Education

  • Ph.D., University of California, Berkeley, 1987
  • M.S., Michigan State University, 1984
  • B.S., National Cheng-Kung University, Taiwan, 1980

Research Areas and Descriptors

Background

Dr. Liang began at Tech in 1990 as an Assistant Professor. Prior, he was an Assistant Professor at Oklahoma State University. He was named to the Bryan Professorship in 2005. He was President of Walsin-Lihwa Corporation in 2008-2010.

Research

Dr. Liang's research interests focus on precision manufacturing processes in the context of modeling, monitoring, control, and optimization.  Specifically, his work has been devoted to physics-based analysis and predictive modeling of metal machining and additive manufacturing, with emphasis on materials-driven processing.  It addresses the materials microstructural response to process-induced thermal-mechanical strain, stress, and heat distributions germane to part properties and performance, thus rendering a deeper insight into the manufacturing process physics as well as a scientific foundation to support process planning and optimization for effectiveness and productivity.


Full-field infrared digital thermography in wet machining
Full-field infrared digital
thermography in wet machining
In the field of precision machining, Dr. Liang’s research has centered on predictive modeling of shear straining, thermal kinematics, and material constitutives to apprehend the coupling of thermal and mechanical loadings and the related materials behavior evolutions.  The study has shed lights on the effects of machining and grinding parameters, tool geometries, and lubrication condition on the dynamics of velocity, deformation, stress, and temperature profiles.  It has examined the microstructural aspects of recrystallization, grain growth, texture variation, and phase field change in machining, thus offering a better understanding of the fundamental mechanisms that govern the machined part performance of tolerance, strength, modulus, hardness, and endurance, in addition to process effectiveness attributes of machinability, tool efficiency, and environmental compatibility.
 

Temperature gradients in Ti64 additive manufacturing

Temperature gradients in Ti64 
additive manufacturing

In the field of metal additive manufacturing, Dr. Liang’s work has developed physics-based analytical modeling flanked by computational mechanics of materials to quantify the thermodynamics, heat-transfer, and materials thermo-physical behaviors in powder bed and powder feed processes.  Aiming at a scientific scope and engineering applicability far beyond experimentation and finite element iteration numerics, closed-form analytical solutions have been established by integrating semi-infinite medium solutions with boundary heat transfers for temperature and thermal stress distributions.  The corresponding build residual stress, microstructure, distortion, porosity, and mechanical properties are expressed as explicit functions of process parameters and powder properties, factoring in the effects of scan strategy and powder size statistical distributions.
 

Thermal conductivity profile in Ti64 additive manufacturing

Thermal conductivity profile in Ti64 
additive manufacturing

Much of Dr. Liang’s studies have bonded together materials science and mechanical manufacturing engineering to provide clearer linkages between the manufacturing process condition, material microstructures, and the part properties and functionalities.  Dr. Liang’s research program has been sponsored largely by federal agencies, national laboratories, along with industry sectors of aerospace, automotive, and energy to provide fundamental science and engineering with tangible application relevance.

Distinctions

  • American Society of Mechanical Engineers (ASME)
    • Milton C. Shaw Manufacturing Research Medal, 2016
    • International Manufacturing Science and Engineering Conference  Chair, 2008
    • International Symposium on Flexible Automation Conference Chair, 2007
    • Blackall Machine Tool and Gage Award, 2005
    • Fellow, 2002
    • Manufacturing Engineering Division Executive Committee, 2001-2005
    • Japan-U.S.A. Symposium on Flexible Automation Program Committee Chair, 2000
  • Society of Manufacturing Engineers (SME)
    • Fellow, 2012
    • President of the North American Manufacturing Institution  (NAMRC/SME), 2006
    • Scientific Committee Chair, 2002-2004
    • Robert B. Douglas Outstanding Young Manufacturing Engineer Award,1991
  • Woodruff School Faculty Fellow, 1997-2002
  • Society of Automotive Engineers Ralph R. Teetor Educational Award, 1995

Publications

SECECTED 3-YEAR PUBLICATIONS (revised 1-1-2020)

