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

Full-field infrared digital thermography for the modeling of temperature distributions in we maching processes.

Dr. Liang's research interests center around precision manufacturing processes in the context of modeling, monitoring, control, and optimization. Specific projects include hard cutting, submicron machine tools, predictive tooling for machining, and environmentally conscious processes. Much of the study aims at the development of theoretical and physical understanding of manufacturing technology with realistic industry applications. In the area of hard cutting, technology is been developed to apply deterministic-geometry cutting tools to shape and finish hardened parts. The research addresses issues related to part finish, residual stress, surface/sub-surface metallurgical damage, tool life, and machine stability.

In the area of submicron machine tools, research is underway to investigate the design and implementation principles of miniaturized cutting machines that achieves small chip size, short range, and minimum errors in thermal expansion and forced deflection. Issues are examined at the component and system levels in terms of drive mechanisms, position controls, work/tool fixtures, cutting tools, and inspection techniques. The study also provides a platform for the analysis of mechanical and thermodynamic behaviors of machining at the submicron scale.

In the area of predictive tooling for machining, Dr. Liang and his research group are developing an analytical understanding of the kinematics, dynamics, thermodynamics, and mechatronics of material removal processes such that optimization tooling can be achieved without exhaustive trial-and-error. This study aims to establish the fundamental basis for the prediction, control, and optimization of machining processes performance in terms of finish, tolerance, and part integrity.

His work on environmentally conscious machining focuses on the environmental impact associated with the use of coolants and lubricants in machining processes. The characteristics of airborne cutting fluids in terms of particulate size and concentration are analytically modeled in relation to machining process conditions, fluid material properties, and fluid application parameters.

The future direction of work will based on Dr. Liang's accumulated expertise in the field with new emphasis on machine/tool miniaturization, submicron precision manufacturing, and model-based tooling optimization.

Graduate students can find the projects intellectually challenging and academically stimulating. The research is useful in fostering the critical thinking and adaptive learning capability of graduate students who are willing to go beyond themselves. In addition, the projects all involve extensive collaboration with company partners and the research outcomes are meant to suit the needs and visions of today's manufacturing industry for greater precision and higher productivity.

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

SELECTED 3 YEAR PUBLICATIONS (revised 1-28-2019)

