Laser-Machining of Microchannels in NiTi-Based Shape-Memory Alloys: Experimental Analysis and Process Optimization
Abstract
:1. Introduction
2. Material and Methods
3. Results and Discussion
3.1. Top-Width Error (TWE)
3.2. Taper Angle
3.3. Spatter
3.4. MRR
3.5. Microhardness Analysis
3.6. Optimization
4. Conclusions
- The laser machined microchannels were associated with dimensional errors, tapered side walls and spatter. However, with suitable selection of process parameters these defects could be minimized;
- In general, higher values of speed and layer thickness, along with scan strategy S1 were found to produce microchannels with least dimensional error;
- Layer thickness was found to have a significant effect on the taper angle of the microchannel. Low layer-thickness resulted in microchannels with least taper angle;
- Spatter thickness was found to be significantly affected by scan speed, layer thickness and scan strategy. Low levels of speed and layer thickness along with scan strategy S1 was found to produced microchannels with least spatter;
- MRR was mostly influenced with scan speed, layer thickness and track displacement. Higher values of speed, layer thickness and track displacement result in higher MRR;
- Multi-objective optimization was successfully carried out using MOGA-II algorithm. Optimal solution was characterized by high frequency, moderate speed and low layer-thickness and track displacement;
- Optimization provides the decision-makers with the resourceful and efficient results. Optimal solutions could be selected from within these results depending upon the requirement;
- Optimal solution resulted in a minimum taper of 12.5° and a spatter of 30.8 µm. Additional experiments and optimization algorithms could be tested for further minimization of taper and spatter;
- Microhardness tests beneath the microchannel surface showed the absence of any detrimental effect of laser processing on the material properties. However, a detailed analysis of the effect of laser processing on the functional properties of the NiTi SMAs was essential for actual applications.
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Brinson, L.C.; Lammering, R. Finite element analysis of the behavior of shape memory alloys and their applications. Int. J. Solids Struct. 1993, 30, 3261–3280. [Google Scholar] [CrossRef]
- Tarnita, D.; Tarnita, D.N.; Bizdoaca, N.; Popa, D.; Tarnita, C.E.; Cismaru, F.L. Modular Orthopedic Devices Based on Shape Memory Alloys. In Proceedings of the SYROM, Brasov, Romania, 12–15 October 2009; Visa, I., Ed.; Springer: Dordrecht, The Netherlands, 2009; pp. 709–721. [Google Scholar]
- Bellouard, Y. Shape memory alloys for microsystems: A review from a material research perspective. Mater. Sci. Eng. A 2008, 481–482, 582–589. [Google Scholar] [CrossRef] [Green Version]
- Endo, K.; Ohno, H. Corrosion Behavior of NiTi Alloys in a Physiological Saline Solution. In Shape Memory Implants; Yahia, L., Ed.; Springer: Berlin/Heidelberg, Germany, 2000; pp. 177–193. ISBN 978-3-642-59768-8. [Google Scholar]