A. Refereed Journal Papers

  1. Fergani, O., Berto, F., Welo, T., Liang, S. Y., “Analytical Modeling of Residual Stress in Additive Manufacturing,” Fatigue & Fracture of Engineering Materials & Structures (SCI archived), Vol. 40, No. 6, pp.971-978,2017.
  2. Wu, C., Li, B., Liu, Y., Pang, J., and Liang, S. Y., “Strain Rate Sensitive Analysis for Grinding Damage of Brittle Materials,” International Journal of Advanced Manufacturing Technology(SCI archived), March 2017, Vol. 89, Issue 5–8, pp. 2221–2229, 2017.
  3. Pan, Z., Shih, D. S., Tabei, A., Garmestani, H., and Liang, S. Y., “Modeling of Ti-6Al-4V Machining Force Considering Material Microstructure Evolution,” International Journal of Advanced Manufacturing Technology(SCI archived), Vol. 91, Issue 5-8, pp 2673–2680, July 2017.
  4. Pan, Z., Lu, Y. T., Lin, Y. F., Hung, T. P., Hsu, F. C., and Liang, S. Y., “Analytical Model for Force Prediction in Laser-assisted Milling of IN718,” International Journal of Advanced Manufacturing Technology (SCI archived), Vol. 90, Issue 9-12, pp. 2935-2942, June 2017.
  5. Du, Z., Zhang, D., Hou, H., and Liang, S. Y., “Peripheral Milling Force Induced Error Compensation using Analytical Force Model and APDL Deformation Calculation,” International Journal of Advanced Manufacturing Technology(SCI archived), Vol. 88, Issue 9–12, pp 3405–3417, 2017.
  6. Lu, X., Jia, Z., Zhang, H., Liu, S., Feng, Y., and Liang, S. Y., "Tool Point Frequency Response Prediction for Micro-milling by Receptance Coupling Substructure Analysis," ASME Transactions, Journal of Manufacturing Science and Engineering (SCI archived), Vol. 139, No. 7, pp. 1-13, 2017.
  7. Yue, C., Liu, X., and Liang, S. Y., “A Model for Predicting Chatter Stability Considering Contact Characteristics between Milling Cutter and Workpiece,” International Journal of Advanced Manufacturing Technology(SCI archived), Vol. 88, Issue 5-8, pp. 2345-2354, 2017.
  8. Wang, L., and Liang, S. Y., “A Novel Approach of Tool Wear Evaluation,” Transactions of ASME, Journal of Manufacturing Science and Engineering (SCI archived), Vol. 139 (9), doi: 10.1115/1.4037231, 2017.
  9. Lu, Y., Rajora, M., Zou, P., and Liang, S. Y., “Physics-embedded Machine Learning: Case Study with Electrochemical Micro-Machining”, Machines, Special Editionof Precision Manufacturing Processes, Vol. 5(1), pp. 4-14, 2017.
  10. Lu, X. H., Wang, F. R., Jia, Z. Y., Si, L. K., Zhang, C. and Liang., S. Y., “A Modified Analytical Cutting Force Prediction Model under the Tool Flank Wear Effect in Micro-milling Nickel-based Superalloy,” International Journal of Advanced Manufacturing Technology (SCI archived), Vol. 91, N. 9-12, pp. 3709-3716, August 2017.
  11. Fergani, O., Yousfi, M., Ding, Z., Welco, T., and Liang, S. Y., “A Physics-Based Approach to Relate Grinding Process Parameters to Tribological Behavior of Ground Surfaces,” International Journal of Advanced Manufacturing Technology (SCI archived), doi:10.1007/s00170-017-0111-x, 2017.
  12. Lu, X. H., Jia, Z. Y., Zhang, H. X., Liu, S. Q., Feng, Y. X.and Liang, S. Y., “Tool Point Frequency Response Prediction for Micromilling by Receptance Coupling Substructure Analysis,” Journal of Manufacturing Science and Engineering, Transactions of the ASME (SCI archived), Vol. 139, N. 7, pp. 071004-1-071004-13, July 2017.
  13. Pan, Z., Feng, Y., Lu, Y.-T., Lin, Y.-F., Hung, T.-P., Hsu, F.-C., and Liang, S. Y., “Force Modeling of Inconel 718 Laser-assisted End Milling under Recrystallization Effects,” International Journal of Advanced Manufacturing Technology (SCI archived), Vol.92, Issue 5–8, pp.2965–2974, September2017.
  14. Pan, Z., Feng, Y., Lu, Y.-T,, Lin, Y., Hung, T., Hsu, F., Lin, C., Lu, Y.-C., and Liang, S. Y., “Microstructure-Sensitive Flow Stress Modeling for Force Prediction in Laser assisted Milling of Inconel 718,” Manufacturing Review,Vol. 4, No. 6, doi: 10.1051/mfreview/2017005, May 2017.
  15. Wang S., Jia, Z., Lu, X., Zhang, H.,Zhang, C., and Liang, S. Y., "Simultaneous Optimization of Fixture and Cutting Parameters Based on Particle Swarm Optimization Algorithm," Simulation: Transactions of the Society for Modeling and Simulation International(SCI archived), doi: https://doi.org/10.1177/0037549717713850, 2017.
  16. Lu, X. H., Jia, Z. Y., Lu, Y. J., Feng, Y. X.and Liang., S. Y., “Predicting the Surface Hardness of Micro-milled Nickel-base Superalloy Inconel 718,” International Journal of Advanced Manufacturing Technology (SCI archived), Vol. 93, N. 1-4, pp. 1283-1292, October 2017.
  17. Li, Q, Ji, X., and Liang, S. Y., “Incipient Fault Feature Extraction for Rotating Machinery Based on Improved AR-Minimum Entropy Deconvolution Combined with Variational Mode Decomposition Approach,” Entropy (SCI archived), Vol. 19, No. 7, doi: 10.3390/e19070317, 2017.
  18. Li, Q and Liang, S., “Incipient Fault Diagnosis of Rolling Bearing based on Impulse-step Impact Dictionary and Re-weighted Minimizing Nonconvex Penalty Lq Technique,” Entropy (SCI archived), Vol. 19, No. 8, doi: 10.3390/e19080421, 2017.
  19. Lu, X. H., Hu, X. C., Jia, Z. Y., Liu, M. Y., Gao, S., Qu, C. L.and Liang. S. Y., “Model for the Prediction of 3D Surface Topography and Surface Roughness in Micro-milling Inconel 718,” International Journal of Advanced Manufacturing Technology (SCI archived), Vol. 94, N. 5-8, pp. 2043-2056, February 2018.
  20. Wu, C., Li, B., Liu, Y., and Liang, S. Y., “Surface Roughness Modeling for Grinding of Silicon Carbide Ceramics Considering Co-existence of Brittleness and Ductility,” International Journal of Mechanical Sciences (SCI archived), Vol.133, pp. 167-177, November 2017.
  21. Liang, S.Y. and Pan, Z. “Integration of Process Mechanics and Materials Mechanics for Precision Machining,” Solid State Phenomena, V. 261, pp. 9-16, August 2017.
  22. Pan, Z., Feng, Y. and Liang, S.Y., "Material Microstructure Affected Machining: a Review,”Manufacturing Review (EI archived), V. 4, pp. 5, May 2017.
  23. Pan, Z. and Liang, S.Y., "Material Driven Machining Process Modeling,”Manufacturing Letters (SCI archived), V. 14: pp. 1-5, October 2017.
  24. Pan, Z., Shih, D.S., Garmestani, H., Rollett, A.D. and Liang, S.Y., "MTS Model Based Force Prediction for Machining of Ti-6Al-4V,”Journal of Advanced Mechanical Design, Systems, and Manufacturing (SCI archived), V. 11(3), pp. JAMDSM0033, March 2017.
  25. Pan, Z., Shih, D. S., Garmestani, H., Rollett, A., and Liang. S. Y., “MTS Based Force Modeling for Machining of Ti-6Al-4V”, Journal of Advanced Mechanical Design, Systems and Manufacturing (SCI Archived), Vol. 11, No. 3, doi: 10.1299/jamdsm.2017/jamdsm0033, 2017.
  26. Pan, Z., Feng, Y., Ji, X., and Liang, S. Y., “Turning Induced Residual Stress Prediction of AISI 4130 Considering Dynamic Recrystallization,” Machining Science and Technology (SCI archived),Vol 9, pp. 1-15, 2017.
  27. Lu, X., Jia, Z., Wang, F., Wang, S., and Liang, S. Y., " The Effect of Cutting Parameters on Surface Roughness and Surface Roughness Prediction of Curved Surfaces in Micro-Milling Inconel 718, " accepted by International Journal of Machining and Machinability of Materials (EI archived), 2017 (in print).