A. Refereed Journal Papers

  1. Shao, Y., Fergani, O., Li, B., and Liang, S. Y., “Residual Stress Modeling in Minimum Quantity Lubrication Grinding,” International Journal of Advanced Manufacturing Technology (SCI archived), 83 (5), pp. 743-751, 2016.
  2. Ding, Z., Li, B., Shao, Y., and Liang, S. Y., “Phase Transition at High Heating Rate and Strain Rate during Maraging Steel C250 Grinding,” Materials and Manufacturing Processes (SCI archived), Vol. 31, Issue 13, pp. 1763-1769, 2016.
  3. Tabei, A., Shih, D. S., Garmestani, H., and Liang, S. Y., “Micro-texture Evolution in Aggressive Machining of Al Alloy 7075,” Materials and Manufacturing Processes (SCI archived), Vol. 31, Issue 13, pp. 1709-1717, 2016.
  4. Majora, M., Zou, P., and Liang, S. Y., “Intelligent Manufacturing System for Next Generation Factories,” Advances in Intelligent Systems Research, Atlantis Press, doi: 10.2991/mse-15.2016.3, 2016.
  5. Fergani, O., Jiang, X., Shao, Y., Welo, T., Yang, J., and Liang, S. Y., “Prediction of Residual Stress Regeneration in Multi-pass Milling,” International Journal of Advanced Manufacturing Technology (SCI archived), Vol. 83, Issue 5, pp 1153–1160, March 2016.
  6. Ding, Z., Li, B., and Liang, S. Y., “Material Phase Transformation at High Heating Rate during Grinding,” Machining Science and Technology (SCI archived), Vol. 20, No. 2, pp. 290-311, 2016.
  7. Ji, X., Zhang, X. P., and Liang,S. Y., “Predicting the Effects of Cutting Fluid on Machining Force, Temperature and Residual Stress by Analytical Method,” International Journal of Computer Applications in Technology(EI archived), Vol. 53, Issue 2, pp.135-141, 2016.
  8. Guo, M., Li, B., Ding, Z., and Liang, S. Y., “Empirical Modeling of Dynamic Grinding Force based on Process Analysis,” International Journal of Advanced Manufacturing Technology(SCI archived), 86(9-12), pp. 3395-3405, 2016.
  9. Wu, C., Li, B., and Liang, S. Y., “A Critical Energy Model for Brittle-Ductile Transition in Grinding considering Wheel Speed and Chip Thickness Effects,” Journal of Engineering Manufacture, (SCI archived), Vol. 230(8), pp. 1372-1380, 2016.
  10. Tabei, A., Shih D. S., Garmestani. H., and Liang, S. Y., “Dynamic Recrystallization of Al Alloy 7075 in Turning,” ASME Transactions, Journal of Manufacturing Science and Engineering(SCI archived), 138(7), doi: 10.1115/1.4032807, 2016.
  11. Pang, J. Z., Wu, C. J., Li, B., Zhou Y., and Liang, S. Y., “Experimental Investigation of the Real Contact Arc Length Measurement in the Cylindrical Plunge Grinding,” Materials Science Forum (EI archived), doi: 10.1051/matecconf/20166705023, 2016.
  12. Su, Y.-F., Liang, S. Y., and Chiang, K.-N., “Design and Reliability Assessment of Novel 3D-IC Packaging,” Journal of Mechanics(SCI archived), 33(2), pp. 193-203, 2016.
  13. Li, Q., Liang, S. Y., Yang, J. “Bearing Fault Pattern Recognition Using Harmonic Wavelet Sample Entropy and Hidden Markov Model,” Journal of Shanghai Jiaotong University(EI archived), Vol. 50, No. 5, pp. 723-735, May 2016.
  14. Wu, C.,Li, B.,Yang, J., and Liang, S. Y., “Experimental Investigations of Machining Characteristics of SiC in High Speed Plunge Grinding,” Journal of Ceramic Processing Research (SCI archived), Vol. 17, No. 3, pp. 223-231, 2016.
  15. Wu, C., Li, B., Yang, J., and Liang, S. Y., “Prediction of Grinding Force for Brittle Materials Considering Co-existing of Ductility and Brittleness,” International Journal of Materials Processing Technology(SCI archived), Vol. 87, Issue 5-8, pp. 1967-1975, 2016.
  16. Li, B., Ding, Z., Xiao, J., and Liang, S. Y., “Maraging Steel 3J33 Phase Transformation during Micro-grinding,” Materials Letters (SCI archived), Vol. 164, pp. 217–220, February 2016.
  17. Li, Q., Liang, S. Y., Yang, J., and Li, B., “Long Range Dependence Prognostics for Bearing Vibration Intensity Chaotic Time Series,” Entropy (SCI archived), Vol.18, No. 1, pp. 23-37, 2016.
  18. Pan, Z., Garmestani, H., Shih, D. S., and Liang, S. Y., “Prediction of Machining-Induced Phase Transformation and Grain Growth of Ti-6Al-4V Alloy,” International Journal of Advanced Manufacturing Technology(SCI archived), V. 87(1-4), pp. 859-866, October 2016
  19. Rajora, M., Zou, P., Yang, Y. G., Fan, Z. W., Chen, H. Y., Wu, W. C., Li, B., and Liang, S. Y., “A Split-optimization Approach for Obtaining Multiple Solutions in Single-objective Process Parameter Optimization,” SpringerPlus (SCI archived), Vol. 5 (1), pp. 1424-1439, 2016.
  20. Wu, C., Li, B., Pang, J., and Liang, S. Y., “Ductile Grinding of Silicon Carbide in High Speed Grinding,” Journal of Advanced Mechanical Design, Systems and Manufacturing(SCI archived), Vol. 10, No. 2, doi: 10.1299/jamdsm.2016jamdsm0020, 2016.
  21. Yue, C., Liu X., Ding Y., and Liang, S. Y., “Off-line Error Compensation in Corner Milling Process,” Proceedings of the Institution of Mechanical Engineers Part B-journal of Engineering Manufacture(SCI archived), V. 232, pp. 1172-1181, May 2018.
  22. Zhao, M., Ji, X., Li, B., and Liang, S. Y., ”Investigation on the Influence of Material Crystallographic Orientation on Grinding Force in the Micro-grinding of Single-crystal Copper with Single Grit,” International Journal of Advanced Manufacturing Technology, (SCI archived), Vol. 90, Issue 9-12, pp. 3345-3355, 2017.
  23. 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.
  24. 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.
  25. 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.
  26. 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.
  27. 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.
  28. 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.
  29. 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.
