Laser-Assisted Forming of Ultra-High Strength Steels: A Critical Review of Mechanisms, Processes, and Future Directions

Abstract

Ultra-high strength steels (UHSS) are critical for lightweighting in the automotive and aerospace industries, but their poor room-temperature formability presents a significant manufacturing barrier. Laser-assisted forming (LAF) has emerged as a key enabling technology that utilizes localized laser heating to reduce forming forces, enhance ductility, and mitigate springback. This paper provides a critical review of the state-of-the-art in LAF of UHSS. It begins by elucidating the governing principles, including the coupled thermo-mechanical and metallurgical mechanisms such as thermal softening, dynamic microstructure evolution, and non-equilibrium phase transformations. The review then systematically surveys the major LAF process variants—including bending, roll forming, and incremental forming—and their applications in fabricating complex UHSS components. Despite its proven advantages, significant challenges impede its widespread industrial adoption. The most critical issues are identified and discussed, including local mechanical property degradation due to uncontrolled thermal cycles, the complexity of predictive multi-physics modeling, and the need for robust in-situ process monitoring and control. Ultimately, this review presents a forward-looking perspective, proposing future research directions that focus on microstructure management, the development of high-fidelity digital twins, and the implementation of intelligent closed-loop control systems to ensure process stability and part integrity. This work provides a comprehensive roadmap for advancing the science and technology of LAF for next-generation lightweight manufacturing.

Keywords

Laser-assisted forming / Ultra-high strength steel / Thermo mechanical coupling / Microstructure evolution / Process-structure-property relationship

Author Contributions

J.G.-G.d.R.: Methodology, Validation, Original Draft Preparation; Z.H.: Conceptualization, Writing-Review & Editing, Funding Acquisition, Project Administration; Y.G. and L.C.: Methodology, Formal Analysis; Z.W. and J.W.: Validation, Project Administration; J.M.: Writing-Review & Editing, Supervision.

Ethics Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Funding

The present work was supported by and the Science and Technology Commission of Shanghai Municipality (No.24520790200) and the National Natural Science Foundation of China (No. 52105395). JY Min acknowledges the financial support by the Xiaomi Young Scholars Program.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

References

[1] Li J, Zhan D, Jiang Z, Zhang H, Yang Y, Zhang Y. Progress on improving strength-toughness of ultra-high strength martensitic steels for aerospace applications: A review. J. Mater. Res. Technol. 2023, 23, 172-190. doi:10.1016/j.jmrt.2022.12.177.

[2] Wang X, Li W, Yao Y, Fan L, Wang J, Wang W, et al. In-situ alloyed ultrahigh strength steels via additive manufacturing. Addit. Manuf. 2023, 77, 103825. doi:10.1016/j.addma.2023.103825.

[3] Li J, Tian J, Zhan D, Wang W, Jiang Z. Designing a new ultra-high strength steel with multicomponent precipitates under material genetic design. J. Mater. Res. Technol. 2024, 33, 4449-4461. doi:10.1016/j.jmrt.2024.10.140.

[4] Arola A-M, Kaijalainen A, Kesti V, Troive L, Larkiola J, Porter D. The effect of mechanical behavior on bendability of ultrahigh-strength steel. Mater. Today Commun. 2021, 26, 101943. doi:10.1016/j.mtcomm.2020.101943.

[5] Li K, Yang T, Gong N, Wu J, Wu X, Zhang DZ, et al. Additive manufacturing of ultra-high strength steels: A review. J. Alloys Compd. 2023, 965, 171390. doi:10.1016/j.jallcom.2023.171390.

[6] Pokka A-P, Kesti V, Kaijalainen A. Global formability and bendability of ultra-high strength steels: Effect of mechanical properties on the strain distribution and behaviour in air-bending. Mater. Today Commun. 2023, 37, 107081. doi:10.1016/j.mtcomm.2023.107081.

[7] Li F, Liu C, Cao Y, Meng Y, Xu W. Deformation inhomogeneity evolution and crack formation mechanism analysis in ultra-high strength steel by crystal plasticity simulations. Eng. Fail. Anal. 2024, 163, 108502. doi:10.1016/j.engfailanal.2024.108502.

[8] Mori K, Bariani PF, Behrens B-A, Brosius A, Bruschi S, Maeno T, et al. Hot stamping of ultra-high strength steel parts. CIRP Ann. 2017, 66, 755-777. doi:10.1016/j.cirp.2017.05.007.

