Assessment, analysis and optimization for high temperature sliding wear process parameter with additive built nickel-base superalloy

doi:10.21203/rs.3.rs-3141664/v1

Download PDF

Research Article

Assessment, analysis and optimization for high temperature sliding wear process parameter with additive built nickel-base superalloy

https://doi.org/10.21203/rs.3.rs-3141664/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

The nickel-base superalloy is developed through an additive manufacturing process following a metal laser sintering technique. The developed alloy is used to perform high-temperature sliding wear analysis with the different input process conditions. Applied load, sliding duration and the working temperature are the defined process environment for the investigation. The process conditions are designed with twenty-seven sets of experimental trials for statistical analysis and process assessment. The responses on surface roughness and the material loss with respect to the input process parameters are technically assessed and justifications are made with the electron microscopic images. The surface topography has been influenced due to applied load and the sliding duration. The statistical analysis has proved that the influence of temperature is less and negotiable compared to the load and time factors. From the optimization process, the optimal parameter for the experimental design is 10 N, 100 ºC and 30 min is the ultimate condition to produce the best results from the high temperature sliding wear analysis.

additive manufacturing

wear

mass

optimization

The nickel alloys are in high demand for mechanical structures operating at an elevated temperature. These alloys are recommended by the materialist due to their inherent properties in mechanical loading and metallurgical phase transformation at different operating conditions. The mechanical testing and failures of the material under different load conditions are available in the existing literatures [1]. The materials failure is discussed for load conditions such rotational force, tensile force, compressive force, shear force, etc to decide the selection of materials. In another way of research, the load combinations like thermo – mechanical loading, high temperature tribological studies, thermo – chemical studies and many more available in the literatures [2, 3]. To protect the component such aggressive operating environment and to increase the reliability of the material; the research pave attention towards the development of the alloy. As an outcome, the development of conventional cast route nickel alloys is manufactured through additive manufacturing process. The additive manufacturing techniques are made through different process. Innovations in additive manufacturing has a tremendous future in all disciplines [4]. The additive manufacturing techniques depends on the materials properties, shape and size of the product to be developed. Especially the nickel alloys are highly sensitive and they are tough to develop using directional solidification process. Metal laser sintering is the versatile process to develop hard and tough materials with less in wastage. In this paper, a nickel-based superalloy is developed and subjected to perform a high temperature sliding wear experimental investigation. The sliding wear analysis using pin – on – disc is common experimental procedure followed to decide the frictional wear behaviour of any materials [5–7]. For lightweight materials and the composite material, the wear analysis is in enormous to discuss about. There is a research gap to take additive built nickel alloy for sliding wear behaviour and process optimization.

In order to recommend the optimal process (working environment) condition, statistical analysis and optimization tools are widely used [8]. The analysis of variance (ANOVA) is the common tool used to study the influence of input process parameters. Research on other tools such as grey relation analysis (GRA), Taguchi, MOORA, TOPSIS and other statistical tools are widely used for process optimization [8–12]. The response from the statistical tools are used to fix the goodness of fit curve and to infer that the data generated is to be recommended or not. Followed for response surface methodology (RSM) is used to find the optimal process condition and the same are used to make the confirmation test.

In this paper, it has been proposed to develop nickel alloy using additive manufacturing. The developed alloys are prepared for high sliding wear analysis following the ASTM standards. The test is planned for different process condition and the results are proposed to evaluated using statistical tools. The influence of the process parameters is in scope and the optimal process condition for the proposed design of experiments. From the analysis, the recommendations are made.

The nickel alloys are very challenging to develop and process for high temperature applications. In this research the nickel alloy was developed through 3D printing procedure following the industrial standards. The alloys made of laser sintering on metal powders and they are solidified to a solid structure. The standard process conditions as follows: Laser energy – 285w, laser scan speed – 950mm/s, hatching – 0.15mm in horizontal direction and hatch thickness – 40µm. The elemental composition of the alloy developed has Ni – 52.3%, Fe – 19.8%, Cr – 17.5%, Nb – 4.7%, Mo – 3.38%, Ti – 1.1% and traces of Al, Si, C, Co & W throughout the bulk. These samples are processed as built are fixed to a cubic shape for a dimension of 8 mm as a work material for high temperature sliding wear analysis. The 3D printed samples are brazed to an austenitic stainless steel (SS316) material available in the form of cylindrical rod. The photo image of the sample prepared for high temperature sliding wear is as given in the Fig. 1.

