Browse > Article
http://dx.doi.org/10.7234/composres.2022.35.5.303

Stiffness Enhancement of Piecewise Integrated Composite Robot Arm using Machine Learning  

Ji, Seungmin (Department of Mechanical Engineering, Graduated School, Kongju National University)
Ham, Seokwoo (Department of Mechanical Engineering, Graduated School, Kongju National University)
Cheon, Seong S. (Department of Mechanical Engineering, Graduated School, Kongju National University)
Publication Information
Composites Research / v.35, no.5, 2022 , pp. 303-308 More about this Journal
Abstract
PIC (Piecewise Integrated Composite) is a new concept for designing a composite structure with mosaically assigning various types of stacking sequences in order to improve mechanical properties of laminated composites. Also, machine learning is a sub-category of artificial intelligence, that refers to the process by which computers develop the ability to continuously learn from and make predictions based on data, then make adjustments without further programming. In the present study, the tapered box beam type PIC robot arm for carrying and transferring wide and thin LCD display was designed based on the machine learning in order to increase structural stiffness. Essential training data were collected from the reference elements, which were intentionally designated elements among finite element models, during preliminary FE analysis. Additionally, triaxiality values for each finite element were obtained for judging the dominant external loading type, such as tensile, compressive or shear. Training and evaluating machine learning model were conducted using the training data and loading types of elements were predicted in case the level accuracy was fulfilled. Three types of stacking sequences, which were to be known as robust toward specific loading types, were mosaically assigned to the PIC robot arm. Henceforth, the bending type FE analysis was carried out and its result claimed that the PIC robot arm showed increased stiffness compared to conventional uni-stacking sequence type composite robot arm.
Keywords
LCD glass panel display; Box beam; Carbon/epoxy composite material; Machine learning; Piecewise integrated composite;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Mukherjee, D., Gupta, K., Chang, L.H., and Najjaran, H., "A Survey of Robot Learning Strategies for Human-Robot Collaboration in Industrial Settings," Robotics and Computer-Integrated Manufacturing, Vol. 73, 2022, 102231.   DOI
2 Lee, C.S., Lee, D.G., Oh, J.H., and Kim, H.S., "Composite Wrist Blocks for Double Arm Type Robots for Handling Large LCD Glass Panels," Composite Structures, Vol. 57, No. 1-4, 2002, pp. 345-355.   DOI
3 Lee, C.S., and Lee, D.G., "Manufacturing of Composite Sandwich Robot Structures Using the Co-cure Bonding Method," Composite Structures, Vol. 65, No. 3-4, 2004, pp. 307-318.   DOI
4 Bai, Y., Teng, X., and Wierzbicki, T., "On the Application of Stress Triaxiality Formula for Plane Strain Fracture Testing," Journal of Engineering Materials and Technology, Transactions of the ASME, Vol. 131, No. 2, 2009, 0210021.
5 Kim, S.H., and Seo, D.H., "A Study on Occupancy Estimation Method of a Private Room Using IoT Sensor Data Based Decision Tree Algorithm," Journal of the Korean Solar Energy Society, Vol. 37, No. 2, 2017, pp. 23-33.   DOI
6 Bao, Y., and Wierzbicki, T., "On Fracture Locus in the Equivalent Strain and Stress Triaxiality Space," International Journal of Mechanical Sciences, Vol. 46, No. 1, 2004, pp. 81-98.   DOI
7 Vapnik, V., The Nature of Statistical Learning Theory, Springer Pub. Co., Berlin, Germany, 1999.
8 Konjevoda, P., and Stambuk, N., Open-source Tools for Data Mining in Social Science, IntechOpen Limited Pub. Co., London, UK, 2012.
9 Bang, M., Kang, H., Lee, K., Oh, C., Choi, W., Park, G., and Kim, D., "Analysis of Gas Turbine Compressor Degradation Using Random Forest-based Machine Learning Model," Journal of Transactions of the Korean Society of Mechanical Engineers, B, Vol. 46, No. 3, 2022, pp. 605-612.
10 Jeong, C.H., Ham, S.W., Kim, G.S., and Cheon, S.S., "Development of the Piecewisely-integrated Composite Bumper Beam Based on the IIHS Crash Analysis," Composites Research, Vol. 31, No. 1, 2018, pp. 37-41.   DOI
11 Wu, Y., Lai, Y., Zhang, X., and Zhu, Y., "A Finite Beam Element for Analyzing Shear Lag and Shear Deformation Effects in Composite-laminated Box Girders," Computers & Structures, Vol. 82, No. 9-10, 2004, pp. 763-771.   DOI
12 Feraboli, P., Wade, B., Deleo, F., Rassaian, M., Higgins, M., and Byar, A., "LS-DYNA MAT54 Modeling of the Axial Crushing of a Composite Tape Sinusoidal Specimen," Composites Part A: Applied Science and Manufacturing, Vol. 42, 2011, pp.1809-1825.   DOI
13 Oh, J.H., Lee, D.G., and Kim, H.S., "Composite Robot end Effector for Manipulating Large LCD Glass Panels," Composite Structures, Vol. 47, No. 1-4, 1999, pp. 497-506.   DOI
14 Vo, T.P., and Lee, J., "Flexural-torsional Behavior of Thinwalled Closed-section Composite Box Beams," Engineering Structures, Vol. 29, No. 8, 2007, pp. 1774-1782.   DOI