[9] Tsang KS, Ion W, Blackwell P, English M. Industrial validation of strain in cold roll forming of UHSS. Procedia Manuf. 2018, 15, 788-795. doi:10.1016/j.promfg.2018.07.322.

[10] Geiger M, Merklein M, Pitz M. Laser and forming technology—an idea and the way of implementation. J. Mater. Process. Technol. 2004, 151, 3-11. doi:10.1016/j.jmatprotec.2004.04.004.

[11] Vogt S, Weisheit A, Schleifenbaum JH. Local laser softening of cold forming steels. J. Laser Appl. 2020, 32, 042020. doi:10.2351/7.0000221.

[12] Safari M, de Sousa RA, Joudaki J. Recent Advances in the Laser Forming Process: A Review. Metals 2020, 10, 1472. doi:10.3390/met10111472.

[13] Duflou JR, Callebaut B, Verbert J, De Baerdemaeker H. Laser Assisted Incremental Forming: Formability and Accuracy Improvement. CIRP Ann. 2007, 56, 273-276. doi:10.1016/j.cirp.2007.05.063.

[14] Luo C, Zhao Y, Cao Y, Zhao L, Shan J. Effect of laser heat treatment on bending property of laser welded joints of low-alloy ultra-high strength steel. J. Laser Appl. 2019, 31, 032011. doi:10.2351/1.5089875.

[15] Amraei M, Afkhami S, Javaheri V, Larkiola J, Skriko T, Björk T, et al. Mechanical properties and microstructural evaluation of the heat-affected zone in ultra-high strength steels. Thin-Walled Struct. 2020, 157, 107072. doi:10.1016/j.tws.2020.107072.

[16] Sun J, Dilger K. Influence of preheating on residual stresses in ultra-high strength steel welded components. J. Mater. Res. Technol. 2023, 25, 3120-3136. doi:10.1016/j.jmrt.2023.06.181.

[17] Roohi AH, Gollo MH, Naeini HM. External force-assisted laser forming process for gaining high bending angles. J. Manuf. Process. 2012, 14, 269-276. doi:10.1016/j.jmapro.2012.07.004.

[18] Sedlmaier A, Dietl T. 3D roll forming center for automotive applications. Procedia Manuf. 2018, 15, 767-774. doi:10.1016/j.promfg.2018.07.319.

[19] Sweeney K, Grunewald U. The application of roll forming for automotive structural parts. J. Mater. Process. Technol. 2003, 132, 9-15. doi:10.1016/S0924-0136(02)00193-0.

[20] Mäntyjärvi K, Merklein M, Karjalainen JA. UHS Steel Formability in Flexible Roll Forming. Key Eng. Mater. 2009, 410-411, 661-668. doi:10.4028/www.scientific.net/KEM.410-411.661.

[21] Yuan H, Li YL, Zhao GL, Liu FF, Li FY. Incremental rolling forming process to fabricate surface micro-grooves. IOP Conf. Ser. Mater. Sci. Eng. 2022, 1270, 012033. doi:10.1088/1757-899X/1270/1/012033.

[22] Liu Y, Min J, Zhang J, Cai W, Carlson BE, Bobel AC, et al. Laser-assisted robotic roller forming of an ultrahigh strength martensitic steel. J. Manuf. Process. 2022, 82, 192-202. doi:10.1016/j.jmapro.2022.07.066.

[23] Min J, Wang J, Lian J, Liu Y, Hou Z. Laser-Assisted Robotic Roller Forming of Ultrahigh-Strength Steel QP 1180 with High Precision. Materials 2023, 16, 1026. doi:10.3390/ma16031026.

[24] DebRoy T, Wei HL, Zuback JS, Mukherjee T, Elmer JW, Milewski JO, et al. Additive manufacturing of metallic components—Process, structure and properties. Prog. Mater. Sci. 2018, 92, 112-224. doi:10.1016/j.pmatsci.2017.10.001.

[25] Liu Y.Investigation on the Microstructure Evolution and Multi-Field Coupling Simulation of Laser assisted Roller Forming of Martensitic Steels. Doctoral Dissertation. School of Mechanical Engineering, Tongji University, Shanghai, China, 2024.

[26] The Numerical Challenges in Multiphysical Modeling of Laser Welding with ALE, (n.d.).Available online: accessed on 8 July 2025).

[27] Yang J, Sun S, Brandt M, Yan W. Experimental investigation and 3D finite element prediction of the heat affected zone during laser assisted machining of Ti6Al4V alloy. J. Mater. Process. Technol. 2010, 210, 2215-2222. doi:10.1016/j.jmatprotec.2010.08.007.

