151 0.6151 0.6151 0.6151
80 80 100 100 80 80 100 100 80 80 100 100 80 80 100 100
4.3820 4.3820 4.6051 4.6051 4.3820 4.3820 4.6051 4.6051 4.3820 4.3820 4.6051 4.6051 4.3820 4.3820 4.6051 4.6051
80 160 80 160 80 160 80 160 80 160 80 160 80 160 80 160
4.3820 5.0751 4.3820 5.0751 4.3820 5.0751 4.3820 5.0751 4.3820 5.0751 4.3820 5.0751 4.3820 5.0751 4.3820 5.0751
Intercept ln(P) ln(S) ln(D) ln(T)
6.5924 0.0185 0.1245 0.0740 0.0685
3.4153 0.2310 0.2603 0.7177 0.2310
0.0798 0.9376 0.6418 0.9198 0.7725
0.9246 0.5270 0.6975 1.6535 0.5770
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
6.2. Quantification of fatigue life for 316L material Similarly, the analysis from the results of Table 11 yields the following correlation between fatigue life (FL) and the peening parameters: lnðFLÞ ¼ 6:5924 0:0185 lnðPÞ 0:1245 lnðSÞ 0:074 lnðDÞ 0:0685 lnðTÞ
Fatigue life in percentage for 316L
AISI 1045 material
316L material
FL
ln(FL)
FL
ln(FL)
249.588 401.236 418.269 442.72 264.973 392.308 417.857 307.143 361.813 421.016 388.187 211.951 432.967 178.709 415.659 404.121
5.519812 5.99455 6.036125 6.092938 5.579628 5.972047 6.035139 5.727313 5.891128 6.042671 5.961487 5.356355 6.070662 5.185759 6.029865 6.001714
462.254 398.245 214.912 424.844 344.332 388.644 412.105 302.271 344.148 472.354 375.542 352.408 428.458 165.714 412.256 401.546
6.136115 5.987067 5.370229 6.051722 5.841606 5.962664 6.021278 5.711324 5.841072 6.157729 5.92837 5.86479 6.060193 5.110263 6.021645 5.995322
Table 10 Coefficients and intercepts for AISI 1045 material Term
Coefficient
SE
p
95% CI of coefficient
Intercept ln(P) ln(S) ln(D) ln(T)
4.1016 0.0754 0.0595 0.5516 0.1353
3.3541 0.2269 0.2557 0.7048 0.2269
0.2469 0.7460 0.8202 0.4504 0.5629
3.2808 0.5748 0.6222 0.9997 0.6347
to to to to to
11.4839 0.4240 0.5032 2.1029 0.3641
where b1, b2, b3 and b4 are the regression coefficients to be determined and Y is the fatigue life. 6.1. Quantification of fatigue life for AISI 1045 material The analysis that results from Table 10 yield the following correlation between the fatigue life and the peening parameters: lnðFLÞ ¼ 4:1016 0:0754 lnðPÞ 0:0595 lnðSÞ þ 0:5516 lnðDÞ 0:1353 lnðTÞ The above equation in an exponential form can be expressed as follows: Fatigue life in percentage for AISI 1045 ðFL1 Þ ¼ 60:44ðPÞ0:075 ðSÞ0:059 ðDÞ0:551 ðTÞ0:13
14.1095 0.4900 0.4484 1.5056 0.4401
The above equation in an exponential form can be expressed as follows:
Table 9 Log transformed response table for both materials Trial no.
to to to to to
ð1Þ
ðFL2 Þ ¼ 729:53ðPÞ0:018 ðSÞ0:124 ðDÞ0:074 ðTÞ0:069
ð2Þ
The resulting regression equations (1) and (2) yield approximate values for both the materials. However, they would serve as a useful guide for selecting proper values of process parameters for the above materials so as to obtain desired fatigue life of the component. 7. Concluding remarks To summarise, this study has, thus, brought out the effect of SP parameters on the fatigue performance of AISI 1045 and 316L material. It is interesting to note that with the use of larger shot size in case of 316L material, the fatigue life increases with a decrease in pressure, but with smaller shot size it increases with an increase in pressure. This is opposite to that of AISI 1045 material. This behaviour can be attributed to the deviation in the deformation characteristics of the peening materials. Effect of shot peening parameters, viz. pressure (P), shot size (S), exposure time (T) and nozzle distance (D) and their interactions on fatigue performance was studied using ANOVA. It was found that the process parameters that have influence on fatigue performance of AISI 1045 in decreasing order of significance are nozzle distance, exposure time, shot size and pressure. For 316L material, the order is shot size, nozzle distance, exposure time and pressure. Regression models correlating fatigue performance with process parameters have also been obtained. These equations would serve as a useful guide for setting proper values of process parameters so as to obtain desired fatigue life of the component. References [1] Brahmankar PK, Mahagaonkar SB, Seemikeri CY. Shot peening: state-of-theart. In: Proceedings of the international conference on advances in materials and material processing. 2006. p. 296–303. [2] Curtisa S, De los Rios ER, Rodopoulos CA, Levers A. Analysis of the effects of controlled shot peening on fatigue damage of high strength aluminium alloys. Int J Fatigue 2003;25:59–66. [3] O’Hara P. Super finishing and shot peening of surfaces to optimize roughness and stress. In: Brebbia CA, Kenny JM, editors. Surface treatment IV. Wessex: WIT Press; 1999. p. 321–30. [4] Kobayashi M, Matsui T, Murakami Y. Mechanism of creation of compressive residual stress by shot peening. Int J Fatigue 1998;20(5):351–7. [5] Al-Obaid YF. Shot peening mechanics: experimental and theoretical analysis. Mech Mater 1995;19:251–60. [6] Martin U, Altenberger I, Scholtes B, Kremmer K, Oettel H. Cyclic deformation and near surface microstructures of normalized shot peened steel SAE 1045. Mater Sci Eng A 1998;246:69–80.
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