  28. Li, Q., and Liang, S.Y., “Degradation Trend Prognostics for Rolling Bearing Using Improved R/S Statistic Model and Fractional Brownian Motion Approach,” IEEE Access (SCI archived), V. 6, pp. 21103-21114, December 2017.
  29. Li, Q, Ji, Xia, and Liang, S. Y., “BEMD and Nonconvex Penalty Minimization Lq (q=0.5) Regular SRC for Image Recognition,” accepted by Pattern Recognition and Image Processing (EI Archived), 2017 (in print).
  30. Pan, Z., Feng, Y., Hung, T.-P., Jiang, Y.C., Hsu, F.-C., Wu, L.-T., Lin, C. F., Lu, Y. C., and Liang, S. Y., “Heat Affected Zone in the Laser-Assisted Milling of Inconel 718” Journal of Manufacturing Processes(SCI archived), Vol. 30, p 141 – 147, Vol.30, pp. 141–147, 2017.
  31. Davis, B., Dabrow, D., Ifju, P., Xiao, G., Liang, S. Y., and Huang, Y., “Study of the Shear Strain and Shear Strain Rate Progression during Titanium Machining,” accepted by Transactions of ASME, Journal of Manufacturing Science and Engineering (SCI archived), 2017 (in print).
  32. Lu, X. H., Jia, Z. Y., Wang, H., Feng, Y. X. and Liang. S. Y., “Strain Hardening Properties and the Relationship between Strain and Hardness of Inconel 718,” International Journal of Manufacturing Research (EI archived), Vol. 13, N. 4, pp. 330-341, September 2018.
  33. Davis B., Dabrow, D., Newell, R., Miller, A., Schueller, J. K., Xiao, G., Liang, S. Y., Hartwig, K. T., Ruzycki, N. J., Sohn, Y., and Huang, Y., “Study of Chip Morphology and Chip Formation Mechanism during Machining of ECAE-Processed Titanium,” ASME Transactions, Journal of Manufacturing Science and Engineering (SCI archived), Vol. 140 / 031008-1, March 2018.
  34. Wang, S., Jia, Z., Lu, X., Zhang, H., Zhang, C., Liang, S. Y., “Simultaneous Optimization of Fixture and Cutting Parameters of Thin-Walled Workpieces based on Particle Swarm Optimization Algorithm,” Simulation, Vol. 94, No. 1, pp. 67-76, 2018.
  35. Yue, C., Gao, H., Liu, X., andLiang, S. Y., “Part Functionality Alterations Induced by Changes of Surface Integrity in Metal Milling Process: A Review,” Applied Sciences (SCI archived), Vol. 8, No. 12, pp. 2550-2568, December 2018.
  36. Ning, J., and Liang, S. Y., “Model-driven Determination of Johnson-Cook Material Constants using Temperature and Force Measurements,” International Journal of Advanced Manufacturing Technology (SCI archived), Vol. 97(1-4), pp. 1053-1060, July 2018.
  37. Ning, J., Nguyen, V., Huang, Y., Hartwig, K.T., and Liang, S.Y., “Inverse Determination of Johnson–Cook Model Constants of Ultra-fine-grained Titanium based on Chip Formation Model and Iterative Gradient Search,” International Journal of Advanced Manufacturing Technology (SCI archived), Vol. 99(5-8), pp. 1131-1140, November 2018.
  38. Ning. J., Liang, S. Y., “Prediction of Temperature Distribution in Orthogonal Machining Based on the Mechanics of the Cutting Process using a Constitutive Model,” Journal of Manufacturing and Materials Processing Vol. 2(2), pp. 37, June 2018.
  39. Ning, J., and Liang, S. Y., “Evaluation of an Analytical Model in the Prediction of Machining Temperature of AISI 1045 Steel and AISI 4340 Steel,” Journal of Manufacturing and Materials Processing, Vol. 2(4), pp. 74, October 2018.
  40. Zhao, M., Ji, X., Li, B., & Liang, S. Y., “Forces Prediction in Micro-Grinding Single-Crystal Copper Considering the Crystallographic Orientation,”Manufacturing Review (ESCI Archived), Vol. 5, No, 15, pp. 1884-2020, 2018.
  41. Zhang,Y.,Li, B., Yang, J., and Liang, S. Y., “Modeling and Optimization of Alloy Steel 20CrMnTi Grinding Process Parameters based on Experiments Investigation,” International Journal of Advanced Manufacturing Technology, (SCI archived), Vol. 95, Issue 5-8, pp. 1859-1873, 2018
  42. Lu, X. H., Zhang, H. X., Jia, Z. Y., Feng, Y. X.,and Liang. S. Y., “Cutting Parameters Optimization for MRR under the Constraints of Surface Roughness and Cutter Breakage in Micro-milling Process,” Journal of Mechanical Science and Technology (SCI archived), Vol. 32, N. 7, pp. 3379-3388, July 2018.
  43. Lu, X. H., Jia, Z. Y., Yang, K., Shao, P. L., Ruan, F. X., Feng, Y. X.,and Liang. S. Y., “Analytical Model of Work Hardening and Simulation of the Distribution of Hardening in Micro-milled Nickel-based Superalloy,” International Journal of Advanced Manufacturing Technology (SCI archived), Vol. 97, N. 9-12, pp. 3915-3923, August 2018.
  44. Lu, X. H., Wang, F. R., Jia, Z. Y., Si, L. K.,and Liang. S. Y., “The Flank Wear Prediction in Micro-milling Inconel 718,” Industrial Lubrication and Tribology (SCI archived), Vol. 70, N. 8, pp. 1374-1380, November 2018.
  45. Lu, X. H., Wang, H., Jia, Z. Y., Feng, Y. X.,and Liang. S. Y., “Effects of Cutting Parameters on Temperature and Temperature Prediction in Micro-milling of Inconel718,” International Journal of Nanomanufacturing (EI archived), Vol. 14, N. 4, pp. 377-386, September 2018.
  46. Lu, Y., Li, Q., and Liang, S.Y., “Physics-based Intelligent Prognosis for Rolling Bearing with Fault Feature Extraction,”The International Journal of Advanced Manufacturing Technology (SCI Archived), Vol. 97, pp. 611-620, 2018.
  47. Lu, Y., Xie, R., and Liang, S. Y., “Detection of Weak Fault using Sparse Empirical Wavelet Transform for Cyclic Fault”, The International Journal of Advanced Manufacturing Technology (SCI archived), Vol. 99, pp. 1195-1201, 2018.
  48. Lu, Y., Xie, R., and Liang, S. Y., “Adaptive Online Dictionary Learning for Bearing Fault Diagnosis”, accepted by The International Journal of Advanced Manufacturing Technology(SCI archived), doi:10.1007/s00170-018-2902-0, 2018.
  49. Lu, X. H., Zhang, H. X., Jia, Z. Y., Feng, Y. X.,and Liang. S. Y., “Floor Surface Roughness Model considering Tool Vibration in the Process of Micro-Milling,” International Journal of Advanced Manufacturing Technology (SCI archived), Vol. 94, N. 9-12, pp. 4415-4425, February 2018.
  50. Yue, C., Liu X., Ding Y., and Liang, S. Y., “Off-line Error Compensation in Corner Milling Process,” Proceedings, the Institution of Mechanical Engineers Part B - Journal of Engineering Manufacture (SCI archived), V. 232, pp. 1172-1181, May 2018.
  51. Mirkoohi, E., Bocchini, P., and Liang, S. Y., "An Analytical Modeling for Process Parameter Planning in the Machining of Ti-6Al-4V for Force Specifications Using an Inverse Analysis," The International Journal of Advanced Manufacturing Technology, (SCI archieved), Vol. 98, Issue 9-12, pp. 2347-2355, 2018.
  52. Mirkoohi, E., Ning, J., Bocchini, P., Fergani, O., Chiang, K.-N., and Liang, S. Y., "Thermal Modeling of Temperature Distribution in Metal Additive Manufacturing Considering Effects of build Layers, Latent Heat, and Temperature-Sensitivity of Material Properties," Journal of Manufacturing and Materials Processing, Vol. 2, Issue 3, pp. 63-81, 2018.
  53. Liang, S. Y., Rajora, M., Liu, X., Yue, C., Zou, P., and Wang, L., “Intelligent Manufacturing Systems: A Review,” International Journal of Mechanical Engineering and Robotics Research, Vol. 7, No. 3, pp. 324-330, May 2018.
  54. Zou, P., Rajora, M., and Liang, S. Y., “A New Algorithm based on Evolutionary Computation for Hierarchically Coupled Constraint Optimization: Methodology and Application to Assembly Job-shop Scheduling,” Journal of Scheduling (SCI archived), Vol. 21, No. 5, pp. 545-563, October 2018.
