Abstract
This paper develops a hybrid optimization approach for multi-criteria optimal design of a compliant positioning platform for nanoindentation tester. The platform mimics the biomechanical behavior of beetle so as to allow a linear motion. Structure of the beetle-liked mechanism consists of six legs arranging in a symmetric topology. Amplification ratio and static characteristics of the platform are analyzed by finite element analysis (FEA). To improve the performances of the platform, the main geometric parameters of the platform are optimized by an efficient hybrid approach of the Taguchi method (TM), response surface methodology (RSM), improved adaptive neuro-fuzzy inference system (ANFIS), and teaching learning based optimization (TLBO). Numerical data are collected by integrating of the RSM and FEA. Signal to noise ratios are determined and the weight factor of each response is calculated. The suitable ANFIS’s parameters are optimized through the TM. The results found that trapezoidal-shaped MFs is the best type for the safety factor and the displacement. The optimal ANFIS’s parameters for the safety factor and the displacement were determined at the number of input MFs of 4, trapmf, hybrid learning method, and linear output MFs. According to improved ANFIS establishments, TLBO algorithm is utilized for solving the multi-objective optimization. Analysis of variance and sensitivity are investigated to determine the significant effects of design factors on the responses. The simulated and experimental validations are in a good agreement with the predicted results.
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References
Álvarez MJ, Ilzarbe L, Viles E, Tanco M (2009) The use of genetic algorithms in response surface methodology. Qual Technol Quant Manag 6:295–307. https://doi.org/10.1080/16843703.2009.11673201
Bahloul R, Arfa H, Belhadjsalah H (2013) Application of response surface analysis and genetic algorithm for the optimization of single point incremental forming process. Key Eng Mater 554–557:1265–1272. https://doi.org/10.4028/www.scientific.net/KEM.554-557.1265
Bhattacharyya S, Basu D, Konar A, Tibarewala DN (2015) Interval type-2 fuzzy logic based multiclass ANFIS algorithm for real-time EEG based movement control of a robot arm. Robot Auton Syst 68:104–115. https://doi.org/10.1016/j.robot.2015.01.007
Chau NL, Nguyen MQ, Dao TP, Huang SC, Hsiao TC, Dinh DC, Dang VA (2018) An effective approach of adaptive neuro-fuzzy inference system-integrated teaching learning-based optimization for use in machining optimization of S45C CNC turning. Optim Eng. https://doi.org/10.1007/s11081-018-09418-x
Cheng C-H, Wei L-Y (2009) One step-ahead ANFIS time series model for forecasting electricity loads. Optim Eng 11:303–317. https://doi.org/10.1007/s11081-009-9091-5
Dao TP, Huang SC (2017a) Compliant thin-walled joint based on zygoptera nonlinear geometry. J Mech Sci Technol 31:1293–1303. https://doi.org/10.1007/s12206-017-0228-8
Dao TP, Huang SC (2017b) Design and multi-objective optimization for a broad self-amplified 2-DOF monolithic mechanism. Sadhana Acad Proc Eng Sci 42:1527–1542. https://doi.org/10.1007/s12046-017-0714-9
Dao TP, Ho NL, Nguyen TT, Le HG, Thang PT, Pham HT, Do HT, Tran MD, Nguyen TT (2017a) Analysis and optimization of a micro-displacement sensor for compliant microgripper. Microsyst Technol 23:5375–5395. https://doi.org/10.1007/s00542-017-3378-9
Dao TP, Huang SC, Thang PT (2017b) Hybrid Taguchi-cuckoo search algorithm for optimization of a compliant focus positioning platform. Appl Soft Comput J 57:526–538. https://doi.org/10.1016/j.asoc.2017.04.038
Fung RF, Lin WC (2009) System identification of a novel 6-DOF precision positioning table. Sens Actuators A Phys 150:286–295. https://doi.org/10.1016/j.sna.2009.01.007
Hu Z, Lynne KJ, Markondapatnaikuni SP, Delfanian F (2013) Material elastic-plastic property characterization by nanoindentation testing coupled with computer modeling. Mater Sci Eng, A 587:268–282. https://doi.org/10.1016/j.msea.2013.08.071
Huang SC, Dao TP (2016a) Design and computational optimization of a flexure-based XY positioning platform using FEA-based response surface methodology. Int J Precis Eng Manuf 17:1035–1048. https://doi.org/10.1007/s12541-016-0126-5
Huang SC, Dao TP (2016b) Multi-objective optimal design of a 2-DOF flexure-based mechanism using hybrid approach of grey-taguchi coupled response surface methodology and entropy measurement. Arab J Sci Eng 41:5215–5231. https://doi.org/10.1007/s13369-016-2242-z
Kang BH, Wen JTY, Dagalakis NG, Gorman JJ (2005) Analysis and design of parallel mechanisms with flexure joints. IEEE Trans Robot 21:1179–1184. https://doi.org/10.1007/s10773-015-2880-z
Kim HY, Ahn DH, Gweon DG (2012) Development of a novel 3-degrees of freedom flexure based positioning system. Rev Sci Instrum. https://doi.org/10.1063/1.4720410
Kumar Y, Singh PK (2018) A chaotic teaching learning based optimization algorithm for clustering problems. Appl Intell 49(3):1036–1062
Lai LJ, Zhu ZN (2017) Design, modeling and testing of a novel flexure-based displacement amplification mechanism. Sens Actuators A Phys 266:122–129. https://doi.org/10.1016/j.sna.2017.09.010