- Kaya, E.; Kaya, İ. A review on machining of NiTi shape memory alloys: The process and post process perspective. Int. J. Adv. Manuf. Technol. 2019, 100, 2045–2087. [Google Scholar] [CrossRef]
- Weinert, K.; Petzoldt, V.; Kötter, D. Turning and Drilling of NiTi Shape Memory Alloys. CIRP Ann. 2004, 53, 65–68. [Google Scholar] [CrossRef]
- Kaynak, Y.; Karaca, H.E.; Noebe, R.D.; Jawahir, I.S. Tool-wear analysis in cryogenic machining of NiTi shape memory alloys: A comparison of tool-wear performance with dry and MQL machining. Wear 2013, 306, 51–63. [Google Scholar] [CrossRef]
- Yung, K.C.; Zhu, H.H.; Yue, T.M. Theoretical and experimental study on the kerf profile of the laser micro-cutting NiTi shape memory alloy using 355 nm Nd:YAG. Smart Mater. Struct. 2005, 14, 337–342. [Google Scholar] [CrossRef]
- Al-Ahmari, A.M.A.; Rasheed, M.S.; Mohammed, M.K.; Saleh, T. A Hybrid Machining Process Combining Micro-EDM and Laser Beam Machining of Nickel–Titanium-Based Shape Memory Alloy. Mater. Manuf. Process. 2016, 31, 447–455. [Google Scholar] [CrossRef]
- Kong, M.C.; Axinte, D.; Voice, W. Challenges in using waterjet machining of NiTi shape memory alloys: An analysis of controlled-depth milling. J. Mater. Process. Technol. 2011, 211, 959–971. [Google Scholar] [CrossRef]
- Liu, L.; Li, D.B.; Tong, Y.F.; Zhu, Y.F. Fiber laser micromachining of thin NiTi tubes for shape memory vascular stents. Appl. Phys. A 2016, 122, 638. [Google Scholar] [CrossRef]
- Sharma, N.; Gupta, K. Wire Spark Erosion Machining of Ni rich NiTi Shape Memory Alloy for Bio-Medical Applications. Procedia Eng. 2019, 35, 401–406. [Google Scholar] [CrossRef]
- Oliveira, J.P.; Cavaleiro, A.J.; Schell, N.; Stark, A.; Miranda, R.M.; Ocana, J.L.; Braz Fernandes, F.M. Effects of laser processing on the transformation characteristics of NiTi: A contribute to additive manufacturing. Scripta Mater. 2018, 152, 122–126. [Google Scholar] [CrossRef]
- Oliveira, J.P.; Braz Fernandes, F.M.; Miranda, R.M.; Schell, N.; Ocaña, J.L. Effect of laser welding parameters on the austenite and martensite phase fractions of NiTi. Mater. Charact. 2016, 119, 148–151. [Google Scholar] [CrossRef] [Green Version]
- Ilhom, S.; Seyitliyev, D.; Kholikov, K.; Thomas, Z.; Er, A.O.; Li, P.; Karaca, H.E.; San, O. Laser Shock Wave-Assisted Patterning on NiTi Shape Memory Alloy Surfaces. Shap. Mem. Superelast. 2018, 4, 224–231. [Google Scholar] [CrossRef]
- Ilhom, S. Laser-Induced Recoverable Surface Patterning on Ni50Ti50 Shape Memory Alloys. 2018. Available online: https://digitalcommons.wku.edu/theses/3052 (accessed on 11 June 2020).
- Oliveira, J.P.; Miranda, R.M.; Schell, N.; Braz Fernandes, F.M. High strain and long duration cycling behavior of laser welded NiTi sheets. Int. J. Fatigue 2016, 83, 195–200. [Google Scholar] [CrossRef] [Green Version]
- Wilhelm, E.; Richter, C.; Rapp, B.E. Phase change materials in microactuators: Basics, applications and perspectives. Sens. Actuators Phys. 2018, 271, 303–347. [Google Scholar] [CrossRef]