To study the high temperature sliding wear behaviour of the 3D printed material, a friction and wear test rig / analyser is used for the investigation. The photo image and the work model of the test setup is given in the Fig. 2. It works based on the procedure of pin – on – disc test rig; where the samples slide for a defined working condition based on experimentally designed process parameters. Internationally recommended standard procedure designated as ASTM G99–05 using the pin – on – disc tribometer (Model: Ducom – TR20LE) is used for experimental investigation. The counter material used as a disc for sliding wear analysis is designated as high – grade hard steel which is considered for the application of turbine power shaft made of nickel alloy fixed over the hard steel hub to control friction vibration and for energy transformation. The experiments are controlled through the PID control device integrated with data acquisition system.

The input process parameters for the proposed investigation are (i) applied load (N); (ii) work temperature (ºC); and (iii) sliding time (min). The experiments are planned for twenty-seven combinations of trials as given in the Table 1 and the work plans are made to report on surface roughness and the mass loss.

Table 1

Design of experiments for high temperature sliding wear analysis
Exp No.	Input Parameter
Exp No.	Load (N)	Temp (ºC)	Time (min)
1	5	100	10
2	5	100	20
3	5	100	30
4	5	150	10
5	5	150	20
6	5	150	30
7	5	200	10
8	5	200	20
9	5	200	30
10	10	100	10
11	10	100	20
12	10	100	30
13	10	150	10
14	10	150	20
15	10	150	30
16	10	200	10
17	10	200	20
18	10	200	30
19	15	100	10
20	15	100	20
21	15	100	30
22	15	150	10
23	15	150	20
24	15	150	30
25	15	200	10
26	15	200	20
27	15	200	30

In addition, the tested materials are investigated with the electron microscope to report on wear morphology and the influence of process parameters. Followed by the experimental evaluations with different mathematical techniques to justify the influence of input process parameters. In this case the minimum surface roughness and the minimum material loss is expected as a major response. To study the influence of input process parameters, analysis of variance is adopted and to find the unknown – test data the regression equation is generated. The response surface methodology is used to find the optimized process parameters from the experimental data developed. Based on the statistical analysis and the optimization, the process conditions are recommended for similar work material.

Sliding wear – material loss, surface roughness and surface topography

The additive manufactured samples are investigated for the high temperature sliding wear and the moss loss measured. The mass loss indicates that the frictional energy developed during the sliding has highly influenced towards the material loss. Figure 3 represents the measured mass loss with respect to the sliding time at different applied load conditions. It is clear that the minimum material loss during the friction is 0.103 g at applied load 5 N. For the same case, the mass loss increases with increase in temperature. It infers that, when there is increase in temperature the material sensitivity has influenced towards deformation and material loss occurs. Subsequently, with increase in applied load the sensitivity has highly influenced on surface wear and the material loss trend increases. At an applied load of 15 N the maximum material loss was recorded 0.2 to 0.31 g.

The high temperature sliding wear test samples after materials deformation is subjected to measure the surface roughness for discussion. At this state the severity of the working condition has made the material to undergo severe surface degradation and the responses are revealed in the form of wear tracks. Figure 4 depicts the surface roughness value measured at each test conditions. Maximum surface roughness of 1.76 µm is recorded from the investigation for the maximum applied load of 15 N. While investigation, the material in contact with the counter surface are prone to severe surface roughness with increase in applied load and temperature. In addition, the wear debris at the contact surface may also influence over roughening the area. In the same case for minimum applied load surface roughness measured are in the range of 0.5–0.57 µm. During investigation the samples do slide with a centrifugal force and the mechanical action between the pin and the disc will lead to surface damage.

The test samples are analysed with the support of scanning electron microscope (SEM) to reveal the surface topography. Figure 5 illustrates the profile of worn surface at different process conditions. These samples are chosen based on the results of surface roughness and the conditions are given in the inset of the Fig. 5 caption. The minimal roughness was notices with 200 ºC – 5 N – 10 min process condition. As the wear tracks are less but the wear scars are deep in penetration. The depth of penetration might be due to the temperature sensitised by the material during the experimentation. For minimum applied load with low working temperature the surface roughness was found to be average after 30 min of experimentation at the process condition of 100 ºC – 5 N – 30 min. The wear scars are less and uniform throughout the contact surface. Similarly, for the 150 ºC – 15 N – 10 min process condition the roughness revealed close to 100 ºC – 5 N – 30 min. On continuous process the wear has extended in severe for 150 ºC – 15 N at the end of 30 min. The contact surface has prone to severe wear and the surface topography revealed with maximum wear tracks. The exposed contact area has a severe worn surface with material loss due to abrasion and ablate of material in bulk. This is the hybrid action of mechanical and metallurgical transformation held over the contact surface. In order to control material behaviour, the post processing of 3D printed materials can be one the scope in future to lead the proposed work study.