[28] Goldak J, Chakravarti A, Bibby M. A new finite element model for welding heat sources. Met. Trans. B 1984, 15, 299-305. doi:10.1007/BF02667333.

[29] Liu Y, Wang J, Cai W, Carlson BE, Lian J, Min J. A thermo-metallurgical-mechanical model for microstructure evolution in laser-assisted robotic roller forming of ultrahigh strength martensitic steel. J. Mater. Res. Technol. 2023, 25, 451-464. doi:10.1016/j.jmrt.2023.05.228.

[30] Xu J, Li Z-J, Dai H-L. Thermal behavior analysis of UHSS rectangular plates via gradient thermoforming process under coupled heat conduction and radiation. Therm. Sci. Eng. Prog. 2024, 47, 102331. doi:10.1016/j.tsep.2023.102331.

[31] Afkhami S, Amraei M, Javaheri V, Ghafouri M, Björk T, Salminen A, et al. Flow and hardening behavior in the heat-affected zone of welded ultra-high strength steels. Weld World 2024, 68, 1001-1016. doi:10.1007/s40194-024-01703-x.

[32] Qiu J, Xu C, Liu Y, Han F, Min J. Experimental investigation on process parameters of laser-assisted robotic roller bending of a thin-walled structure. IOP Conf. Ser. Mater. Sci. Eng. 2024, 1307, 012010. doi:10.1088/1757-899X/1307/1/012010.

[33] Liu Y, Min J, Lin J. Robotic Roller Forming Process and Strategies to Eliminate Geometrical Defect of Edge Waves. In Forming the Future; Daehn G, Cao J, Kinsey B, Tekkaya E, Vivek A, Yoshida Y, Eds.; Springer International Publishing: Cham, Switzerland, 2021; pp. 479-491. doi:10.1007/978-3-030-75381-8_40.

[34] Liu Y, Qiu J, Wang J, Lian J, Hou Z, Min J. An iterative path compensation method for double-sided robotic roller forming of compact thin-walled profiles. Robot. Comput. -Integr. Manuf. 2024, 86, 102689. doi:10.1016/j.rcim.2023.102689.

[35] Li L, Xie H, Zhang T, Pan D, Li X, Chen F, et al. Influence of intermediate roll shifting on strip shape in a CVC-6 tandem cold mill based on a 3D multi-stand FE model. Int. J. Adv. Manuf. Technol. 2022, 121, 4367-4385. doi:10.1007/s00170-022-09529-x.[GoogleScholar]

[36] Darmawan A, Anggono AD, Hamid A. Die design optimization on sheet metal forming with considering the phenomenon of springback to improve product quality. MATEC Web Conf. 2018, 154, 01105. doi:10.1051/matecconf/201815401105.

[37] Hu J, Liu T, Zeng H, Chua MX, Katupitiya J, Wu L. Static Modeling of a Class of Stiffness-Adjustable Snake-like Robots with Gravity Compensation. Robotics 2023, 12, 2. doi:10.3390/robotics12010002.

[38] Hu S, Zhao J, Liu Y. Prediction and Prevention of Edge Waves in Continuous Cold Forming of Thick-Wall High-Strength Welded Pipe. Metals 2025, 15, 455. doi:10.3390/met15040455.

[39] Farzin M, Tehrani MS, Shameli E. Determination of buckling limit of strain in cold roll forming by the finite element analysis. J. Mater. Process. Technol. 2002, 125-126, 626-632. doi:10.1016/S0924-0136(02)00357-6.

[40] Woo YY, Han SW, Hwang TW, Park JY, Moon YH. Characterization of the longitudinal bow during flexible roll forming of steel sheets. J. Mater. Process. Technol. 2018, 252, 782-794. doi:10.1016/j.jmatprotec.2017.10.048.

[41] Zeng G, Li SH, Yu ZQ, Lai XM. Optimization design of roll profiles for cold roll forming based on response surface method. Mater. Des. 2009, 30, 1930-1938. doi:10.1016/j.matdes.2008.09.018.

[42] Liang C, Li S, Liang J, Li J. Method for Controlling Edge Wave Defects of Parts during Roll Forming of High-Strength Steel. Metals 2022, 12, 53. doi:10.3390/met12010053.

[43] Lokhande AM, Nandedkar VM. Effects of Process Parameters And Investigation of Springback Using Finite Element Analysis. Int. J. Recent Dev. Eng. Technol. 2014, 3, 1-5.