  30. 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.
  31. 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.
  32. Lu, X., Wang, F., Jia, Z., Si, L., Zhang, C., and Liang, S. Y., “A Modified Analytical Cutting Forces Prediction Model under the Tool Flank Wear Effect in Micro-milling Nickel-based Superalloy,” International Journal of Advanced Manufacturing Technology (SCI archived), Vol. 91, No. 9-12, pp 2709-3716, 2017.
  33. 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.
  34. 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.
  35. Pan, Z., Feng, Y., Lu, Y., Lin, Y., Hung, T., Hsu, F., Lin, C., Lu, Y., and Liang, S. Y., accepted by “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.
  36. 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.
  37. Lu, X., Jia, Z., Feng, Y., and Liang, S. Y., “Predicting the Surface Hardness of Micro-milled Nickel-base Superalloy Inconel 718,” International Journal of Advanced Manufacturing Technology (SCI archived). 93(1-4), pp. 1283-1292, 2017.
  38. 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.
  39. 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.
  40. Lu, X., Hu X., Jia Z., Liu M., Gao S., Qu C. 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), No. 1, pp.1-14, 2017
  41. 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,” InternationalJournal of Mechanical Sciences(SCI archived), V. 133, pp. 167-177, November 2017.
  42. Lu, X., Wang, H., Jia, Z., Feng, Y., and Liang, S. Y., “Effects of Cutting Parameters on Temperature and Temperature Prediction in Micro-milling of Inconel 718,” accepted by International Journal of Nanomanufacturing (EI archived), 2017 (in print).
  43. 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.
  44. Pan, Z., Feng, Y. and Liang, S.Y., "Material Microstructure Affected Machining: a Review,”Manufacturing Review (EI archived), V. 4, pp. 5, May 2017.
  45. Pan, Z. and Liang, S.Y., "Material Driven Machining Process Modeling,”Manufacturing Letters (SCI archived), V. 14: pp. 1-5, October 2017.
  46. 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.
  47. 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.
  48. 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.
  49. 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).
  50. 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.
  51. 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).
  52. Lu, X., Zhang, H,, Jia, Z., Feng, Y., 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), No. 9-12, pp. 1-11, 2017.
  53. 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.
  54. 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).
  55. Lu, X., Xv, Y., Wang, W., Zhou, Y., and Liang, S. Y., “Experimental Study of the Effect of Light Source Spot Size on Measure Error of PSD,” accepted by International Journal of Manufacturing Research (EI archived), 2017 (in print).
  56. Lu, X., Wang, H., Jia, Z., Feng, Y., Liang, S. Y.,“Strain HardeningProperties and the Relationship Between Strain and Hardness of Inconel 718,”accepted byInternational Journal of Materials and Structural Integrity(EI archived), 2017 (in print).
  57. 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.
  58. 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.
  59. 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). 2018. (In print).
  60. Ning, J., and Liang S. Y., “Inverse Identification of Johnson-Cook Material Constants Based on Modified Chip Formation Model and Iterative Gradient Search Using Temperature and Force Measurements,”accepted by International Journal of Advanced Manufacturing Technology (SCI archived), 2018 (in print).
  61. Ning, J., Nguyen, V., & Liang, S. Y., “Analytical Modeling of Machining Forces of Ultra-fine-grained Titanium,”International Journal of Advanced Manufacturing Technology (SCI archived), 1-10, doi: 10.1007/s00170-018-2889-6, 2018.
  62. 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), V. 97(1-4), pp 1053-1060, July 2018.
  63. Ning, J., Nguyen, V., Huang, Y., Hartwig, K.T., 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) V. 99(5-8), pp.1131-1140, November 2018.
  64. 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 V. 2(2), pp. 37, June 2018.
  65. 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 V. 2(4), pp. 74, October 2018.
  66. 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, doi org/10.1051/Mfreview / 2018014, 2018.
  67. Zhao, M., Ji, X., Li, B., & Liang, S. Y. “Effect of Crystallographic Orientation on the Hardness of Polycrystalline Materials AA7075,” Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science (SCI Archived), doi: org/10.1177/0954406218802935, 2018.
  68. Zhao M, Ji X, Liang S Y. “Influence of AA7075 Crystallographic Orientation on Micro-Grinding Force,” Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture (SCI Archived),doi: 0954405418803706, 2018.
  69. Lu, X., Zhang, H. X., Jia, Z. Y., Feng, Y. X., 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/EI archived), V. 32, N. 7, pp. 3379-3388, July 2018.
  70. Lu, X., Jia, Z. Y., Yang, K., Shao, P. L., Ruan, F. X., Feng, Y. X., 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/EI archived), V. 97, N. 9-12, pp. 3915-3923, August 2018.
  71. Lu, X., Wang, F. R., Jia, Z. Y., Si, L. K., Liang, Y. S., “The Flank Wear Prediction in Micro-milling Inconel 718,”Industrial Lubrication and Tribology (SCI/EI archived), V. 70, N. 8, pp. 1374-1380, November 2018.
  72. Lu, X., Wang, H., Jia, Z. y., Feng, Y. X., Liang, S. Y., “Coupled Thermal and Mechanical Analyses of Micro-milling Inconel 718,”Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture (SCI/EI Archived), doi: 10.1177/0954405418774586, 2018 (in print).