Figure 5: Electron image of test samples after high temperature sliding wear analysis

Statistical Analysis and Process optimization

The experimental data derived from the investigation are used to evaluate using statistical analysis tool and response surface methodology (RSM) to optimize the process parameter for surface roughness and material loss. The statistical analysis is performed using MINITAB software for the twenty seven set of experiments as given in the Table 2.

Table 2

Experimental plan and response for the sliding wear analysis
Exp No.	Input Parameter			Responses
Exp No.	Load (N)	Temp (ºC)	Time (min)	SR (µm)	mass loss (g)
1	5	100	10	0.316	0.046
2	5	100	20	0.487	0.068
3	5	100	30	0.568	0.104
4	5	150	10	0.412	0.057
5	5	150	20	0.489	0.068
6	5	150	30	0.577	0.108
7	5	200	10	0.298	0.071
8	5	200	20	0.347	0.083
9	5	200	30	0.509	0.132
10	10	100	10	0.587	0.059
11	10	100	20	0.875	0.088
12	10	100	30	1.384	0.142
13	10	150	10	0.508	0.065
14	10	150	20	0.789	0.079
15	10	150	30	1.26	0.155
16	10	200	10	0.487	0.049
17	10	200	20	0.724	0.087
18	10	200	30	1.226	0.192
19	15	100	10	0.759	0.093
20	15	100	20	0.987	0.170
21	15	100	30	1.693	0.233
22	15	150	10	0.865	0.130
23	15	150	20	1.216	0.193
24	15	150	30	1.766	0.307
25	15	200	10	0.814	0.087
26	15	200	20	1.112	0.120
27	15	200	30	1.644	0.240

From the experimental investigation, the responses on surface roughness – SR and material loss are evaluated for the input process parameters – load (N), temperature (ºC) and sliding time (min). The significant reason for the material loss and the surface roughness of the worn samples are discussed in the previous section. In order to study the influence of input process parameter in detail, the statistical tool is used to study the contribution through analysis of variance (ANOVA). From the analysis of variance, the influence of input parameters evaluated are given in Fig. 6. It is clear to infer that the applied load (N) and the sliding time (min) are the two predominant factors to influence the responses on material loss (g) and surface roughness (µm). For material loss has 53.6% of contribution for sliding time and 43% for applied load; it shows that the time has highly influenced towards the wear and material loss. Subsequently the applied load has 53% and 36% for sliding time. Roughness has impact on applied load and the contact area. At the same time, the contribution for the temperature has not influenced towards material loss. Temperature for the nickel alloy has less impact which is negotiable compare to the other two process parameters (load and time). The data generated from the experiments are evaluated to check the fitness and it is confirmed that the data falls in tract. The R² (residual value) value for the proposed design of experiment is 90.26% for material loss and 86.05% for surface roughness. The regression equation derived from the design of experimental analysis is as follows.

SR(Ra) = -0.458 + 0.07614 Load − 0.000550 Temp + 0.03101 Time

Mass Loss = -0.0896 + 0.00928 Load + 0.000066 Temp + 0.005313 Time

The regression equation has used to find the nearest value for the proposed design of experiments for unknown set of experiments. It has very less difference and the values are acceptable. This technique can be used to study unknown value of test data within the boundary limit of proposed design.

The interrelation between the input process parameters and the response outcomes are discussed with contour plots. The surface roughness value for the proposed experimental design are presented in Fig. 7. As discussed from the analysis of variance, the time and load factors are the major presider to produce wide variation in surface roughness. The interrelation between the load and the temperature has very meagre influence over surface roughness. At the same the relation between the temperature and the time are in negotiable relations. The same pattern was recorded for the material loss studies having strong influence between the load and sliding durations. All other two combinations negotiable and or steady to ignore for response methodology. Figure 8 infers the results for mass loss in similar to surface roughness.

In continuation to the surface plot for process parameters interrelation, the response surface methodology was adopted to predict the optimal process parameter. Based on the experimental design, for the twenty-seven set (three factors) of trial run response surface methodology was design and executed. From the execution the experimental data generated from the investigation falls in line with the normal probability line. Residual plot for the response surface methodology is depicted in the Fig. 9. Similar graphical data was extracted for material loss and it has been given in Fig. 10. Data generated for the also meets the desired expectations and the quality data are validated. From the analysis it has been noticed that the best process condition was 10 N applied load at a working temperature of 100 ºC for a sliding time of 30 min. It is also merit to say that the responses aligned near to the experimental data for the same process conditions. Therefore, the demand for confirmation test has been neglected to redo the work.