[44] Weiss M, Marnette J, Wolfram P, Larranaga J, Hodgson P. Comparison of Bending of Automotive Steels in Roll Forming and in a V-Die. Key Eng. Mater. 2012, 504-506, 797-802. doi:10.4028/www.scientific.net/KEM.504-506.797.

[45] Li Y, Wu Z, Wang D, Nagaumi H, Luo G, Feng Z, et al. Effect of mechanical properties, microstructure and residual stress on the bending springback behavior of high-strength Al-Mg-Si-Cu alloy tubes. J. Mater. Res. Technol. 2024, 28, 3609-3618. doi:10.1016/j.jmrt.2023.12.230.

[46] Badr OM, Rolfe B, Weiss M. Effect of the forming method on part shape quality in cold roll forming high strength Ti-6Al-4V sheet. J. Manuf. Process. 2018, 32, 513-521. doi:10.1016/j.jmapro.2018.03.022.

[47] Liu X, Cao J, Chai X, Liu J, Zhao R, Kong N. Investigation of forming parameters on springback for ultra high strength steel considering Young’s modulus variation in cold roll forming. J. Manuf. Process. 2017, 29, 289-297. doi:10.1016/j.jmapro.2017.08.001.

[48] Sharad G, Nandedkar VM. Spring back in Sheet Metal Bending-A Review. IOSR-JMCE. 2023, 53-56.

[49] Lal RK, Choubey VK, Dwivedi JP, Kumar S. Study of factors affecting Springback in Sheet Metal Forming and Deep Drawing Process. Mater. Today Proc. 2018, 5, 4353-4358. doi:10.1016/j.matpr.2017.12.002.

[50] Badr OM, Rolfe B, Zhang P, Weiss M. Applying a new constitutive model to analyse the springback behaviour of titanium in bending and roll forming. Int. J. Mech. Sci. 2017, 128-129, 389-400. doi:10.1016/j.ijmecsci.2017.05.025.

[51] Chongthairungruang B, Uthaisangsuk V, Suranuntchai S, Jirathearanat S. Springback prediction in sheet metal forming of high strength steels. Mater. Des. 2013, 50, 253-266. doi:10.1016/j.matdes.2013.02.060.

[52] Gisario A, Barletta M, Conti C, Guarino S. Springback control in sheet metal bending by laser-assisted bending: Experimental analysis, empirical and neural network modelling. Opt. Lasers Eng. 2011, 49, 1372-1383. doi:10.1016/j.optlaseng.2011.07.010.

[53] Gisario A, Barletta M, Venettacci S. Improvements in springback control by external force laser-assisted sheet bending of titanium and aluminum alloys. Opt. Laser Technol. 2016, 86, 46-53. doi:10.1016/j.optlastec.2016.06.013.

[54] Grèze R, Manach PY, Laurent H, Thuillier S, Menezes LF. Influence of the temperature on residual stresses and springback effect in an aluminium alloy. Int. J. Mech. Sci. 2010, 52, 1094-1100. doi:10.1016/j.ijmecsci.2010.04.008.

[55] Racz S-G, Crenganiș M, Breaz R-E, Bârsan A, Gîrjob C-E, Biriș C-M, et al. Integrating Trajectory Planning with Kinematic Analysis and Joint Torques Estimation for an Industrial Robot Used in Incremental Forming Operations. Machines 2022, 10, 531. doi:10.3390/machines10070531.

[56] Dumas C, Caro S, Garnier S, Furet B. Joint stiffness identification of six-revolute industrial serial robots. Robot. Comput. -Integr. Manuf. 2011, 27, 881-888. doi:10.1016/j.rcim.2011.02.003.

[57] Wu K, Li J, Zhao H, Zhong Y. Review of Industrial Robot Stiffness Identification and Modelling. Appl. Sci. 2022, 12, 8719. doi:10.3390/app12178719.

[58] Huang X, Kong L, Dong G. Modeling and Compensation of Motion Errors for 6-DOF Robotic Manipulators. Appl. Sci. 2021, 11, 10100. doi:10.3390/app112110100.

[59] Lin J, Li Y, Xie Y, Hu J, Min J. Joint stiffness identification of industrial serial robots using 3D digital image correlation techniques. Proc. Inst. Mech. Eng. Part C J. Mech. Eng. Sci. 2022, 236, 536-551. doi:10.1177/09544062211002878.

[60] Toyohisa S, Masaki U, Yusuke F. Development of Press Forming Technologies for Ultra-High Strength Steel Sheets Utilizing Computer Aided Engineering. JFE Tech. Rep. 2019, 24, 39-45.