  73. Lu, X., Wang, F. R., Xue, L., Feng, Y. X., 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 indexed), 2018 (in print).
  74. 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.
  75. 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.
  76. 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.
  77. 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), 98(9-12): p. 2347-2355, 2018.
  78. Mirkoohi, E., Ning, J., Bocchini, P., Fergani, O., Chiang, K-N., 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 (SCI Archieved), 2(3):63, 2018.
  79. Allen, J., Hoar, E., Mirkoohi, E., Bocchini, P., Rollet, A., Liang, S., and Garmestani, H.,“Viscoplastic Self-Consistent Modeling of High Speed Machining of Dual Phase Ti-6Al-4V with a Mechanical Threshold Stress Flow Stress Model,”Accepted by Algorithm Development in Materials Science and Engineering, 2018.
  80. Liang, S., 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.
  81. 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.
  82. 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), V. 6,pp. 10986-10995, March 2018.
  83. Lu, Y.F., Li, Q., and Liang, S.Y., “Physics-Based Intelligent Prognosis for Rolling Bearing withFault Feature Extraction,” The International Journal of Advanced Manufacturing Technology (SCI archived), V. 7, pp. 1-10, April 2018.
  84. 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), 20, no. 3, pp. 1409-1425, May 2018.
  85. 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), V. 6, pp. 20242-20254, April 2018.
  86. 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.
  87. 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.
  88. Li,Q., Ji, X., Yang, J.G., and Liang, S.Y., “Stability Analysis for SiC Grinding Based Upon Harmonic Wavelet and Lipschitz Exponent,”accepted by Machining Science and Technology (SCI archived),2018 (in print).
  89. 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), V.18, no.16, pp. 6693-6705, June 2018.
  90. Li, Q., and Liang, S.Y., “Intelligent Prognostics of Degradation Trajectories for Rotating Machinery Based on Asymmetric Penalty Sparse Decomposition Model,” Symmetry (SCI archived), V. 10, no. 6, 214, June 2018.
  91. 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.
  92. Li, Q., and Liang, S.Y., “Weak Crack Detection for Gearbox Using Sparse Denoising and Decomposition Method,”accepted by IEEE Sensors Journal (SCI archived), 2018 (in print).
  93. Li, Q., and Liang, S.Y., “Degradation Trend Prediction for Rotating Machinery Using Long-range Dependence and Particle Filter Approach,” Algorithms (EI archived), V. 11, no. 7, 89, June 2018.
  94. 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), V.54, no. 23, pp. 102-111, December 2018.
  95. 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
  96. Li, Q., and Liang, S.Y., “Weak Fault Detection of Tapered Rolling Bearing Based on Penalty Regularization Approach,” Algorithms (EI archived), V. 11, no.11, 184, November 2018.
  97. 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,” accepted byProceedings of the CSEE (EI archived), 2018 (in print).
  98. 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.
  99. 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.
  100. 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 of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture (SCI archived), doi:10.1177/0954405418769927, 2018.
  101. 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 of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science (SCI archived), doi: 10.1177/0954406218805122, 2018.
  102. Pan, Z., Tabei, A., Shih, D.S., Garmestani, H. and Liang, S.Y., "The Effects of Dynamic Evolution of Microstructure on Machining Forces,”Proceedings of the institution of mechanical engineers, Part B: Journal of Engineering Manufacture (SCI archived), V. 232(14): pp. 2677-2681, December 2018.
  103. 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.
  104. 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.
  105. Feng, Y., Hung, T.-P., Lu, Y.-T., Lin, Y.-F., Hsu, F.-C., Lin, C.-F., Lu, Y-C., and Liang, S. L., “Analytical Prediction of Temperature in Laser-assisted Milling with Laser Preheating and Machining Effects,” International Journal of Advanced Manufacturing Technology (SCI archived), doi:10.1007/s00170-018-2930-9, 2018.
  106. 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. L., “Inverse Analysis of Inconel 718 Laser-Assisted Milling to Achieve Machined Surface Roughness,” International Journal of Precision Engineering and Manufacturing(SCI archived), V. 19, pp. 1611-1618, November 2018.
  107. 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. L., “Surface Roughness Modeling of Laser-assisted End Milling Inconel 718,” accepted by Machining Science and Technology(SCI archived), 2018 (in print).
  108. 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.
  109. 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), 2018 (in print).
  110. Feng, Y., Hung, T.-P., Lu, Y.-T., Lin, Y.-F., Hsu, F.-C., Lin, C.-F., Lu, Y-C., and Liang, S. L., “Residual Stress Prediction in Laser-assisted Milling considering Recrystallization Effects,” International Journal of Advanced Manufacturing Technology (SCI archived), doi:10.1007/s00170-018-3207-z, 2019.
  111. Mirkoohi, E., Bocchini, P., and Liang, S. Y.,“Analytical Temperature Predictive Modeling and Non-Linear Optimization in Machining,”Accepted by The International Journal of Advanced Manufacturing Technology (SCI Archieved), 2019.
  112. 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 of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture (SCI archived), V. 223(1), pp. 109-117, January 2019.