  55. Lu, Y. F., Li, Q., Pan, Z. P., and Liang, S. Y., “Prognosis of Bearing Degradation using Gradient Variable Forgetting Factor RLS Combined with Time Series Model,” IEEE Access (SCI archived), Vol. 6, pp. 10986-10995, March 2018.
  56. Li, Q., and Liang, S.Y., “Bearing Incipient Fault Diagnosis Based upon Maximal Spectral Kurtosis TQWT and Group Sparsity Total Variation Denoising Approach,” Journal of Vibroengineering (EI archived), Vol. 20, No. 3, pp. 1409-1425, May 2018.
  57. Li, Q., and Liang, S. Y., “Multiple Faults Detection for Rotating Machinery Based on Bi-component Sparse Low-rank Matrix Separation Approach,” IEEE Access (SCI archived), Vol. 6, pp. 20242-20254, April 2018.
  58. Li, Q., Hu, W., Peng, E.F., and Liang, S.Y., “Multichannel Signals Reconstruction Based on Tunable Q-factor Wavelet Transform-morphological Component Analysis and Sparse Bayesian Iteration for Rotating Machines,” Entropy (SCI archived), V. 20, No. 4, 263, April 2018.
  59. Li, Q., and Liang, S.Y., “Microstructure Images Restoration of Metallic Materials Based upon KSVD and Smoothing Penalty Sparse Representation Approach,” Materials (SCI archived), V. 11, No. 4, 637, April 2018.
  60. Li, Q., and Liang, S. Y., “An Improved Sparse Regularization Method for Weak Fault Diagnosis of Rotating Machinery based upon Acceleration Signals,” IEEE Sensors Journal (SCI archived), Vol.18, No.16, pp. 6693-6705, June 2018.
  61. Li, Q., and Liang, S. Y., “Intelligent Prognostics of Degradation Trajectories for Rotating Machinery based on Asymmetric Penalty Sparse Decomposition Model,” Symmetry (SCI archived), Vol. 10, No. 6, 214, June 2018.
  62. Li, Q., and Liang, S.Y., “Weak Fault Detection for Gearbox Based on Majorization–minimization and Asymmetric Nonconvex Penalty Regularization Approach,” Symmetry (SCI archived), V. 10, No. 7, 243, June 2018.
  63. Li, Q., and Liang, S.Y., “Degradation Trend Prediction for Rotating Machinery Using Long-range Dependence and Particle Filter Approach,” Algorithms (EI archived), Vol. 11, No. 7, 89, June 2018.
  64. Li, Q., and Liang, S.Y., “Incipient Fault Diagnosis for Large Reducer Taper Roller Bearings Based on Non-convex Penalty Regularization Sparse Low-rank Matrix Approach,” Journal of Mechanical Engineering (EI archived), Vol.54, No. 23, pp. 102-111, December 2018.
  65. Li, Q., and Ji, X., Liang, S.Y., “Bi-dimensional Empirical Mode Decomposition and Nonconvex Penalty Minimization Lq (q = 0.5) Regular Sparse Representation-based Classification for Image Recognition,” Pattern Recognition and Image Analysis (EI archived), V. 28, No. 1, pp. 59-70, March 2018.
  66. Li, Q., and Liang, S.Y., “Weak Fault Detection of Tapered Rolling Bearing Based on Penalty Regularization Approach,” Algorithms (EI archived), Vol. 11, No.11, 184, November 2018.
  67. Ji X., Li B. Z., and Liang S. Y., “Analysis of Thermal and Mechanical Effectson Residual Stress in Minimum Quantity Lubrication (MQL) Machining,” Journal of Mechanics (SCI archived), V. 34, pp. 41-46, February 2018.
  68. Feng, Y., Pan, Z. and Liang, S.Y., "Temperature Prediction in Inconel 718 Milling with Microstructure Evolution,”The International Journal of Advanced Manufacturing Technology (SCI archived), V. 95(9-12), pp. 4607-4621, April 2018.
  69. Pan, Z., Liang, S.Y. and Garmestani, H., "Finite Element Simulation of Residual Stress in Machining of Ti-6Al-4V with a Microstructural Consideration,”Proceedings, the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture (SCI archived), doi: 10.1177/0954405418769927, 2018.
  70. Pan, Z., Liang, S.Y., Garmestani, H., Shih, D. and Hoar, E., "Residual Stress Prediction Based on MTS Model During Machining of Ti-6Al-4V,”Proceedings, the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science (SCI archived), doi: 10.1177/0954406218805122, 2018.
  71. Pan, Z., Tabei, A., Shih, D.S., Garmestani, H. and Liang, S.Y., " The Effects of Dynamic Evolution of Microstructure on Machining Forces,”Proceedings, the institution of mechanical engineers, Part B: Journal of Engineering Manufacture (SCI archived), V. 232(14): pp. 2677-2681, December 2018.
  72. Liu, X., Liu, Q., Yue, C., Wang, L., and Liang. S. Y., “Intelligent Machining Technology in Cutting Process”, Journal of Mechanical Engineering (In Chinese) (EI archived), V. 54, pp. 45-61, August 2018.
  73. Ding, Z, Jiang, X, Guo, M, and Liang, S. Y., “Investigation of the Grinding Temperature and Energy Partition during Cylindrical Grinding,”International Journal of Advanced Manufacturing Technology (SCI archived), V. 97, pp. 1767-1778, July 2018.
  74. Feng, Y., Lu, Y.-T., Lin, Y.-F., Hung, T.-P., Hsu, F.-C., Lin, C.-F., Lu, Y-C., and Liang, S. L., “Inverse Analysis of the Cutting Force in Laser-assisted Milling on Inconel 718,” International Journal of Advanced Manufacturing Technology (SCI archived), V. 96, pp. 905-914, April 2018.
  75. Feng, Y., Hung, T.-P., Lu, Y.-T., Lin, Y.-F., Hsu, F.-C., Lin, C.-F., Lu, Y.-C., Lu, X., and Liang, S. Y., “Inverse Analysis of Inconel 718 Laser-Assisted Milling to Achieve Machined Surface Roughness,” International Journal of Precision Engineering and Manufacturing (SCI archived), Vol. 19, pp. 1611-1618, November 2018.
  76. Lu, X. H., Wang, H., Jia, Z. Y., Feng, Y. X., and Liang. S. Y., “Coupled Thermal and Mechanical Analyses of Micro-milling Inconel 718,” Proceedings, the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture (SCI archived), Vol. 233, N. 4, pp. 1112-1126, March 2019.
  77. Lu, Y., Xie, R., and Liang, S. Y., “Bearing Fault Diagnosis with Nonlinear Adaptive Dictionary Learning”, The International Journal of Advanced Manufacturing Technology. (SCI archived), Vol. 102, pp. 4227-4239, 2019.
  78. Yue, C., Gao, H., Liu, X., Liang, S. Y., and Wang, L., “A Review of Chatter Vibration Research in Milling,” Chinese Journal of Aeronautics (SCI archived), Vol. 32, Issue 2, pp. 215-242, 2019.
  79. Zhao, M., Ji, X., Li, B., & Liang, S. Y., “Effect of Crystallographic Orientation on the Hardness of Polycrystalline Materials AA7075,” Proceedings, the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science (SCI Archived), Vol. 233, No, 9, pp. 3182-3192, 2019.
  80. Wu, C., Pang, J., Li B. and Liang, S.Y. “High Speed Grinding of HIP-SiC Ceramics on Transformation of Microscopic Features,” International Journal of Advanced Manufacturing Technology (SCI Archived), Vol. 102, pp. 1913–1921, 2019.
  81. Feng, Y., Hung, T.-P., Lu, Y.-T., Lin, Y.-F., Hsu, F.-C., Lin, C.-F., Lu, Y.-C., and Liang, S. Y., “Inverse Analysis of the Residual Stress in Laser-assisted Milling,” International Journal of Advanced Manufacturing Technology (SCI archived), doi: 10.1007/s00170-019-04794-9, 2019.
  82. Ning, J., Mirkoohi, E., Dong, Y., Sievers, D. E., Garmestani, H., and Liang, S. Y., "Analytical Modeling of 3D Temperature Distribution in Selective Laser Melting of Ti-6Al-4V Considering Part Boundary Conditions," Journal of Manufacturing Processes (SCI archieved), Vo. 44, pp. 319-326, 2019.