[61] Nishimura R, Tanaka Y, Miyagi T, Ogawa M, Otsuka K, Nakazawa Y. Development of Forming Methods for Functional Improvement of Car Body Structural Parts. Nippon. Steel Tech. Rep. 2019, 122, 13-19.

[62] Liu Y, Wang J, Cai W, Lian J, Carlson BE, Hou Z, et al. Influence of Bending Radius and Heat-Affected Zones on the Bending Performance of High-Strength Thin-Walled Structures Formed by Laser-Assisted Robotic Roller Forming. In Proceedings of the 14th International Conference on the Technology of Plasticity—Current Trends in the Technology of Plasticity; Mocellin K, Bouchard P-O, Bigot R, Balan T, Eds.; Springer Nature: Cham, Switzerland, 2024; pp. 382-391. doi:10.1007/978-3-031-42093-1_37.

[63] Liu Y, Qiu J, Wang J, Bambach M, Min J. Fabrication of thin-walled hat-shaped beams from ultrahigh strength steel by laser-assisted robotic roller forming. Smart Manuf. 2023, 02, 2340001. doi:10.1142/S273754982340001X.

[64] He X, Welo T, Ma J. In-process monitoring strategies and methods in metal forming: A selective review. J. Manuf. Process. 2025, 138, 100-128. doi:10.1016/j.jmapro.2025.02.011.

[65] Mokhtari E, Heidarpour A, Javidan F. Mechanical performance of high strength steel under corrosion: A review study. J. Const. Steel Res. 2024, 220, 108840. doi:10.1016/j.jcsr.2024.108840.

[66] Fajri A, Prabowo AR, Muhayat N, Smaradhana DF, Bahatmaka A. Fatigue Analysis of Engineering Structures: State of Development and Achievement. Procedia Struct. Integr. 2021, 33, 19-26. doi:10.1016/j.prostr.2021.10.004.

[67] Divse V, Dubey A, Deepak M. A 3D FEM-based model of laser heating for selection of process parameters in laser-assisted machining of Ti6Al4V. Res. Squa. 2022. doi:10.21203/rs.3.rs-2051569/v1.

[68] Bargmann S, Klusemann B, Markmann J, Schnabel JE, Schneider K, Soyarslan C, et al. Generation of 3D representative volume elements for heterogeneous materials: A review. Prog. Mater. Sci. 2018, 96, 322-384. doi:10.1016/j.pmatsci.2018.02.003.

[69] Ali M, Porter D, Kömi J, Eissa M, El Faramawy H, Mattar T. Effect of cooling rate and composition on microstructure and mechanical properties of ultrahigh-strength steels. J. Iron Steel Res. Int. 2019, 26, 1350-1365. doi:10.1007/s42243-019-00276-0.

[70] Li FF, Fu MW, Lin JP, Wang XN. Experimental and theoretical study on the hot forming limit of 22MnB5 steel. Int. J. Adv. Manuf. Technol. 2014, 71, 297-306. doi:10.1007/s00170-013-5468-x.

[71] Mandal G, Dey I, Mukherjee S, Ghosh SK. Phase transformation and mechanical properties of ultrahigh strength steels under continuous cooling conditions. J. Mater. Res. Technol. 2022, 19, 628-642. doi:10.1016/j.jmrt.2022.05.033.

[72] Quan G, Zhan Z, Zhang L, Wu D, Luo G, Xia Y. A study on the multi-phase transformation kinetics of ultra-high-strength steel and application in thermal-mechanical-phase coupling simulation of hot stamping process. Mater. Sci. Eng. A 2016, 673, 24-38. doi:10.1016/j.msea.2016.07.010.

[73] He K, Zhao X. 3D Thermal Finite Element Analysis of the SLM 316L Parts with Microstructural Correlations. Complexity 2018, 2018, 6910187. doi:10.1155/2018/6910187.

[74] Tang B, Wang Q, Wei Z, Meng X, Yuan Z. FE Simulation Models for Hot Stamping an Automobile Component with Tailor-Welded High-Strength Steels. J. Mater. Eng. Perform. 2016, 25, 1709-1721. doi:10.1007/s11665-016-2011-x.

[75] Ghafouri M, Ahn J, Mourujärvi J, Björk T, Larkiola J. Finite element simulation of welding distortions in ultra-high strength steel S 960 MC including comprehensive thermal and solid-state phase transformation models. Eng. Struct. 2020, 219, 110804. doi:10.1016/j.engstruct.2020.110804.