- Neurohr, A.J.; Dunand, D.C. Shape-memory NiTi with two-dimensional networks of micro-channels. Acta Biomater. 2011, 7, 1862–1872. [Google Scholar] [CrossRef]
- Farasati, R.; Ebrahimzadeh, P.; Fathi, J.; Teimouri, R. Optimization of laser micromachining of Ti–6Al–4V. Int. J. Lightweight Mater. Manuf. 2019, 2, 305–317. [Google Scholar] [CrossRef]
- Leone, C.; Genna, S.; Tagliaferri, F.; Palumbo, B.; Dix, M. Experimental investigation on laser milling of aluminium oxide using a 30 W Q-switched Yb:YAG fiber laser. Opt. Laser Technol. 2016, 76, 127–137. [Google Scholar] [CrossRef]
- Campanelli, S.L.; Casalino, G.; Contuzzi, N. Multi-objective optimization of laser milling of 5754 aluminum alloy. Opt. Laser Technol. 2013, 52, 48–56. [Google Scholar] [CrossRef]
- Lei, C.; Pan, Z.; Jianxiong, C.; Tu, P. Influence of processing parameters on the structure size of microchannel processed by femtosecond laser. Opt. Laser Technol. 2018, 106, 47–51. [Google Scholar] [CrossRef]
- Chen, T.-C.; Darling, R.B. Laser micromachining of the materials using in microfluidics by high precision pulsed near and mid-ultraviolet Nd:YAG lasers. J. Mater. Process. Technol. 2008, 198, 248–253. [Google Scholar] [CrossRef]
- Karazi, S.M.; Issa, A.; Brabazon, D. Comparison of ANN and DoE for the prediction of laser-machined micro-channel dimensions. Opt. Lasers Eng. 2009, 47, 956–964. [Google Scholar] [CrossRef] [Green Version]
- Benton, M.; Hossan, M.R.; Konari, P.R.; Gamagedara, S. Effect of Process Parameters and Material Properties on Laser Micromachining of Microchannels. Micromachines 2019, 10, 123. [Google Scholar] [CrossRef] [Green Version]
- Teixidor, D.; Ferrer, I.; Ciurana, J.; Özel, T. Optimization of process parameters for pulsed laser milling of micro-channels on AISI H13 tool steel. Robot. Comput. Integr. Manuf. 2013, 29, 209–218. [Google Scholar] [CrossRef]
- Campanelli, S.L.; Ludovico, A.D.; Bonserio, C.; Cavalluzzi, P.; Cinquepalmi, M. Experimental analysis of the laser milling process parameters. J. Mater. Process. Technol. 2007, 191, 220–223. [Google Scholar] [CrossRef]
- Shukla, A.K.; Jayachadndran, S.; Bhoyar, J.V.; Akash, K.; Mani Prabu, S.S.; Bhirodkar, S.L.; Shiva, M.S.; Palani, A.I. Micro-channel fabrication on NiTi shape memory alloy substrate using Nd3+: YAG laser. Mater. Manuf. Process. 2020, 35, 270–278. [Google Scholar] [CrossRef]
- Wang, X.; Huang, Y.; Xing, Y.; Fu, X.; Zhang, Z.; Ma, C. Fabrication of micro-channels on Al2O3/TiC ceramics using picosecond laser induced plasma micromachining. J. Manuf. Process. 2019, 44, 102–112. [Google Scholar] [CrossRef]
- Singh, S.S.; Baruah, P.K.; Khare, A.; Joshi, S.N. Effect of laser beam conditioning on fabrication of clean micro-channel on stainless steel 316L using second harmonic of Q-switched Nd:YAG laser. Opt. Laser Technol. 2018, 99, 107–117. [Google Scholar] [CrossRef]
- Biswas, R.; Kuar, A.S.; Sarkar, S.; Mitra, S. A parametric study of pulsed Nd:YAG laser micro-drilling of gamma-titanium aluminide. Opt. Laser Technol. 2010, 42, 23–31. [Google Scholar] [CrossRef]