  83. Ning, J., Nguyen, V. and Liang, S. Y., “Analytical Modeling of Machining Forces of Ultra-fine-grained Titanium,” The International Journal of Advanced Manufacturing Technology (SCI archived), Vol. 101(1-4), pp. 627-636, March 2019.
  84. Feng, Y., Hung, T.-P., Lu, Y.-T., Lin, Y.-F., Hsu, F.-C., Lin, C.-F., Lu, Y.-C., and Liang, S. Y., “Analytical Prediction of Temperature in Laser-assisted Milling with Laser Preheating and Machining Effects,” International Journal of Advanced Manufacturing Technology (SCI archived), Vol. 100, pp. 3185-3195, February 2019.
  85. Yue, C., Hao,X.,Chen,Z.,Liu,X.,Liang,S. Y., and Wang, L., “Research on TANH Material Constitutive Model Based on Analytical Method,” accepted by Journal of Mechanical Engineering (In Chinese) (EI archived), 2019 (in print).
  86. Li, Q., and Liang, S. Y., “Weak Crack Detection for Gearbox using Sparse Denoising and Decomposition Method,” IEEE Sensors Journal (SCI archived), Vol. 19, No. 6, pp. 2243-2253, March 2019.
  87. Feng, Y., Hung, T.-P., Lu, Y.-T., Lin, Y.-F., Hsu, F.-C., Lin, C.-F., Lu, Y.-C., and Liang, S. Y., “Residual Stress Prediction in Laser-assisted Milling considering Recrystallization Effects,” International Journal of Advanced Manufacturing Technology (SCI archived), Vol. 102, pp. 393-402, May 2019.
  88. Lu, Y., Xie, R., and Liang, S. Y., “Extraction of Weak Fault using Combined Dual-Tree Wavelet and Improved MCA for Rolling Bearings”, The International Journal of Advanced Manufacturing Technology (SCI archived), Vol. 104, Issue 5-8, pp. 2389-2400, 2019.
  89. Ning, J., Sievers, D.E., Garmestani, H. and Liang, S. Y., ”Analytical Modeling of In-Process Temperature in Powder Bed Additive Manufacturing Considering Laser Power Absorption, Latent Heat, Scanning Strategy, and Powder Packing,” Materials (SCI archived), Vol.12(5), pp. 808, March 2019.
  90. Lu, Y., Xie, R., and Liang, S. Y., “CEEMD Assisted Bearing Degradation Assessment using Tight Clustering”, The International Journal of Advanced Manufacturing Technology (SCI archived), Vol. 104, pp.1259-1267, 2019.
  91. Zhao M, Ji X, Liang S Y., “Force Prediction in Micro-Grinding Maraging Steel 3J33b Considering the Crystallographic Orientation and Phase Transformation,” International Journal of Advanced Manufacturing Technology. (SCI archived), Vol. 103, pp. 2821–2836, April 2019.
  92. Li, Q., Ji, X., Yang, J. G., and Liang, S. Y., “Stability Analysis for SiC Grinding Based Upon Harmonic Wavelet and Lipschitz Exponent,” Machining Science and Technology (SCI archived), Vol. 23, No.5, pp. 669-687, August 2019.
  93. Ning, J. and Liang, S. Y., “Predictive Modeling of Machining Temperatures with Force–Temperature Correlation using Cutting Mechanics and Constitutive Relation,” Materials (SCI archived), Vol. 12(2), pp. 284, January 2019.
  94. Li, Q., Hu, W., Peng, E. F., and Liang, S. Y., “Weak Fault Diagnosis of Rotating Machinery based on Augmented Huber Regularized Sparse Low-Rank-Matrix Approach,” Proceedings, the CSEE (EI archived), Vol. 39, No.15, pp. 4579-4588, August, 2019.
  95. Lu, Y., Xie, R., and Liang, S. Y., “Bayesian Optimized Deep Convolutional Network for Electro-Chemical Drilling Process”, Journal of Manufacturing and Materials Processing, 3(3), 57, doi: 10.3390/jmmp3030057, 2019.
  96. Du, J., Yue, C., Liu, X., Liang, S. Y., Wang, L., Gao, H., and Liu, H., “Transient Temperature Field Model of Wear Land on the Flank of End Mills: a Focus on Time-varying Heat Intensity and Time-varying Heat Distribution Ratio,” Applied Sciences (SCI archived), V. 9, No. 8, pp. 1698-1724, April 2019.
  97. Ning, J., Sievers, D.E., Garmestani, H., and Liang, S. Y., “Analytical Modeling of Transient Temperature in Powder Feed Metal Additive Manufacturing during Heating and Cooling Stages,” Applied Physics A, (SCI archived), Vol. 125(8), pp. 496, July 2019.
  98. Feng, Y., Hung, T.-P., Lu, Y.-T., Lin, Y.-F., Hsu, F.-C., Lin, C.-F., Lu, Y.-C., and Liang, S. Y., “Inverse Analysis of the Tool Life in Laser-assisted Milling,” International Journal of Advanced Manufacturing Technology (SCI archived), Vol.103, pp. 1947-1958, August 2019.
  99. Ning, J., Sievers, D. E., Garmestani, H. ,and Liang, S. Y., “Analytical Modeling of in-process Temperature in Powder Feed Metal Additive Manufacturing considering Heat Transfer Boundary Condition,” International Journal of Precision Engineering and Manufacturing-Green Technology (SCI archived), doi: 10.1007/s40684-019-00164-8, 2019.
  100. Mahdavi, M., Hoar, E., Sievers, D. E., Chong, Y., Tsuji, N., Liang, S., Y., and Garmestani, H. “Statistical Representation of the Microstructure and Strength for a Two-phase Ti–6Al–4V,” Materials Science and Engineering: A (SCI archived), 759, pp. 313-319, 2019.
  101. Chou, P.H., Liang, S. Y., Chiang, K. N., “Reliability Assessment of Wafer Level Package using Artificial Neural Network Regressional Model,” Journal of Mechanics (SCI archived), 2019.
  102. Feng, Y., Hung, T.-P., Lu, Y.-T., Lin, Y.-F., Hsu, F.-C., Lin, C.-F., Lu, Y.-C., Lu, X., and Liang, S. Y., “Surface Roughness Modeling in Laser-assisted End Milling of Inconel 718,” Machining Science and Technology (SCI archived), Vol. 23 (4), pp. 650-668, 2019.
  103. Ning, J., Sievers, D.E., Garmestani, H., and Liang, S. Y., “Analytical Thermal Modeling of Metal Additive Manufacturing by Heat Sink Solution,” Materials (SCI archived), Vol. 12(16), pp. 2568, August 2019.
  104. Lu, X. H., Xv Y. C. , Wang, W. T., Zhou, Y., and Liang. S. Y., “Experimental Study of the Effect of Light Source Spot Size on Measure Error of PSD,” International Journal of Manufacturing Research (EI archived). Vol. 14, N. 1, pp. 1-14, January 2019.
  105. Mirkoohi, E., Seivers, D. E., Garmestani, H., and Liang, S. Y., "Heat Source Modeling in Selective Laser Melting, " Materials (SCI archieved), Vol. 12, Issue 13, pp. 2052-2069, 2019.
  106. Ning, J., Wang, W., Zamorano, B., and Liang, S. Y., “Analytical Modeling of Lack-of-fusion Porosity in Metal Additive Manufacturing,” Applied Physics A (SCI archived), Vol. 125(11), pp. 797, November 2019.
  107. Yue, C., Chen, Z., Liang, S. Y., Gao, H., and Liu, H., “Modeling Machining Errors for Thin-walled Parts according to Chip Thickness,” International Journal of Advanced Manufacturing Technology (SCI archived), Vol. 103, No. 1-4, pp. 91-100, July 2019.
  108. Lu, X. H., Jia, Z. Y., Wang, X. X., Liu, Y. B., Liu M. Y., Feng, Y. X. and Liang. S. Y., “Measurement and Prediction of Vibration Displacement in Micro-milling of Nickel-based Superalloy,” Measurement: Journal of the International Measurement Confederation (SCI archived), Vol. 145, pp. 254-263, October 2019.
  109. Zou, P., Rajora, M., and Liang, S. Y., “Multimodal Optimization of Job-Shop Scheduling Problems using a Clustering Generic-Algorithm Based Approach,” International Journal of Industrial Engineering: Theory, Applications, and Practice (SCI indexed), Vol 26, No. 5, pp. 651-662, October 2019.
  110. Zhao M, Ji X, Liang, S Y., “Influence of AA7075 Crystallographic Orientation on Micro-Grinding Force,” Proceedings, the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture (SCI archived),Vol. 233, No, 8, pp.1831–1843, 2019.