[76] Hou Y, Min J, El-Aty AA, Han HN, Lee M-G. A new anisotropic-asymmetric yield criterion covering wider stress states in sheet metal forming. Int. J. Plast. 2023, 166, 103653. doi:10.1016/j.ijplas.2023.103653.

[77] Wang J, Bai Z, Gao Y, Shi Z, Guo Z, Li X. Study on Contact Characteristics of Cold Rolled Deformation Zone of Ultra-High-Strength Steel. Metals 2025, 15, 311. doi:10.3390/met15030311.

[78] Trondl A, Sun D-Z.Modelling of Strain-Rate Dependence of Deformation and Damage Behavior of HSS- and UHSS at Different Loading States. 2015. Available online: accessed on 9 July 2025).

[79] Priest J, Ghadbeigi H, Ayvar-Soberanis S, Liljerehn A, Way M. A modified Johnson-Cook constitutive model for improved thermal softening prediction of machining simulations in C 45 steel. Procedia CIRP 2022, 108, 106-111. doi:10.1016/j.procir.2022.03.022.

[80] Donadon MV, Bressan JD. Application of Barlat’s Yld 2000-2d Yield Criterion to Predict the Anisotropic Response of Stainless Steel. In Forming the Future; Daehn G, Cao J, Kinsey B, Tekkaya E, Vivek A, Yoshida Y, Eds.; Springer International Publishing: Cham, Switzerland, 2021; pp. 749-761. doi:10.1007/978-3-030-75381-8_62.

[81] Li D-H, Shang D-G, Li Z-G, Wang J-J, Hui J, Liu X-D, et al. Unified viscoplastic constitutive model under axial-torsional thermo-mechanical cyclic loading. Int. J. Mech. Sci. 2019, 150, 90-102. doi:10.1016/j.ijmecsci.2018.09.046.

[82] Castillo JI, Celentano DJ, Cruchaga MA, García-Herrera CM. Characterization of strain rate effects in sheet laser forming. Comptes Rendus Mécanique 2018, 346, 794-805. doi:10.1016/j.crme.2018.05.001.

[83] Song J, Jang I, Gwak S, Noh W, Lee J, Bae G, et al. Effect of Pulsed Currents on the Springback Reduction of Ultra-High Strength Steels. Procedia Eng. 2017, 207, 359-364. doi:10.1016/j.proeng.2017.10.788.

[84] Bidabadi BS, Naeini HM, Tafti RA, Tajik Y. Optimization of required torque and energy consumption in the roll forming process. Int. J. Interact. Des. Manuf. 2019, 13, 1029-1048. doi:10.1007/s12008-019-00564-9.

[85] Bammer F. Optimized Heat Distributions for Laser-Assisted Forming. J. Eng. 2024, 2024, 9470839. doi:10.1155/2024/9470839.

[86] Farshidianfar MH, Khajepouhor A, Gerlich A. Real-time monitoring and prediction of martensite formation and hardening depth during laser heat treatment. Surf. Coat. Technol. 2017, 315, 326-334. doi:10.1016/j.surfcoat.2017.02.055.

[87] Zhang X, Zhou L, Feng G, Xi K, Algadi H, Dong M. Laser technologies in manufacturing functional materials and applications of machine learning-assisted design and fabrication. Adv. Compos. Hybrid. Mater. 2024, 8, 76. doi:10.1007/s42114-024-01154-4.

[88] Wei Z, Cao J, Cheng J, Wang X, Zhu H, Zhu X, et al. Precise local deformation control for UHSS thin-walled component in roll forming. J. Manuf. Process. 2024, 112, 302-312. doi:10.1016/j.jmapro.2024.01.017.

[89] Jiang H, Yang Z, Guo Z, Hou J, Lei Z, Bai R, et al. Interpretation of mechanical properties gradient in laser-welded joints: Experiments and grain morphology-dependent crystal plasticity modeling. J. Mater. Res. Technol. 2024, 33, 5934-5950. doi:10.1016/j.jmrt.2024.10.226.

[90] Cao Y, Zhao L, Peng Y, Song L, Zhong M, Ma C, et al. Microstructure and Mechanical Properties of Simulated Heat Affected Zone of Laser Welded Medium-Mn Steel. ISIJ Int. 2020, 60, 2266-2275. doi:10.2355/isijinternational.ISIJINT-2019-716.

[91] Xue J, Peng P, Guo W, Xia M, Tan C, Wan Z, et al. HAZ Characterization and Mechanical Properties of QP980-DP 980 Laser Welded Joints. Chin. J. Mech. Eng. 2021, 34, 80. doi:10.1186/s10033-021-00596-x.