- Ghosal, A.; Manna, A. Response surface method based optimization of ytterbium fiber laser parameter during machining of Al/Al2O3-MMC. Opt. Laser Technol. 2013, 46, 67–76. [Google Scholar] [CrossRef]
- Mohammed, M.K.; Umer, U.; Abdulhameed, O.; Alkhalefah, H. Effects of Laser Fluence and Pulse Overlap on Machining of Microchannels in Alumina Ceramics Using an Nd:YAG Laser. Appl. Sci. 2019, 9, 3962. [Google Scholar] [CrossRef] [Green Version]
Factor | 1 | 2 | 3 | 4 |
---|---|---|---|---|
Frequency | 25 kHz | 35 kHz | 40 kHz | |
Scan speed | 200 mm/s | 400 mm/s | 600 mm/s | |
Layer thickness | 1 µm | 2 µm | 3 µm | |
Track displacement | 8 µm | 10 µm | 12 µm | |
Scan strategy | S1 | S2 | S3 | S4 |
Run | Frequency (kHz) | Speed (mm/sec) | Layer Thickness (µm) | Track Disp. (µm) | Scan Strategy | TWE (µm) | Taper (degree) | Spatter (µm) | MRR (µm3/s) |
---|---|---|---|---|---|---|---|---|---|
1 | 40 | 200 | 2 | 8 | 3 | 53.4 | 24.9 | 39.3 | 793,647.4 |
2 | 35 | 400 | 1 | 10 | 3 | 73.5 | 15.6 | 38.6 | 939,033.5 |
3 | 35 | 400 | 2 | 12 | 1 | 44.9 | 21.1 | 37.2 | 2,038,995 |
4 | 40 | 600 | 1 | 8 | 2 | 41.7 | 18.4 | 51.0 | 722,953 |
5 | 25 | 200 | 2 | 10 | 4 | 86.2 | 23.8 | 38.4 | 1,384,979 |
6 | 35 | 600 | 3 | 8 | 4 | 52.9 | 19.8 | 44.6 | 2,172,235 |
7 | 35 | 400 | 3 | 12 | 3 | 66.1 | 29.6 | 40.1 | 2,177,359 |
8 | 25 | 600 | 1 | 8 | 1 | 44.9 | 26.0 | 30.5 | 939,763.4 |
9 | 40 | 200 | 1 | 12 | 3 | 75.0 | 19.6 | 30.7 | 826,080.4 |
10 | 40 | 600 | 3 | 8 | 1 | 53.9 | 24.2 | 34.6 | 1,380,986 |
11 | 40 | 400 | 2 | 12 | 2 | 59.2 | 26.8 | 39.5 | 1,668,078 |
12 | 40 | 400 | 1 | 10 | 1 | 56.6 | 19.1 | 23.5 | 1,146,676 |
13 | 40 | 600 | 3 | 10 | 4 | 41.2 | 22.2 | 51.5 | 2,006,592 |
14 | 40 | 200 | 3 | 12 | 1 | 48.1 | 25.4 | 41.4 | 3,005,666 |
15 | 40 | 400 | 2 | 10 | 4 | 59.7 | 23.9 | 35.5 | 1,601,717 |
16 | 40 | 200 | 2 | 10 | 1 | 49.1 | 21.1 | 28.2 | 1,354,825 |
17 | 25 | 400 | 1 | 10 | 4 | 60.2 | 16.0 | 28.0 | 1,037,431 |
18 | 35 | 400 | 3 | 10 | 2 | 51.2 | 28.5 | 37.9 | 1,909,948 |
19 | 35 | 600 | 1 | 10 | 2 | 51.2 | 21.4 | 36.1 | 1,021,419 |
20 | 35 | 600 | 2 | 10 | 4 | 45.4 | 25.0 | 43.5 | 1,770,126 |
21 | 35 | 400 | 1 | 8 | 4 | 62.4 | 17.2 | 33.2 | 872,032.6 |
22 | 35 | 600 | 1 | 8 | 3 | 73.5 | 15.8 | 26.8 | 1,101,263 |
23 | 40 | 200 | 3 | 10 | 2 | 76.2 | 23.1 | 44.8 | 2,294,011 |
24 | 25 | 200 | 1 | 12 | 2 | 68.7 | 20.2 | 30.6 | 911,940.7 |
25 | 35 | 400 | 3 | 8 | 1 | 31.7 | 21.9 | 49.1 | 2,481,353 |
26 | 35 | 600 | 3 | 12 | 2 | 40.2 | 23.5 | 44.7 | 2,472,150 |
27 | 40 | 600 | 3 | 12 | 3 | 31.1 | 26.9 | 51.9 | 2,497,826 |
28 | 25 | 400 | 1 | 12 | 1 | 51.8 | 18.9 | 28.7 | 1,151,930 |
29 | 35 | 400 | 2 | 8 | 3 | 74.5 | 16.3 | 31.2 | 1,329,239 |
30 | 25 | 200 | 1 | 10 | 3 | 101.0 | 28.1 | 12.3 | 726,000.4 |
31 | 40 | 200 | 1 | 8 | 1 | 43.8 | 20.2 | 33.3 | 832,969.2 |
32 | 25 | 400 | 2 | 12 | 4 | 43.5 | 26.1 | 44.5 | 1,664,514 |
33 | 35 | 200 | 2 | 12 | 3 | 64.0 | 22.8 | 39.7 | 1,376,418 |
34 | 25 | 600 | 1 | 12 | 3 | 46.5 | 18.5 | 32.2 | 1,135,224 |
35 | 40 | 400 | 3 | 8 | 3 | 57.6 | 25.4 | 40.2 | 1,850,694 |
36 | 25 | 600 | 3 | 12 | 1 | 39.1 | 24.4 | 43.6 | 2,633,723 |