B. Referred Conference Papers

  1. Rajora, M., Zou P., and Liang, S. Y., “A Hybrid RF-GA Approach to Bottleneck Machine Diagnosis and Suggestion in Parallel Machine Job-shop Scheduling,” Proceedings of the ASME 11th Manufacturing Science and Engineering Conference (MSEC)(EI archived), Blacksburg, VA, June 27-July 1, 2016.
  2. Ding, Z., Li, B., Fergani, O., Shao, Y., and Liang, S. Y., “Investigation of Temperature during Maraging Steel Micro-grinding,” Proceedings of 2016 International Conference on Design, Materials and Manufacturing (ICDMM), Kuala Lumpur, Malaysia, March 25-27, 2016, also appears in Key Engineering Materials(EI archived).
  3. Li, Qing, Liang, S. Y., and Song W., “Revision of Bearing Fault Characteristic Spectrum using LMD and Interpolation Correction Algorithm,” Procedia CIRP on Intelligent Manufacturing in the Knowledge Economy Era(EI archived), Vol. 56, pp. 182-187, 2016.
  4. Davis, B., Hartwig, T. K., Liang, S. Y., and Huang Y., “Evaluation of Chip Morphology during Machining of ECAE Titanium,” Proceedings of International Symposium on Flexible Automation (ISFA), August 1-3, Cleveland, OH, 2016.
  5. Liu, H. B., Wu, D., Liang, S. Y., Wang, Y. Q., and Sheng, X. J., “Machining-induced Surface Residual Stress Prediction Based on Cutting Action Decomposition,” Proceedings of the 10th International Conference on Residual Stress(IRCS 10), Sydney, Australia, 3-7 July, 2016.
  6. Fergani, O., Pan, Z., Liang, S. Y., Atmani, Z., and Welo, T., “Microstructure Texture Prediction in Machining Processes,” Procedia CIRP (EI archived), Vol, 46, pp. 595-598, 2016.
  7. Pang, J. Z., Wu, C. J., Li, B., Zhou, Y., and Liang, S. Y., “Experimental Investigation of the Real Contact Arc Length Measurement in the Cylindrical Plunge Grinding,” MATEC Web of Conferences (EI archived), , V. 67, July 29, 2016, Proceedings of International Symposium on Materials Application and Engineering, SMAE 2016.
  8. Rajora, M., Zou, P., Xu, W., Jin, L., Chen, W., and Liang, S.Y., “Modelling of Decision Making in the Production of Stator Core Using a GA-ANN Approach”, Proceedings of International Conference on Artificial Intelligence: Techniques and Applications (AITA2016), (EI archived), Shanghai, China, September 25-26, 2016.
  9. Ding, Z., Li, B., Fergani, O., Shao, Y., and Liang, S. Y., “Investigation of Temperature and Energy Partition During Maraging Steel Micro-grinding,” Proceeds of 9th International Conference on Digital Enterprise Technology(DET 2016), March 29 - 31, 2016, Nanjing, China, also in Procedia CIRP (EI archived), Vol, 56, pp. 284–288, 2016.
  10. Zou, P., Rajora, M., Fen, Z.W., Yang, M.Y., Chen, H.Y., Wu, W.C., Li, B., and Liang, S.Y., “Electrochemical Micro-Machining Parameter Optimization based on Hybrid Neural Network and Genetic Algorithm,” Proceedings of International Conference on Manufacturing Technologies (ICMT2017), (EI archived), San Diego, January 19-21, 2017.
  11. Fergani, O., Elmansori, M., and Liang, S. Y., “Additive Manufacturing Process Thermomechanical Signature and Residual Stress: an Analytical Approach,” Proceedings of the ASME 12th International Manufacturing Science and Engineering Conference (EI archived), June 4-8, 2017, Los Angeles, 2017.
  12. Pan, Z., Feng, Y., Ji, X., and Liang, S. Y., “Turning Force Prediction of AISI 4130 Considering Dynamic Recrystallization,” Proceedings of the ASME 12th International Manufacturing Science and Engineering Conference(EI archived), June 4-8, 2017, Los Angeles, 2017.
  13. Lu, X., Zhang, H., Jia, Z., Feng, Y., and Liang, S. Y., "A New Method for the Prediction of Micro-Milling Tool Breakage," Proceedings of the ASME 12th International Manufacturing Science and Engineering Conference(EI archived), June 4-8, 2017, Los Angeles, 2017.
  14. Lu, X., Wang, H., Jia, Z., Si, L., and Liang, S. Y., " The Effect of Tool Nose Corner Radius and Main Cutting Edge Radius on Micro-Milling Temperature,"Proceedings of the ASME 12th International Manufacturing Science and Engineering Conference(EI archived), June 4-8, 2017, Los Angeles, 2017.
  15. Li, Q., Ji, X. and Liang, S.Y., “Pattern Recognition of Tool Wear in High-speed Milling Based upon Nonlinear Analysis,” Proceedings of IEEE International Conference on Electronics Information and Emergency Communication (IEEE-ICEIEC) (EI archived), Macau, July 21-23, 2017.
  16. Ayjhan, B., Kwan, C., and Liang, S. Y., “A Portable Prognostic System for Bearing Monitoring,” Proceedings, 14th International Symposium on Neural Networks (ISNN), Sapporo, Japan, June 21-23, 2017.
  17. 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), v 114, July 10, 2017, 2017 Proceedings of International Conference on Mechanical, Material and Aerospace Engineering, 2MAE 2017.
  18. Li, Q. and Liang, S. Y., “Incipient Multi-Fault Diagnosis of Rolling Bearing using Improved TQWT and Spare Representative Approach,” Proceedings of 2nd IEEE International Conference on Signal and Image Processing(IEEE-ICSIP) (EI archived), 2017, Singapore, August4-6, 2017.
  19. Liang, S. Y. and Pan, Z., “Process and Microstructure in Materials-Affected Manufacturing,” Proceedings of 5th International Conference on Advanced Manufacturing Engineering and Technologies(NEWTECH), Belgrade, Serbia, June 5-9, 2017.
  20. Liang, S. Y. and Pan, Z., “Integration of Process Mechanics and Materials Mechanics for Precision Machining”, Proceedings of 9th International Congress on Precision Machining (ICPM), Athens, Greece, September 6-9, 2017.
  21. 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 of IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference (IEEE-ITNEC)(EI archived), Chengdu, China, December 15-17, 2017.
  22. Lu, Y., Li, Q., and Liang, S. Y., “Adaptive Prognosis of Bearing Degradation Trend Based on Wavelet Decomposition Assisted ARMA Model,” Proceedings of IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference (IEEE-ITNEC)(EI archived), Chengdu, China, December 15-17, 2017.
  23. Ayhan, B., Kwan, C., and Liang, S. Y., “An Accurate Remaining Life Prediction Algorithmfor Bearings,” Proceedings of IEEE International Conference on Prognostics and Health Management (ICPHM), Seattle, WA, USA, June 11-13, 2018.
  24. Ayhan, B., Kwan, C., and Liang, S. Y., “High Performance Remaining Life PredictionAlgorithms for Gearbox,” Proceedings of IEEE International Conference on Prognostics and Health Management (ICPHM), Seattle, WA, USA, June 11-13, 2018.
  25. Pan, Z., Feng, Y., Liang, S.Y., “Microstructural Sensitive Flow Stress Modeling of Ti-6Al-4V in the Machining Process,” Proceedings of ASME International Manufacturing Science and Engineering Conference MSEC 2018 (EI archived), College Station, Texas, July 2018.
  26. 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 of ASME International Manufacturing Science and Engineering Conference MSEC 2018 (EI archived), College Station, Texas, July 2018.
  27. 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.
  28. 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.
  29. 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 of the International Conference on Manufacturing Technologies (ICMT) (EI archived), San Diego, CA, January 19-21, 2017.
  30. 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,” 4th International Conference on Mechanical, Materials and Manufacturing (ICMMM) (EI archived), 2017, Atlanta, GA, October 25-27.
  31. 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.
  32. Feng, Y., Hung, T.-P., Lu, Y.-T., Lin, Y.-F., Hsu, F.-C., Lin, C.-F., Lu, Y-C., and Liang, S. L.,” Prediction of Surface Hardness in Laser-assisted Milling” submitted to Proceedings of the ASME 2019 14th International Manufacturing Science and Engineering Conference, MSEC 2019 (EI archived), Erie, PA, USA., June 10-14, 2019. (under review)
  33. Liang, S. Y., Ning, J., and Mirkoohi, E., “A Closed-form Solution for Temperature Prediction in Selective Laser Melting Considering Boundary Condition” 2019 3rd International Conference on Advanced Manufacturing and Materials (ICAMM 2019) (SCI archived), 2019, Beijing, May 29-31, 2019.
  34. Lu, X. H., Wang, F. R., Yang, K., Feng, Y. X., Liang, S. Y., “An Indirect Method for the Measurement of Micro-milling Forces”, submitted to Proceedings of the ASME 2019 14th International Manufacturing Science and Engineering Conference, MSEC 2019 (EI archived), Erie, PA, USA., June 10-14, 2019. (under review)
  35. Mirkoohi, E., Sievers, D.E., Liang, S. Y.,” Effect of Time Spacing and Hatching Space on Thermal Material Properties and Melt Pool Geometry in Additive Manufacturing of S316L” submitted to Proceedings of the ASME 2019 14th International Manufacturing Science and Engineering Conference, MSEC 2019 (EI archived), Erie, PA, USA., June 10-14, 2019. (under review)