  111. Tabei, A., Mirkoohi, E., Garmestani, H., and Liang, S. Y., "Modeling of Texture Development in Additive Manufacturing of Ni-Based Superalloys," The International Journal of Advanced Manufacturing Technology (SCI archieved), Vol. 103, Issue 1-4, pp. 1057-1066, 2019.
  112. Zhao M, Ji X, Liang S Y., “Micro-Grinding Temperature Prediction Considering the Effect of CrystalloTemperature Field inGraphic Orientation and the Strain Induced by Phase Transformation,” International Journal of Precision Engineering and Manufacturing (SCI archived), Vol. 20, pp. 1861-1876, August 2019.
  113. Mirkoohi, E., Bocchini, P., and Liang, S. Y., "Inverse Analysis of Residual Stress in Orthogonal Cutting," Journal of Manufacturing Processes, (SCI archieved), Vol. 38, pp. 462-471, 2019.
  114. Lu, X. H., Wang F. R., Xue, L., Feng, Y. X. and Liang. S. Y., “ Investigation of Material Removal Rate and Surface Roughness using Multi-objective Optimization for Micro-milling of Inconel 718,” Industrial Lubrication and Tribology (SCI archived), Vol. 71, N. 6, pp. 787-794, August 2019.
  115. Zhao, M., Ji, X. & Liang, S. Y., “Micro-grinding Temperature Prediction considering the Effects of Crystallographic Orientation,” Manufacturing Review(ESCI archived), Vol. 6, No. 22, pp. 1-11, 2019.
  116. Li, Q., Zuo, M. J., and Liang, S. Y., “Prognosis of Bearing Degeneration using Adaptive Quaternion Least Mean Biquadrate under Framework of Hypercomplex Data,” accepted by IEEE Sensors Journal (SCI archived), doi: 10.1109/JSEN.2019.2954054, 2019.
  117. Mahdavi, M., Hoar, E., Sievers, D. E., Liang, S. Y., and Garmestani, H. “Inverse Modeling of Inelastic Properties of a Two-phase Microstructure,” Engineering Research Express, 1(1), 015026, 2019.
  118. Li, Q., and Liang, S. Y., “Noise Suppression for Electronic Microstructure Images using Variational Mode Decomposition and Sparse SURE Algorithm,” accepted by Journal of Harbin Institute of Technology (EI archived), 2019 (in print).
  119. Lu, X. H., Xue, L., Ruan, F. X., Yang K. and Liang. S. Y., “Prediction Model of the Surface Roughness of Micro-milling Single Crystal Copper,” Journal of Mechanical Science and Technology (SCI archived), Vol. 33, N. 11, pp 5369-5374, November 2019.
  120. Mirkoohi, E., Bocchini, P., and Liang, S. Y., "Analytical Temperature Predictive Modeling and Non-Linear Optimization in Machining," The International Journal of Advanced Manufacturing Technology, (SCI archieved), Vol. 102, Issue 5-8, pp. 1557-1566, 2019.
  121. Li, Q., Zuo, M. J., and Liang, S. Y., “A New Method for Long-Distance Data Reconstruction in Big Data Environment,” accepted by IEEE Transactions on Reliability (SCI archived), doi: 10.1109/TR.2019.2954969, 2019.
  122. Ding, Z., Sun, G., Jiang, X., Guo, M., and Liang, S.Y., “Predictive Modeling of Microgrinding Force incorporating Phase Transformation Effects”, Journal of Manufacturing Science and Engineering-Transactions of the ASME (SCI archived), Vol. 141, No. 8, doi:10.1115/1.4043839, 2019.
  123. Feng, Y., Hsu, F.-C., Lu, Y.-T., Lin, Y.-F., Lin, C.-T., Lin, C.-F., Lu, Y.-C., and Liang, S. Y., “Residual Stress Prediction in Ultrasonic Vibration–assisted Milling,” International Journal of Advanced Manufacturing Technology (SCI archived), Vol. 104, pp. 2579-2592, October 2019.
  124. Lu, X. H., Wang, Y. Q., Li, J., Zhou, Y., Ren, Z. J. and Liang. S. Y., “Three-dimensional Coordinate Measurement Algorithm by Optimizing BP Neural Network based on GA,” Engineering Computations (SCI archived), Vol. 36, N. 6, pp. 2066-2083, July 2019.
  125. Mirkoohi, E., Sievers, D. E., Garmestani, H., Chiang, K., and Liang, S. Y., "Three-Dimensional Semi-Elliptical Modeling of Melt Pool Geometry Considering Hatch Spacing and Time Spacing in Metal Additive Manufacturing," Journal of Manufacturing Processes (SCI archieved), Vol. 45, pp. 532-543, 2019.
  126. Lu, X. H., Jia, Z. Y., Liu, S. Q., Yang, K., Feng, Y. X. and Liang. S. Y., “ Chatter Stability of Micro-milling by Considering the Centrifugal Force and Gyroscopic Effect of the Spindle,” Journal of Manufacturing Science and Engineering, Transactions of the ASME (SCI archived), Vol. 141, N. 11, November 2019.
  127. Lu, Y., Pan, Z., Bocchini, P., Garmestani, H., Liang, S.Y., "Grain Size Sensitive MTS Model for Ti-6Al-4V Machining Force and Residual Stress Prediction", The International Journal of Advanced Manufacturing Technology (SCI indexed) Vol. 102, pp. 2173–2181, January 2019.
  128. Li, F., Ning, J., and Liang, S. Y., “Analytical Modeling of the Temperature using Uniform Moving Heat Source in Planar Induction Heating Process,” Applied Sciences-Basel (SCI archived), doi: 10.3390/app9071445 9(7), 1445, 2019.
  129. Pan, Z., Shih, D.S., Garmestani, H. and Liang, S.Y., "Residual Stress Prediction for Turning of Ti-6Al-4V Considering the Microstructure Evolution,”Proceedings, the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture (SCI archived), V. 223(1), pp. 109-117, January 2019.
  130. Chou, P. H., Liang, S. Y., and Chiang, K.-N., “Reliability Assessment of Wafer level Package using Artificial Neural Network Regression Model,” accepted by Journal of Mechanics (SCI archived), doi: https://doi.org/10.1017/jmech.2019.20, 2019.
  131. Lu, X. H., Jia, Z. Y., Wang, H., Feng, Y. X. and Liang. S. Y., “The Effect of Cutting Parameters on Micro-hardness and the Prediction of Vickers Hardness Based on a Response Surface Methodology for Micro-milling Inconel 718,” Measurement: Journal of the International Measurement Confederation (SCI archived), Vol. 140, pp. 56-62, July 2019.
  132. Ning, J., Nguyen, V., Huang, Y., Hartwig, K. T., and Liang, S. Y., “Constitutive Modeling of Ultra-fine-grained Titanium Flow Stress for Machining Temperature Prediction,” Bio-design and Manufacturing (SCI archived), Vol. 2(3), pp.153-160, August 2019.
  133. Wu, C., Guo, W., Wu, Z., Li K., Li, B. and Liang, S. Y., “High Speed Toughening-based Ceramics Grinding Mechanism for Quality and Efficiency,” Journal of Advanced Mechanical Design, Systems, and Manufacturing (SCI archived), 13 (3), doi: 10.1299/jamdsm.2019jamdsm0053, 2019.
  134. Li, F., Ning, J., Wang, T., and Liang, S. Y., “Analytical Modeling and Sensitivity Analysis of the Temperature Distribution in the Planar Scanning Induction Heating based on 2D Moving Heat Source,” Journal of Mechanical Science and Technology (SCI archived), Vol. 33, Issue 10, pp. 5093-5102, 2019.
  135. Yang, C. C., Su, Y. F., Liang, S. Y., and Chiang, K.-N., “Simulation of Wire Bonding Process Using Explicit FEM with ALE Remeshing Technology,” accepted by Journal of Mechanics (SCI archived), doi: https://doi.org/10.1017/jmech.2019.25, 2019.
  136. Ning, J. and Liang, S. Y., “A Comparative Study of Analytical Thermal Models to Predict the Orthogonal Cutting Temperature of AISI 1045 Steel,” The International Journal of Advanced Manufacturing Technology (SCI archived), Vol. 102(9-12), pp.3109-3119, February 2019.
  137. Feng, Y., Hung, T.-P., Lu, Y.-T., Lin, Y.-F., Hsu, F.-C., Lin, C.-F., Lu, Y.-C., and Liang, S. Y., “Flank Tool Wear Prediction of Laser-assisted Milling,” Journal of Manufacturing Processes (SCI archived), Vol. 43, pp. 292-299, July 2019.