From the assessment, analysis and optimization on high temperature sliding wear studies, following points are derived as an major outcome of the research.

The mass loss at minimum load is very less and it is 0.103 g for 5 N load. At the same it has increase from 0.2 to 0.31 g, with respect to increase in applied load. For maximum load, the intensity of the material has paved way to worn fast and more with the counter material.
Surface finish results are as same as mass loss. The minimum roughness of 0.5 µm was recorded for minimum load of 5 N and 1.76 µm was recorded for the maximum load of 15 N. The influence of load and time has made the surface contact to undergo severe damage with contact area.
From the statistical analysis, the impact of temperature found less. As mentioned, the material physical action due to applied load and the sliding time has induced the material to degrade maximum. Average process condition; 10 N, 100 ºC and 30 min can produce better combination for the material developed.

Funding

No funding was received for conducting this study

Conflicts of interest

There is no conflict of interest

Availability of data and material

All data generated or analysed during this study are included in this article.

Jambor M., Bokůvka O., Nový F., Trško L., & Belan J. (2017). Phase transformations in nickel base superalloy Inconel 718 during cyclic loading at high temperature. Production engineering archives, 15(15), 15-18.
B Anush Raj, J T Winowlin Jappes, M Adam Khan, V Dillibabu and Rajesh Jesudoss Hynes (2022) Studies on mechanical attrition and surface analysis on heat treated nickel alloy developed through additive manufacturing, Advances in Materials Science and Engineering. (doi.org/10.1155/2022/4861346)
B Anush Raj, J T Winowlin Jappes, M Adam Khan, V Dillibabu and NC Brintha (2021) Studies on SU718 alloy developed using laser sintering on the additive manufacturing process, Optik - International Journal for Light and Electron Optics 229(2):166252. DOI: 10.1016/j.ijleo.2020.166252
Adam Khan M and Winowlin Jappes JT; Innovations in Additive Manufacturing, Springer Cham, Switzerland, 2022. doi.org/10.1007/978-3-030-89401-6
S C Samuel, M Arivarasu, T R Prabhu, High temperature dry sliding wear behaviour of laser powder bed fused Inconel 718, Additive Manufacturing 34 (2020) 101279
S. Deepak Kumar, D. Karthik, A. Mandal, J.S.R. Pavan Kumar, M. Chakraborty, Mater. Tod. Proc. (4) (2017) 9987–9991.
Abdul Aabid, Mohammed Ali Murtuza, Sher Afghan Khan, Muneer Baig, Optimization of dry sliding wear behavior of aluminium-based hybrid MMC's using experimental and DOE methods, Journal of Materials Research and Technology, 2022, 16:743e763.
K. Gajalakshmi, N. Senthilkumar, B. Prabhu, Meas. Control (52) (5–6) (2019) 540–553.
Mohammad Mohsin Khan, Abhijit Dey, Mohammad Irfan Hajam, Experimental Investigation and Optimization of Dry Sliding Wear Test Parameters of Aluminum Based Composites, Silicon 2021, https://doi.org/10.1007/s12633-021-01158-5
G Girish and V Anandakrishnan, Optimization of dry sliding wear parameters of recursive friction stir processed aluminium 7075 alloy, Proc IMechE Part J:J Engineering Tribology, 2020, 1–10
Ulas Caydas, Ahmet Hascalik, (2008) “Use of the grey relational analysis to determine optimum laser cutting parameters with multi-performance characteristics”, Optics & Laser Technology 40.
Subbarayan Sivasankaran, OPTIMIZATION AND ANALYSIS OF DRY SLIDING WEAR BEHAVIOR OF STIR CASTED AlSi6Cu4–TiO2 COMPOSITE USING CENTRAL COMPOSITE DESIGN, Surface Review and Letters, 2018, 1950052 (11 pages)

No competing interests reported.

Download PDF

Version 1

posted

You are reading this latest preprint version

Assessment, analysis and optimization for high temperature sliding wear process parameter with additive built nickel-base superalloy

Status:

Version 1

Abstract

Figures

Introduction

Experimental Design and Processing

Results and Discussion

Sliding wear – material loss, surface roughness and surface topography

Statistical Analysis and Process optimization

Conclusion

Declarations

References

Additional Declarations

Status:

Version 1