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. Liang, S.Y., Zou, P., and Rajora, M., ”Intelligent Manufacturing System, A Review”, submitted toChinese Journal of Mechanical Engineering (English contributions SCI archived), under review
  4. Lu, X., 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
  5. 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
  6. Li, Q., Ji, X., and Liang, S. Y., “OTD and Nonconvex Penalty Minimization Lq Regular for Microstructure Image Inpainting,” submitted to Optik (SCI archived), under review
  7. Lu, X., Jia, Z., Feng, Y., 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,” submitted to Measurement (SCI archived), under review
  8. 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
  9. Lu, Y., Pan, Z., and Liang, S. Y., "Diagnosis and Prognosis by Recursive Least Square ARMA Model with Case Study of Bearing Vibration," submitted to Mechanical Systems and Signal Processing (SCI archived), under review
  10. 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
  11. 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
  12. Ding, Z., Jiang, X., Guo, M., Fergani, O., and Liang. S. Y., “Phase Transformation Effects on Micro-grinding Forces,” submitted to International Journal of Mechanical Sciences(SCI archived), under review
  13. Li, Q., Ji, X., and Liang, S. Y., “EBSD Microstructure Image Denoising using VMD and Sparse Stein Unbiased Risk Estimator Method,” submitted to Chinese Journal of Electronics (EI archived), under review
  14. Li, Q. and Liang, S. Y., “An Improved Long Range Dependence Approach for Degradation Trend Prognostics of Rolling Bearing,” submitted to Mechanical Systems and Signal Processing (SCI archived), under review
  15. Jiang, X., Ding, Z., Liang, S. Y., and Fergani, O., “Cubic Boron Nitride Wheel Topography Effects on Maraging C250 Steel Phase Transformation and Roughness," submitted to Machining Science and Technology (SCI archived), under review
  16. Zhang,Y.,Li, B., Yang, J., and Liang, S. Y., “Modeling and Optimization of Alloy Steel 20CrMnTi Grinding Process Parameters based on Experiments Investigation,” submitted to International Journal of Advanced Manufacturing Technology, (SCI archived), under review
  17. Pan, Z.,Feng, Y., and Liang, S. L.,“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
  18. Li, Q. and Liang, S. Y.,”A New Non-convex Regularization Approach for Weak Fault Feature Extraction of Rotating Machinery,” submitted to IEEE transactions on neural network and learning system (SCI archived), under review
  19. Lu, Y., Li, Q., Pan, Z., and Liang, S. Y., "Prognosis of Bearing Degradation using Gradient Variable Forgetting Factor RLS Combined with Time Series Model", submitted to IEEE Access (SCI archived), under review
  20. Zou, P., Rajora, M., and Liang, S.Y., “Multimodal Optimization of Job-Shop Scheduling Problems using a Clustering Generic-Algorithm Based Approach,” submitted to International Journal of Industrial Engineering: Theory, Applications, and Practice (SCI indexed), under review
  21. Lu, Y., Li, Q., and Liang, S. Y., “Physics-based Intelligent Prognosis for Rolling Bearing using RV and Energy Ratio”, submitted to International Journal of Advanced Manufacturing Technology (SCI archived), under review
  22. 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
  23. Li, Q. and Liang, S. Y., ”Sparse Optimization with Non-separable Minimax Concave Penalty Regularizer and Its Application on Bearing Fault Detection,”submitted to Mechanical Systems and Signal Processing(SCI archived), under review
  24. 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
  25. Lu, X., Jia, Z., Yang, K., Ruan, F., Feng, Y., and Liang, S. Y., “Analytical Model of Work Hardening and Simulation of the Distribution of Hardening in Micro-milled Nickel Base Superalloy,” submitted to International Journal of Advanced Manufacturing Technology (SCI archived), under review
  26. 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
  27. Lu, X., Jia, Z., Wang, X., Liu, Y., Feng, Y., and Liang, S. Y., “Measurement and Prediction of Vibration Displacement in Micro-milling of Nickel-based Superalloy” submitted to Measurement (SCI archived), under review
  28. Wu C., Pang J., Li B. and Liang S.Y. “Determination of Grinding Chip Thickness Distribution Based on Material Removal Mode in Grinding of Silicon Carbide Ceramics” submitted to Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science (SCI indexed), under review
  29. 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” submitted to International Journal of Advanced Manufacturing Technology (SCI archived), under review
  30. Ning, J., and Liang S. Y., “A Comparative Study of Analytical Thermal Models to Predict the Orthogonal Cutting Temperature of AISI 1045 Steel” submitted to International Journal of Advanced Manufacturing Technology (SCI archived), under review
  31. Ning, J., and Liang S. Y., “Predictive Modeling of Machining Temperatures with Force-Temperature Correlation Using Cutting Mechanics and Constitutive Relation” submitted to Materials (SCI archived), under reviewNing, 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” submitted to Journal of Manufacturing Processes (SCI archived), under review