 

B. Referred Conference Papers

  1. Fergani, O., Elmansori, M., and Liang, S. Y., “Additive Manufacturing Process Thermomechanical Signature and Residual Stress: an Analytical Approach,” Proceedings, the ASME 12th International Manufacturing Science and Engineering Conference (EI archived), June 4-8, 2017, Los Angeles, 2017.
  2. Pan, Z., Feng, Y., Ji, X., and Liang, S. Y., “Turning Force Prediction of AISI 4130 Considering Dynamic Recrystallization,” Proceedings, the ASME 12th International Manufacturing Science and Engineering Conference(EI archived), June 4-8, 2017, Los Angeles, 2017.
  3. Lu, X. H., Zhang, H. X., Jia, Z. Y., Feng, Y. X., and Liang, S. Y., “A New Method for the Prediction of Micro-milling Tool Breakage,” Proceedings, 12th International Manufacturing Science and Engineering Conference, (MSEC2017), (EI archived), 2017,Los Angeles, June 4-8, 2017.
  4. Lu, X. H., Wang, H., Jia, Z. Y., Si, L. K., and Liang, S. Y., “Effects of Tool Nose Corner Radius & Main Cutting-edge Radius on Cutting Temperature in Micro-milling Inconel 718 Process,” Proceedings, 12th International Manufacturing Science and Engineering Conference (MSEC2017), (EI archived), 2017, Los Angeles, June 4-8, 2017.
  5. Li, Q., Ji, X., and Liang, S. Y., “Pattern Recognition of Tool Wear in High-speed Milling based upon Nonlinear Analysis,” Proceedings, IEEE International Conference on Electronics Information and Emergency Communication (ICEIEC) (EI archived), Shenzhen, Jul 21-23, 2017.
  6. Ayjhan, B., Kwan, C., and Liang, S. Y., “A Portable Prognostic System for Bearing Monitoring,” Proceedings, 14th International Symposium on Neural Networks (ISNN), pp. 511-515, Sapporo, Japan, June 21-23, 2017.
  7. Wu, C. J.,Li, B. Z.,Yang, J. G., and Liang, S. Y. “Comparison of Machining Temperature in High Speed Grinding of Metallic Materials and Brittle Materials.” MATEC Web of Conferences (EI archived), Vol. 114, July 10, 2017, 2017 Proceedings, International Conference on Mechanical, Material and Aerospace Engineering, 2MAE 2017.
  8. Li, Q., and Liang, S. Y., “Incipient Multi-fault Diagnosis of Rolling Bearing Using Improved TQWT and Sparse Representation Approach,” Proceedings, IEEE International Conference on Signal and Image Processing, (ICSIP) (EI archived), 2017, Singapore, August 4-6, 2017.
  9. Liang, S. Y. and Pan, Z., “Process and Microstructure in Materials-Affected Manufacturing,” Proceedings, 5th International Conference on Advanced Manufacturing Engineering and Technologies(NEWTECH), Belgrade, Serbia, June 5-9, 2017.
  10. Liang, S. Y. and Pan, Z., “Integration of Process Mechanics and Materials Mechanics for Precision Machining”, Proceedings, 9th International Congress on Precision Machining (ICPM), Athens, Greece, September 6-9, 2017.
  11. Li, Q., Ji, X., and Liang, S. Y., “Physical Mechanism of Material Microstructure Evolution based upon BEMD and Image Multi-scale Entropy during Heat Treatment Process,” Proceedings, IEEE Information Technology, Networking, Electronic and Automation Control Conference, (ITNEC) (EI archived), pp. 1129-1133, Chengdu, December 12-15, 2017.
  12. Lu, Y. F., Li, Q., and Liang, S. Y., “Adaptive Prognosis of Bearing Degradation Trend based on Wavelet Decomposition assisted ARMA Model,” Proceedings, IEEE Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) (EI archived), Chengdu, December 12-15, 2017.
  13. Zou, P., Rajora, M., Ma, M., Chen, H., Wu, W., and Liang, S. Y., “Electrochemical Micro-Machining Process Parameter Optimization Using a Neural Network-Genetic Algorithm Based Approach,” Proceedings, the International Conference on Manufacturing Technologies (ICMT) (EI archived), San Diego, CA, January 19-21, 2017.
  14. Rajora, M., Zou, P., Xu, W., Jin, L., Chen, W., & Liang, S. Y., “Prediction and Optimization of Key Performance Indicators in the Production of Stator Core Using a GA-NN Approach,” Proceedings, 4th International Conference on Mechanical, Materials and Manufacturing (ICMMM) (EI archived), Atlanta, GA, October 25-27, 2017.
  15. Ayhan, B., Kwan, C., and Liang, S. Y., “An Accurate Remaining Life Prediction Algorithmfor Bearings,” Proceedings, IEEE International Conference on Prognostics and Health Management (ICPHM), Seattle, WA, USA, June 11-13, 2018.
  16. Ayhan, B., Kwan, C., and Liang, S. Y., “High Performance Remaining Life PredictionAlgorithms for Gearbox,” Proceedings, IEEE International Conference on Prognostics and Health Management (ICPHM), Seattle, WA, USA, June 11-13, 2018.
  17. Pan, Z., Feng, Y., Liang, S.Y., “Microstructural Sensitive Flow Stress Modeling of Ti-6Al-4V in the Machining Process,” Proceedings, ASME International Manufacturing Science and Engineering Conference MSEC 2018 (EI archived), College Station, Texas, July 2018.
  18. Lu, X., Jia, Z., Wang, F., Wang, S., and Liang, S. Y., " The Effect of Cutting Parameters on Surface Roughness and Surface Roughness Prediction of Curved Surfaces in Micro-Milling Inconel 718, " Proceedings, ASME International Manufacturing Science and Engineering Conference MSEC 2018 (EI archived), College Station, Texas, July 2018.
  19. Liu, X., Li, H., Li, M., Liang, S. Y., “Research on the Intelligent Tool Changer with Decision Tree Algorithm in Processing,” Proceedings, International Symposium of Computation Numerical Control Machining, 2018. Xi’an, China, June 3-5, 2018.
  20. Liu, X., Gao, Hainkng, Yue, C., Wang, L., Liang, S. Y., “Analytical Prediction of Part Dynamics and Process Damping,” Proceedings, 51st CIRP Conference on Manufacturing Systems (EI archived), Stockholm, Sweden, May 16-18, 2018.
  21. Feng, Y., Pan, Z., Lu, X. and Liang, S.Y. "Analytical and Numerical Predictions of Machining-Induced Residual Stress in Milling of Inconel 718 Considering Dynamic Recrystallization", ASME 2018 13th International Manufacturing Science and Engineering Conference (EI archived), 2018, College Station, June 18-22, 2018.
  22. Feng, Y., Hung, T.-P., Lu, Y.-T., Lin, Y.-F., Hsu, F.-C., Lin, C.-F., Lu, Y.-C., and Liang, S. Y., “Prediction of Surface Hardness in Laser-assisted Milling,” Proceedings, ASME 14th International Manufacturing Science and Engineering Conference (MSEC 2019) (EI archived), 2019, USA, June 10–14, 2019.
  23. Liang, S. Y., Ning, J., and Mirkoohi, E., “A Closed-form Solution for Temperature Prediction in Selective Laser Melting Considering Boundary Condition” 3rd International Conference on Advanced Manufacturing and Materials (ICAMM 2019) (EI archived), 2019, Beijing, May 29-31, 2019.
  24. Liang, S. Y., Lu, Y., and Xie, R., “Intelligent Diagnosis and Signal Processing of Vibration Signal from Rotating Machinery”, Proceedings, 1st International Conference on Advances in Signal Processing and Artificial Intelligence (ASPAI 2019), 2019, Barcelona, Spain, March 20-22, 2019.
  25. Lu, X. H., Wang, F. R., Yang K., Feng, Y. X., and Liang, S. Y., “An Indirect Method for the Measurement of Micro-milling Forces,” Proceedings of14th International Manufacturing Science and Engineering Conference (MSEC 2019), (EI archived), 2019, Erie, PA, June 10-14, 2019.
  26. Mirkoohi, E., Sievers, D. E., and Liang, S. Y.,” Effect of Time Spacing and Hatching Space on Thermal Material Properties and Melt Pool Geometry in Additive Manufacturing of S316L,” Proceedings, ASME 14th International Manufacturing Science and Engineering Conference, MSEC2019 (EI archived), Erie, PA, June 10-14, 2019.

 