[92] Dong W, Bao L, Li W, Shin K, Han C. Effects of Laser Forming on the Mechanical Properties and Microstructure of DP 980 Steel. Materials 2022, 15, 7581. doi:10.3390/ma15217581.

[93] Singh R, Alberts MJ, Melkote SN. Characterization and prediction of the heat-affected zone in a laser-assisted mechanical micromachining process. Int. J. Mach. Tools Manuf. 2008, 48, 994-1004. doi:10.1016/j.ijmachtools.2008.01.004.

[94] Chowdhury MN, Kim J, Hong S, Jung J, Han H, So S. Tailoring of Mechanical Properties of Indirect Hot Stamping Steel Tubes by Laser Assisted Local Rapid Heating. J. Iron. Steel Res. Int. 2016, 23, 949-954. doi:10.1016/S1006-706X(16)30143-1.

[95] Han J, Lee Y-K. The effects of the heating rate on the reverse transformation mechanism and the phase stability of reverted austenite in medium Mn steels. Acta Mater. 2014, 67, 354-361. doi:10.1016/j.actamat.2013.12.038.

[96] Arulvel S, Jain A, Kandasamy J, Singhal M. Laser processing techniques for surface property enhancement: Focus on material advancement. Surf. Interfaces 2023, 42, 103293. doi:10.1016/j.surfin.2023.103293.

[97] Aboulkhair NT, Maskery I, Tuck C, Ashcroft I, Everitt NM. Improving the fatigue behaviour of a selectively laser melted aluminium alloy: Influence of heat treatment and surface quality. Mater. Des. 2016, 104, 174-182. doi:10.1016/j.matdes.2016.05.041.

[98] Lee S, Ahmadi Z, Pegues JW, Mahjouri-Samani M, Shamsaei N. Laser polishing for improving fatigue performance of additive manufactured Ti-6Al-4V parts. Opt. Laser Technol. 2021, 134, 106639. doi:10.1016/j.optlastec.2020.106639.

[99] Lu YJ, Zhang ZL, Liu YJ, Yu C, Zhang X, Liu XC. Improving mechanical properties and corrosion behavior of biomedical Ti-3Zr-2Sn-3Mo-25Nb alloy through laser surface remelting. Surf. Coat. Technol. 2024, 490, 131135. doi:10.1016/j.surfcoat.2024.131135.

[100] Liang H, Liu J, Sun L, Hou J, Cao Z. Optimization of the Forming Quality of a Laser-Cladded AlCrFeNiW0.2 High-Entropy Alloy Coating. Coatings 2023, 13, 1744. doi:10.3390/coatings13101744.

[101] Karamimoghadam M, Rezayat M, Moradi M, Mateo A, Casalino G. Laser Surface Transformation Hardening for Automotive Metals: Recent Progress. Metals 2024, 14, 339. doi:10.3390/met14030339.

[102] Rashid RAR, Nazari KA, Barr C, Palanisamy S, Orchowski N, Matthews N, et al. Effect of laser reheat post-treatment on the microstructural characteristics of laser-cladded ultra-high strength steel. Surf. Coat. Technol. 2019, 372, 93-102. doi:10.1016/j.surfcoat.2019.05.021.

[103] Wang Z, Dirrenberger J, Lapouge P, Dubent S. Laser treatment of 430 ferritic stainless steel for enhanced mechanical properties. Mater. Sci. Eng. A 2022, 831, 142205. doi:10.1016/j.msea.2021.142205.

[104] Stewens T, Liu Y, Wang L, Min J. An analytical model for the tool center point placement in Robotic Roller Forming. Comput. Methods Mater. Sci. 2024, 24, 39-48. doi:10.7494/cmms.2024.2.0838.

[105] Seyedkashi SMH, Gollo MH, Biao J, Moon YH. Laser bendability of SUS430/C11000/SUS430 laminated composite and its constituent layers. Met. Mater. Int. 2016, 22, 527-534. doi:10.1007/s12540-016-5711-8.

[106] Safari M, Mostaan H, Farzin M. Laser bending of tailor machined blanks: Effect of start point of scan path and irradiation direction relation to step of the blank. Alex. Eng. J. 2016, 55, 1587-1594. doi:10.1016/j.aej.2016.01.010.

[107] Kotobi M, Honarpisheh M. Through-depth residual stress measurement of laser bent steel-titanium bimetal sheets. J. Strain Anal. Eng. Des. 2018, 53, 130-140. doi:10.1177/0309324717753212.