15 Cook R.D., and Young W.C., Advanced Mechanics of Materials, Pearson Prentice Hall Pub, US, 1985.
16 Bicos, A.S., and Springer, G.S., "Design of Composite Boxbeam," Journal of Composite Materials, Vol. 20, 1986, pp. 86-109.   DOI
17 Loughlan, J., and Ata, M., "The Analysis of Carbon Fibre Composite Box Beams Subjected Torsion with Variable Twist," Computer Methods in Applied Mechanics and Engineering, Vol. 152, No. 3- 4, 1998, pp. 373-391.   DOI
18 Ghiasi, H., Fayazbakhsh, K., Pasini, D., and Lessard, L., "Optimum Stacking Sequence Design of Composite Materials Part II: Variable Stiffness Design," Composite Structures, Vol. 93, No. 1, 2010, pp. 1-13.   DOI
19 Ham, S.W., Cheon, S.S., and Jeong, K.Y., "Strength Optimization of Piecewise Integrated Composite Beam Through Machine Learning," Transactions of the Korean Society of Mechanical Engineers A, Vol. 43, No. 8, 2019, pp. 521-528.   DOI
20 Lantz, B., Machine Learning with R, 2nd ed., Packt Pub., UK, 2015.
21 Toray Composite Materials America, Inc., "2510 Prepreg System," https://www.toraycma.com/wp-content/uploads/2510-Prepreg-System.pdf, 2017.
22 Denk, L., Hatta, H., Misawa, A., and Somiya, S., "Shear Fracture of C/C Composites with Variable Stacking Sequence," Carbon, Vol. 39, No. 10, 2001, pp. 1505-1513.   DOI
23 Muller, M.P., Tomlinson, G., Marrie, T.J., Tang, P., McGeer, A., Low, D.E., Detsky, A.S., and Gold, W.L., "Can Routine Laboratory Tests Discriminate between Severe Acute Respiratory Syndrome and other Causes of Community-acquired Pneumonia?" Journal of Clinical Infectious Diseases, Vol. 40, No. 8, 2005, pp. 1079-1086.   DOI
24 Gajowniczek, K., and Zabkowski, T., "ImbTreeAUC: An R Package for Building Classification Trees Using the Area under the ROC Curve (AUC) on Imbalanced Datasets," SoftwareX, Vol. 15, 2021, 100755.   DOI
25 Oh, J.H., Kim, Y.G., and Lee, D.G., "Optimum Bolted Joints for Hybrid Composite Materials", Composite Structures, Vol. 38, No. 1-4, 1997, pp. 329-341.   DOI
26 Kuo, J.L., "Multi-objective Optimal Design of Motion Precision for Fork Robot Arm in LCD Panel Manufacturing Process System," Microelectronics Reliability, Vol. 99, 2019, pp. 19-30.   DOI
27 Ghazavi, A., and Gordaninejad, F., "A Comparison of the Control of a Flexible Robot Arm Constructed from Graphite/epoxy Versus Aluminum," Computers & Structures, Vol. 54, No. 4, 1995, pp. 621-632.   DOI
28 Wu, Y., Wang, X., Su, Q., and Lin, L., "A Solution for Laminated Box Beams under Bending Loads Using the Principle of Complementary Energy," Composite Structures, Vol. 79, No. 3, 2007, pp. 376-380.   DOI
29 Jeong, C.H., Oh, H.S., Ham, S.W., Kim, G.S., Son, S.N., Cho, Y.S., and Cheon, S.S., "Crash Simulation of a Piecewisely-integrated Composite Bumper Beams," Mechanical and Production Engineering, Vol. 6, 2018, pp. 37-40.
30 Qi, Z., Zhang, N., Liu, Y., and Chen, W., "Prediction of Mechanical Properties of Carbon Fiber Based on Cross-scale FEM and Machine Learning," Composite Structures, Vol. 212, 2019, pp. 199-206.
31 Gareth, J., Daniela, W., Trevor, H., and Robert, T., An Introduction to Statistical Learning: with Applications in R, Springer Pub. Co., Berlin, Germany, 2013.
32 Kim, Y.J., Kim, T.W., Yoon, J.S., and Kim, I.H., "Study on Prediction of Similar Typhoons through Neural Network Optimization," Journal of Ocean Engineering and Technology, Vol. 33, No. 5, 2019, pp. 427-434.   DOI
33 Liu, Y., Bi, Q., Yue, X., Wu, J., Yang, B., and Li, Y., "A Review on Tensegrity Structures-based Robots," Mechanism and Machine Theory, Vol. 168, 2022, 104571.   DOI