  32. Ning, J., Sievers, D. E., Garmestani, H., and Liang, S. Y., “Analytical Modeling of in-Situ Deformation of Part and Substrate in Laser Cladding Additive Manufacturing of Inconel 625” submitted to Journal of Manufacturing Processes (SCI archived), under review
  33. 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), under review
  34. Zhao M, Ji X, Liang S Y. “The Influence of Material Crystallographic Orientation on Grinding Temperature in the Micro Grinding AA7075,” submitted to Journal of manufacturing processes(SCI archived), under review
  35. Zhao M, Ji X, Liang S Y. “The Influence of Material Crystallographic Orientation on Residual Stress in the Micro Grinding AA7075,” submitted to Part C: Journal of Mechanical Engineering Science (SCI archived), under review
  36. Zhao M, Ji X, Liang S Y. “Micro-Grinding Temperature Prediction Considering the Effect of Crystallographic Orientation and the Strain Induced by Phase Transformation,” submitted to International journal of precision engineering and manufacturing(SCI archived), under review
  37. Lu, X. H., Jia, Z. Y., Zhang, H. X., Xue, L., Liu, M. Y., Feng, Y. X., Liang, S. Y., “Research on the Simulation of Micro-milling Inconel 718 Considering Scale Effect”, submitted to Journal of Manufacturing Science and Engineering, Transactions of the ASME (SCI/EI archived), under review
  38. Lu, X. H., Jia, Z. Y., Wang, H., Feng, Y. X., 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”, submitted to Measurement (SCI/EI archived), under review
  39. Lu, X. H., Jia, Z. Y., Liu, S.Q., Wen, C. K., Xiao, H. T., Qiao, X. Y., Feng, Y. X., Liang, S. Y., “Chatter Stability of Micro-Milling by Considering the Centrifugal Force and Gyroscopic Effect of the Spindle”, submitted to Journal of Materials Processing Technology (SCI/EI archived), under review
  40. Lu, X. H., Jia, Z. Y., Wang, X. X., Liu, Y. B., Feng, Y. X., Liang, S. Y., “Measurement and Prediction of Vibration Displacement in Micro-Milling of Nickel-based Superalloy”, submitted to Measurement (SCI/EI archived), under review.
  41. Lu, X. H., Wang, Y. Q., Li, J., Zhou, Y., Ren Z. J., Liang, S. Y., “Three-Dimensional Coordinate Measurement Algorithm by Optimizing BP Neural Network Based on GA”, Engineering Computations (SCI/EI archived), under review
  42. Lu, Y., Xie, R., and Liang, S.Y., “Extraction of Weak Fault Using Combined Dual-Tree Wavelet and Improved MCA for Rolling Bearings” submitted to Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems (SCI-E archived), under reviewLu, Y., Xie, R., and Liang, S.Y., “Intelligent Online Learning Diagnostic Model for Bearing Fault Detection” submitted to The International Journal of Advanced Manufacturing Technology (SCI archived), under review
  43. Mirkoohi, E., Bocchini, P., and Liang, S. Y.,” Inverse Analysis of Residual Stress in Orthogonal Cutting”, submitted to SME Journal of Manufacturing Processes. (SCI archived), under review
  44. Mirkoohi, E., Ning, J., Sievers, D.E., Garmestani, H., Chiang, K-N., Liang, S. Y., “Three-Dimensional Analytical Modeling of Melt Pool Geometry Considering Hatching Space and Time Spacing in Metal Additive Manufacturing”, submitted to SME Journal of Manufacturing Processes. (SCI archived), under review
  45. Mirkoohi, E., Sievers, D.E., Garmestani, H., Liang, S. Y.,” Effects of Time Spacing, Hatching Space, and Number of Scans on Thermal Properties and Melt Pool Geometry in Selective Laser Melting”, submitted to The Journal of Material Processing Technology. (SCI archived), under review
  46. Li, Q., and Liang, S.Y., “Simulated Image Denoising for Electronic Microstructure based on VMD and Sparse Stein Unbiased Risk Estimator Algorithm,” Chinese journal of electronics (EIarchived), under review
  47. Feng, Y., Hung, T.-P., Lu, Y.-T., Lin, Y.-F., Hsu, F.-C., Lin, C.-F., Lu, Y-C., and Liang, S. L., “Flank Tool Wear Prediction of Laser-assisted Milling,” submitted to Journal of Manufacturing Processes (SCI archived), under review
  48. Gao, H., Yue, C., Liu, X., Liang, S. Y., and Wang, L., “Milling stability analysis with simultaneously considering process damping effect and material removing effect” submitted toTransactions of Nanjing University of Aeronautics & Astronautics (EI archived), under review
  49. Ding, Z., Sun, G., Jiang, X., Guo, M., and Liang, S.Y., “Predictive Modeling of Micro-grinding Force Incorporating Phase Transformation Effects” submitted to Journal of Manufacturing Science and Engineering (SCI archived), under review
  50.  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", submitted to The International Journal of Advanced Manufacturing Technology (SCI archived), under review
  51. Tabei, A., Mirkoohi, E., Garmestani, H., Liang, S. Y., “Modeling of Texture Development in Additive Manufacturing of Ni-based Superalloys” submitted to The Journal of Material Processing Technology. (SCI archived), under review
  52. Lu, Y., Pan, Z., Bocchini, P., Garmestani, H., and Liang, S.Y., “Grain Size Sensitive MTS Model for Ti-6Al-4V Machining Force and Residual Stress Prediction” submitted to The International Journal of Advanced Manufacturing Technology(SCI Archived), under review
  53. Ding, Z., Sun, G., Guo., M., Jiang, X., Li, B., Liang, S. Y., ‘’Effect of Phase Transition on the Micro-grinding Introduced Residual Stress”, submitted to Journal of Materials Processing Technology (SCI archived), under review
     