C. Submitted Journal Papers

  1. Li, Q., Yang, J., and Liang, S. Y., “SiC Grinding Stability Analysis based upon Harmonic Wavelet and Lipschitz Exponent Methodology,” submitted to Machining Science and Technology (SCI archived), under review
  2. Zou, P.,Rajora, M., and Liang, S. Y., “A Two-stage Filter Split-Optimization Approach for Obtaining Multiple Solutions with Identical Objective Value,” submitted to Applied Artificial Intelligence (SCI archived), under review.
  3. Lu, X. H., Jia, Z., Wang, Z., Zou, Y., and Liang, S. Y., "Comprehensive Laboratory Testing and Performance Evaluation of Chain-type Tool Magazine and ATC," submitted to International Journal of Industrial and Systems Engineering (EI archived), under review.
  4. Jiang, X., Zhang, Z., Ding, D., Fergani, O., and Liang. S. Y., “Tool Overlaps Effect on Redistributed Residual Stress and Distortion Produced by the Milling Thin-walled Part,” submitted to International Journal of Advanced Manufacturing Technology (SCI archived), under review.
  5. Zou, P., Rajora, M., and Liang, S. Y., “Obtaining Multiple Process Parameter Combinations using a Supervised Clustering-Optimization Approach,” submitted to International Journal of Industrial Engineering: Theory, Applications, and Practice (SCI archived), under review.
  6. Pan, Z., Shih, D. S., Rollett, A., Garmestani, H., and Liang, S. Y., “Microstructure Effects on Residual Stress Generation during Machining of Ti-6Al-4V”, submitted to Journal of Mechanical Engineering Science (SCI archived), under review.
  7. Kuttolamadom, M. A., Niaki, F. A., Huang, Y., Kurfess, T., Liang, S., Mears, L., Ozel, T., Ulutan, D., and Wang, J., “State-of-the-Art Review on Machining Tool Wear Mechanisms and Modeling,” submitted to Machining Science and Technology (SCI archived), under review.
  8. Pan, Z.,Feng, Y., and Liang, S. Y., “FEA for Machining Induced Residual Stress Prediction of Ti-6Al-4V with A Microstructural Consideration”, submitted to Journal of Engineering Manufacture (SCI archived), under review.
  9. Rajora, M., Zou, P., and Liang, S. Y., “Multimodal Optimization of Permutation Flow-Shop Scheduling Problems using a Clustering Genetic-Algorithm Based Approach,” submitted to International Journal of Industrial Engineering: Theory, Applications, and Practice (SCI indexed), under review.
  10. Rajora, M., Zou, P., and Liang, S. Y., “An Improved Approach for Solving Hierarchically Coupled Constrained Optimization Problem in Simultaneous Optimization of Neural Network Structure and Weights,” submitted to International Journal of Industrial Engineering: Theory, Applications, and Practice (SCI indexed), under review.
  11. Lu, X., Liu, S., Jia, Z., Wen C., Xiao H., Qiao X., Feng Y., Liang, S. Y.,“Tool Point Frequency Response Function in Micro-milling Based on Rotating Timoshenko Beam,” submitted to Machining Science and Technology (SCI archived), under review.
  12. Feng, Y., Hsu, F.-C., Lu, Y.-T., Lin, Y.-F., Lin, C.-T., Lin, C.-F., Lu, Y.-C., Lu, X., and Liang, S. Y., “Surface Roughness Prediction in Ultrasonic vibration-assisted Milling,” submitted to Journal of Advanced Mechanical Design, Systems, and Manufacturing (SCI archived), under review.
  13. Ning, J., Praniewicz, M., Wang, W., Dobbs, J. R., and Liang, S. Y., “Analytical Modeling of Part Distortion in Metal Additive Manufacturing,” submitted to The International Journal of Advanced Manufacturing Technology (SCI archived), under review.
  14. Feng, Y., Hsu, F.-C., Lu, Y.-T., Lin, Y.-F., Lin, C.-T., Lin, C.-F., Lu, Y.-C., and Liang, S. Y., “Temperature Prediction of Ultrasonic Vibration-assisted Milling,” submitted to Ultrasonics (SCI archived), under review.
  15. Mirkoohi, E., Dobbs, J. R., and Liang, S. Y., “An Analytical Modeling of the Residual Stress Considering the Dynamic Recrystallization,” submitted to Journal of Material Science and Engineering A (SCI archived), under review.
  16. Ding, Z., Sun, G., Guo, M., Jiang, X., Li, B., and Liang, S. Y., ‘’Effect of Phase Transition on theMicro-grinding Introduced Residual Stress”, submitted to Journal of Materials Processing Technology (SCI archived), under review.
  17. Mirkoohi, E., Hong, C. T.,Yo, Y. L., and Liang, S. Y., “Flow Softening and Microstructure Evolution Affected Residual Stress in Laser Powder Bed Fusion,” submitted to International Journal of Advanced Manufacturing Technology (SCI archived), under review.
  18. Feng, Y., Hsu, F.-C., Lu, Y.-T., Lin, Y.-F., Lin, C.-T., Lin, C.-F., Lu, Y.-C., and Liang, S. Y., “Tool Wear Rate Prediction in Ultrasonic Vibration-assisted Milling,” submitted to Machining Science and Technology (SCI archived), under review.
  19. Zhao, M., Ji, X. & Liang, S. Y., “Phase Transformation Considering the Effect of Crystallographic Orientation in Micro Grinding,”submitted toJournal of Manufacturing Science and Engineering(SCI Archived), under review.
  20. Cai, L., Feng, Y., Lu, Y., Lin, Y., Hsu, F., Hung, T. and Liang, S. Y., “Analytical Prediction of Milling Temperature with Minimum Quantity Lubrication,” submitted to Journal of Materials Processing Technology (SCI archived), under review.
  21. Feng, Y., Hsu, F.-C., Lu, Y.-T., Lin, Y.-F., Lin, C.-T., Lin, C.-F., Lu, Y.-C., and Liang, S. Y., “Force Prediction in Ultrasonic Vibration-assisted milling,” submitted to Machining Science and Technology (SCI archived), under review.
  22. Mirkoohi, E., Seivers, D. E., Garmestani, H., and Liang, S. Y., ”Thermo-Mechanical Modeling of Thermal Stress in Metal Additive Manufacturing Considering Elastoplastic Hardening,” submitted to CIRP Journal of Manufacturing Science and Technology (SCI archived), under review.
  23. Mirkoohi, E., Dobbs, J. R., and Liang, S. Y., “Analytical Modeling of Residual Stress in Metal Additive Manufacturing Considering Volume Conservation in Plastic Deformation,” submitted to Applied Physics A: Material Science. (SCI archived), under review.
  24. Mirkoohi,E., Dobbs, J. R., and Liang, S. Y., “Analytical Mechanics Modeling of In-Process Thermal Stress Distribution in Metal Additive Manufacturing,” submitted to SME Journal of Manufacturing Processes(SCI archived), under review.
  25. Wu, C., Dong, W., Zhu L., Zhang, J., Xu, L. and Liang, S. Y., “Modeling of Grinding Chip Thickness Distribution based on Material Removal Mode in Grinding of SiC Ceramics,” submitted to Journal of Advanced Mechanical Design, Systems, and Manufacturing(SCI Archived), under review.
  26. Mirkoohi, E., Seivers, D. E., Garmestani, H., and Liang, S. Y., ”Effects of Scan Strategy on Thermal Properties and Temperature Field in Selective Laser Melting,” submitted to SME Journal of Manufacturing Processes. (SCI archived), under review.
  27. Cai, L., Feng, Y., and Liang, S. Y., “Analytical Modeling of Residual Stress in End-Milling with Minimum Quantity Lubrication,” submitted to Journal of Manufacturing Processes (SCI archived), under review.
  28. Ding, Z., Sun, G., Jiang, X., and Liang, S.Y., “Cubic Boron Nitride Wheel Topography Effects on Phase Transformation of Maraging C250 Steel and Grinding Surface Quality”submitted to International Journal of Advanced Manufacturing Technology (SCI indexed), under review.
  29. Mahdavi, M., Mirkoohi, E., Hoar, E., Liang, S. Y., and Garmestani, H., "Prediction of the Deformation Behavior of a Selective Laser Melted Ti-6Al-4V Alloy as a Function of Process Parameters," submitted to International Journal of Advanced Manufacturing Technology, under review.
  30. Ning, J., Wang, W., Sievers, D. E., Garmestani, H., and Liang, S. Y., “Analytical Thermal Modeling of Powder Bed Metal Additive Manufacturing considering Boundary Heat Transfer, Powder Size Variation and Packing,” submitted to Materials (SCI archived), under review.
  31. Lu, Y., Wang, Z., Xie, R., and Liang, S. Y., “Bayesian Optimized Deep Convolutional Network for Bearing Diagnosis” submitted to The International Journal of Advanced Manufacturing Technology (SCI archived), under review.
  32. Mirkoohi, E., Ning, J., and Liang, S. Y., “Analytical Modeling of Residual Stress in Laser Powder Bed Fusion,” submitted to Crystals (SCI archived), under review.

 

Patents

  • Liang, S. Y. and Urquhart-Foster, J. A., “Method and Apparatus for Dielectric Sensing in a Thermoplastic Winding Process.” Patent No. 5,495,177, 1996.
  • Invention Disclosure: Dielectric Sensor for Process Monitoring of Thermoplastic Filament Winding,” National Science Foundation Invention Disclosure No. 93-45, 1993.
  • Lu, X., Liang, S. Y., Jia, Z., Zhang, H., Wang, H., Wang, F., and Si, L., “Early Detection Method for Micro-milling Tools,” Patent No. 201610995764.8, 2016.
  • Lu, X., Liang, S. Y., Jia, Z., Zhang, H., Wang, H., Wang, F., and Si, L., “Prediction of the Early Breakage of Micro-milling Cutter,” Patent No. 201610995764.8, 2016.
  • Lu, X., Liang, S. Y., Jia, Z., Zhang, H., Wang, H., Wang, F., Si, L., “Early Detection Method for Micro-milling Tools,” Patent No. 201610995764.8, 2016.
  • Liang, S. Y., Li, Q., and Yang, J., “An Electromechanical Properties Testing Apparatus for Stepping Motor,” Patent No. 201610140478.3, 2016.
  • Lu, X., Liang, S. Y., Jia, Z., Zhang, H., Wang, H., Wang, F., and Si, L., “Prediction of the Early Breakage of Micro-milling Cutter,” Patent No. 201610995764.8, 2016.
  • Liang, S. Y., Li, Q., and Yang, J.G., “A Property Test Equipment for Stepper Motor,” Patent No. ZL 201610140478.3, 2018.
  • Li, Q., and Liang, S.Y., “Gearbox Compound Weak Fault Diagnosis Based on a Novel Sparse Separation Method,” Patent No. ZL201711341698.3, 2018.
  • Li, Q., and Liang, S.Y., “Weak Fault Diagnosis for Gearbox Using Sparse Regularization Filter and Adaptive Sparse Decomposition Method,” Patent No. CN201810532020.1, 2018.
  • Lu, X. H., Zhang, C., Liang., S. Y., Jia, Z. Y., Si, L. K., Wang, F. R., and Ren, Z. J., “A Method for the Early Prediction of Micro-Milling Tool Wear,” Patent No. 201610995764.8, 2019.
  • Li, Q., and Liang, S. Y., “A New Method of Periodic Fault Impulses Separation and Diagnosis for Bearing under Strong Background Noise,” Patent No: CN201910279626.3, (pending), 2019.
  • Li, Q., and Liang, S.Y., “Weak Fault Diagnosis for Gearbox Using Sparse Regularization Filter and Adaptive Sparse Decomposition Method,” Application date: 2018-5-7, (pending), 2019.