37 | 25 | 200 | 3 | 10 | 1 | 45.4 | 19.9 | 35.8 | 1,908,810 |
38 | 25 | 400 | 2 | 10 | 1 | 42.3 | 19.2 | 40.0 | 2,010,132 |
39 | 35 | 600 | 3 | 10 | 1 | 42.8 | 24.8 | 41.5 | 2,544,111 |
40 | 40 | 400 | 1 | 12 | 4 | 68.7 | 15.9 | 30.8 | 1,103,753 |
41 | 25 | 400 | 3 | 10 | 3 | 48.8 | 32.4 | 46.7 | 1,711,848 |
42 | 35 | 200 | 2 | 10 | 2 | 62.4 | 18.8 | 32.6 | 1,312,411 |
43 | 25 | 400 | 1 | 10 | 2 | 67.3 | 18.7 | 37.3 | 964,982.6 |
44 | 40 | 400 | 2 | 8 | 1 | 51.3 | 21.6 | 28.9 | 1,245,896 |
45 | 40 | 600 | 1 | 8 | 4 | 49.8 | 12.5 | 53.1 | 900,554.5 |
46 | 25 | 400 | 1 | 8 | 3 | 68.8 | 16.0 | 29.0 | 925,104.2 |
47 | 35 | 200 | 1 | 12 | 1 | 62.4 | 20.6 | 19.3 | 1,020,239 |
48 | 35 | 200 | 2 | 8 | 1 | 34.5 | 17.7 | 39.0 | 1,368,914 |
49 | 35 | 600 | 2 | 8 | 2 | 52.5 | 18.3 | 36.1 | 1,995,799 |
50 | 40 | 400 | 2 | 10 | 3 | 65.6 | 20.1 | 31.6 | 2,000,856 |
51 | 25 | 400 | 3 | 8 | 2 | 52.3 | 25.4 | 42.7 | 2,070,845 |
52 | 35 | 200 | 1 | 10 | 4 | 68.3 | 16.1 | 30.7 | 722,609.9 |
53 | 25 | 600 | 2 | 8 | 3 | 46.5 | 26.2 | 39.3 | 1,603,850 |
54 | 35 | 200 | 3 | 10 | 3 | 47.3 | 17.5 | 44.2 | 1,476,022 |
55 | 40 | 600 | 1 | 10 | 3 | 57.1 | 15.5 | 30.7 | 1,184,823 |
56 | 25 | 200 | 2 | 8 | 2 | 54.0 | 23.2 | 33.5 | 1,124,789 |
57 | 25 | 400 | 3 | 12 | 4 | 45.5 | 26.5 | 46.7 | 2,474,509 |
58 | 40 | 200 | 2 | 12 | 4 | 73.1 | 23.7 | 34.9 | 1,418,359 |
59 | 35 | 200 | 1 | 8 | 2 | 69.3 | 19.6 | 28.5 | 700,093.2 |
60 | 35 | 600 | 1 | 12 | 4 | 55.6 | 16.4 | 32.3 | 1,270,329 |
61 | 40 | 200 | 3 | 8 | 4 | 67.8 | 25.6 | 36.2 | 1,381,260 |
62 | 25 | 600 | 3 | 10 | 2 | 40.7 | 25.6 | 46.9 | 2,569,118 |
63 | 40 | 600 | 2 | 12 | 1 | 46.1 | 22.0 | 35.2 | 1,646,294 |
64 | 25 | 200 | 3 | 12 | 3 | 63.5 | 23.8 | 34.2 | 1,832,067 |
65 | 25 | 200 | 1 | 8 | 4 | 73.6 | 17.3 | 27.0 | 778,558.2 |
Objective function | 1. Minimize taper |
2. Minimize spatter | |
Constraints | 1. TWE < 50 µm |
2. MRR > 900,000 µm3/s |
ID | Frequency (kHz) | Speed (mm/sec) | Layer Thickness (µm) | Track Disp. (µm) | Scan Strategy | Taper (Degree) | Spatter (µm) | TWE (µm) | MRR (µm3/sec) | |
---|---|---|---|---|---|---|---|---|---|---|
A | 40 | 600 | 1 | 8 | 4 | 12.5 | 53.1 | 49.8 | 900554.5 | F |
B | 40 | 400 | 1 | 8 | 4 | 12.5 | 30.8 | 60.2 | 872032.6 | NF |
C | 40 | 450 | 1 | 8 | 4 | 12.5 | 35.1 | 59.6 | 905973.3 | NF |
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Mohammed, M.K.; Al-Ahmari, A. Laser-Machining of Microchannels in NiTi-Based Shape-Memory Alloys: Experimental Analysis and Process Optimization. Materials 2020, 13, 2945. https://doi.org/10.3390/ma13132945
Mohammed MK, Al-Ahmari A. Laser-Machining of Microchannels in NiTi-Based Shape-Memory Alloys: Experimental Analysis and Process Optimization. Materials. 2020; 13(13):2945. https://doi.org/10.3390/ma13132945
Chicago/Turabian StyleMohammed, Muneer Khan, and Abdulrahman Al-Ahmari. 2020. "Laser-Machining of Microchannels in NiTi-Based Shape-Memory Alloys: Experimental Analysis and Process Optimization" Materials 13, no. 13: 2945. https://doi.org/10.3390/ma13132945