[108] Safari M, Ebrahimi M. Numerical Investigation of Laser Bending of Perforated Sheets. Int. J. Adv. Des. Manuf. Technol. 2016, 9, 53-60.

[109] Dixit US, Fetene BN. A finite element modelling of laser bending of friction stir welded aluminium 5052-H 32 sheets. Int. J. Mechatron. Manuf. Syst. 2016, 9, 215-236. doi:10.1504/IJMMS.2016.079589.

[110] Kant R, Joshi SN. Thermo-mechanical studies on bending mechanism, bend angle and edge effect during multi-scan laser bending of magnesium M1A alloy sheets. J. Manuf. Process. 2016, 23, 135-148. doi:10.1016/j.jmapro.2016.05.017.

[111] Naqvi SMR, Haidry AA, Xie D, Ahmad S, Liu Y, Chen Y, et al. Influence of laser beam process parameters on the bending ability of Ti-6Al-4V titanium alloy sheets. Int. J. Adv. Manuf. Technol. 2024, 133, 3445-3460. doi:10.1007/s00170-024-13903-2.

[112] Yazici C, Domínguez-Gutiérrez FJ. Machine learning techniques for estimating high-temperature mechanical behavior of high strength steels. Results Eng. 2025, 25, 104242. doi:10.1016/j.rineng.2025.104242.

[113] Pantalé O, Mha PT, Tongne A. Efficient implementation of non-linear flow law using neural network into the Abaqus Explicit FEM code. Finite Elem. Anal. Des. 2022, 198, 103647. doi:10.1016/j.finel.2021.103647.

[114] Panthi SK, Ramakrishnan N, Ahmed M, Singh SS, Goel MD. Finite Element Analysis of sheet metal bending process to predict the springback. Mater. Des. 2010, 31, 657-662. doi:10.1016/j.matdes.2009.08.022.

[115] Adzima F, Balan T, Manach PY. Springback prediction for a mechanical micro connector using CPFEM based numerical simulations. Int. J. Mater. Form. 2020, 13, 649-659. doi:10.1007/s12289-019-01503-5.

[116] Adzima F, Balan T, Manach PY, Bonnet N, Tabourot L. Crystal plasticity and phenomenological approaches for the simulation of deformation behavior in thin copper alloy sheets. Int. J. Plast. 2017, 94, 171-191. doi:10.1016/j.ijplas.2016.06.003.

[117] Brahme A, Alvi MH, Saylor D, Fridy J, Rollett AD. 3D reconstruction of microstructure in a commercial purity aluminum. Scr. Mater. 2006, 55, 75-80. doi:10.1016/j.scriptamat.2006.02.017.

[118] Park T, Hector LG, Hu X, Abu-Farha F, Fellinger MR, Kim H, et al. Crystal plasticity modeling of 3rd generation multi-phase AHSS with martensitic transformation. Int. J. Plast. 2019, 120, 1-46. doi:10.1016/j.ijplas.2019.03.010.

[119] Zaikovska L, Ekh M, Gupta M, Moverare J. Three-Dimensional Non-Homogeneous Microstructure Representation Using 2D Electron Backscatter Diffraction Data for Additive-Manufactured Hastelloy X. Materials 2024, 17, 5937. doi:10.3390/ma17235937.

[120] Azhari F, Wallbrink C, Sterjovski Z, Crawford BR, Menzel A, Agius D, et al. Predicting the complete tensile properties of additively manufactured Ti-6Al-4V by integrating three-dimensional microstructure statistics with a crystal plasticity model. Int. J. Plast. 2022, 148, 103127. doi:10.1016/j.ijplas.2021.103127.

[121] Gao Z, Zhu C, Wang C, Shu Y, Liu S, Miao J, et al. Advanced deep learning framework for multi-scale prediction of mechanical properties from microstructural features in polycrystalline materials. Comput. Methods Appl. Mech. Eng. 2025, 438, 117844. doi:10.1016/j.cma.2025.117844.

[122] Liu Z, Hou Y, He R, Ye Y, Niu C, Min J. Machine learning for extending capability of mechanical characterization to improve springback prediction of a quenching and partitioning steel. J. Mater. Process. Technol. 2022, 308, 117737. doi:10.1016/j.jmatprotec.2022.117737.

[123] Belitzki A, Stadter C, Zaeh MF. Distortion minimization of laser beam welded components by the use of finite element simulation and Artificial Intelligence. CIRP J. Manuf. Sci. Technol. 2019, 27, 11-20. doi:10.1016/j.cirpj.2019.10.001.