Patents

  • US Patent Number 5,495,177, “Method and Apparatus for Dielectric Sensing in a Thermoplastic Winding Process.” Inventors: S Y. Liang, S. Y. and Urquhart-Foster, J. A., Patent date: February 27, 1996.
  • Invention Disclosure: Dielectric Sensor for Process Monitoring of Thermoplastic Filament Winding,” National Science Foundation Invention Disclosure No. 93-45, 1993.
  • Chinese Patent No. 201610995764.8, “Early Detection Method for Micro-milling Tools,” Inventors: Lu, X., Liang, S. Y., Jia, Z., Zhang, H., Wang, H., Wang, F., Si, L., 2016.
  • Chinese Patent No. 201610140478.3, “An Electromechanical Properties Testing Apparatus for Stepping Motor,” Inventors: Liang, S. Y., Li, Q., Yang, J., 2016.
  • Chinese Patent No. 201610995764.8, “Prediction of the Early Breakage of Micro-milling Cutter,” Inventors: Lu, X., Liang, S. Y., Jia, Z., Zhang, H., Wang, H., Wang, F., Si, L., 2016.
  • Patent Application: “Gearbox Compound Weak Fault Diagnosis based on a Novel Sparse Separation Method,” Inventors: Qing Li, Q. and Liang, S. Y., (pending), 2017.
  • Liang, S.Y., Li, Q., and Yang, J.G., “A Property Test Equipment for Stepper Motor,” No. ZL 201610140478.3, 2018.
  • Li, Q., and Liang, S.Y., “Gearbox Compound Weak Fault Diagnosis Based on a Novel Sparse Separation Method,” No. ZL201711341698.3, (published online), 2018.
  • 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).