Le Zhu W, Zhu Z, Guo P, Ju BF (2018) A novel hybrid actuation mechanism based XY nanopositioning stage with totally decoupled kinematics. Mech Syst Signal Process 99:747–759. https://doi.org/10.1016/j.ymssp.2017.07.010
Ling M, Cao J, Zeng M, Lin J, Inman DJ (2016) Enhanced mathematical modeling of the displacement amplification ratio for piezoelectric compliant mechanisms. Smart Mater Struct 25:1–11. https://doi.org/10.1088/0964-1726/25/7/075022
Ling M, Cao J, Jiang Z, Zeng M, Li Q (2019) Optimal design of a piezo-actuated 2-DOF millimeterrange monolithic flexure mechanism with a pseudo-static model. Mech Syst Signal Process 115:120–131
Linh HN, Dao TP (2018) Optimal design of a compliant microgripper for assemble system of cell phone vibration motor using a hybrid approach of ANFIS and Jaya. Arab J Sci Eng. https://doi.org/10.1007/s13369-018-3445-2
Lu K, Zhang J, Chen W, Jiang J, Chen W (2014) A monolithic microgripper with high efficiency and high accuracy for optical fiber assembly. In: Proceedings of the 2014 9th IEEE conference on industrial electronics and applications, ICIEA, pp 1942–1947. https://doi.org/10.1109/iciea.2014.6931486
Nohava J, Randall NX, Conté N (2009) Novel ultra nanoindentation method with extremely low thermal drift: principle and experimental results. J Mater Res 24:873–882. https://doi.org/10.1557/jmr.2009.0127
O’brien W (2005) Long-range motion with nanometer precision. Photonics Spectra 39:80–81
Polit S, Dong J (2011) Development of a high-bandwidth XY nanopositioning stage for high-rate micro-/nanomanufacturing. IEEE/ASME Trans Mechatron 16:724–733. https://doi.org/10.1109/TMECH.2010.2052107
Rao RV, Patel V (2013) Multi-objective optimization of heat exchangers using a modified teaching-learning-based optimization algorithm. Appl Math Model 37:1147–1162. https://doi.org/10.1016/j.apm.2012.03.043
Rao RV, Savsani VJ, Vakharia DP (2011) Teaching–learning-based optimization: a novel method for constrained mechanical design optimization problems. CAD Comput Aided Des 43:303–315. https://doi.org/10.1016/j.cad.2010.12.015
Rao RV, Savsani VJ, Vakharia DP (2012) Teaching–learning-based optimization: an optimization method for continuous non-linear large scale problems. Inf Sci (Ny) 183:1–15. https://doi.org/10.1016/j.ins.2011.08.006
Singh S, Ashok A, Kumar M (2018) Adaptive infinite impulse response system identification using teacher learner based optimization algorithm. Appl Intell 49(5):1785–1802
Song M-G, Baek H-W, Park N-C, Park K-S, Yoon T, Park Y-P, Lim S-C (2010) Development of small sized actuator with compliant mechanism for optical image stabilization. IEEE Trans Magn. https://doi.org/10.1109/tmag.2010.2042288
Suraj S, Sinha RK, Ghosh S (2016) Jaya based ANFIS for monitoring of two class motor imagery task. IEEE Access 4:9273–9282. https://doi.org/10.1109/ACCESS.2016.2637401
Tawhid MA, Savsani V (2018) A novel multi-objective optimization algorithm based on artificial algae for multi-objective engineering design problems. Appl Intell 48(10):3762–3781
Thanh-Phong D, Huang S-C, Le Chau N (2018) Robust parameter design for a compliant microgripper based on hybrid Taguchi-differential evolution algorithm. Microsyst Technol 24(3):1461–1477. https://doi.org/10.1007/s00542-017-3534-2
Tsai JT, Chiu KY, Chou JH (2015) Optimal design of SAW gas sensing device by using improved adaptive neuro-fuzzy inference system. IEEE Access 3:420–429. https://doi.org/10.1109/ACCESS.2015.2427291
Wei LY (2016) A hybrid ANFIS model based on empirical mode decomposition for stock time series forecasting. Appl Soft Comput J 42:368–376. https://doi.org/10.1016/j.asoc.2016.01.027
Xiao S, Li Y, Zhao X (2011) Optimal design of a novel micro-gripper with completely parallel movement of gripping arms. In: IEEE conference on robotics, automation and mechatronics, RAM, pp 35–40. https://doi.org/10.1109/ramech.2011.6070452
Xu Q (2014) Design and testing of a novel multi-stroke micropositioning system with variable resolutions. Rev Sci Instrum 85:025002. https://doi.org/10.1063/1.4866475
Xu Q, Li Y (2011) Analytical modeling, optimization and testing of a compound bridge-type compliant displacement amplifier. Mech Mach Theory 46:183–200. https://doi.org/10.1016/j.mechmachtheory.2010.09.007
Yong YK, Aphale SS, Moheimani SOR (2009) Design, identification, and control of a flexure-based XY stage for fast nanoscale positioning. IEEE Trans Nanotechnol 8:46–54. https://doi.org/10.1109/TNANO.2008.2005829
Zukhri Z, Paputungan IV (2013) A hybrid optimization algorithm based on genetic algorithm and ant colony optimization. Int J Artif Intell Appl. https://doi.org/10.5121/ijaia.2013.4505
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The authors are thankful for the financial support from the HCMC University of Technology and Education, Vietnam, under Grant No. T2019-05TD.
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Dang, M.P., Le, H.G., Le Chau, N. et al. A multi-objective optimization design for a new linear compliant mechanism. Optim Eng 21, 673–705 (2020). https://doi.org/10.1007/s11081-019-09469-8
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DOI: https://doi.org/10.1007/s11081-019-09469-8