El-Said Salah, Rania Mostafa, M. M. Tawfik, Montasser Dewidar
{"title":"激光成形技术:全面检讨的机制,工艺优化,和工业应用","authors":"El-Said Salah, Rania Mostafa, M. M. Tawfik, Montasser Dewidar","doi":"10.1007/s12289-025-01943-2","DOIUrl":null,"url":null,"abstract":"<div><p>Laser forming (LF) is an advanced non-contact manufacturing technique that utilizes laser energy to induce controlled thermal expansion and plastic deformation in metal sheets, enabling the shaping of high-strength and brittle materials with minimal residual stresses. The effectiveness of LF is governed by three primary mechanisms Temperature Gradient Mechanism (TGM), Buckling Mechanism (BM), and Upsetting Mechanism (UM)) which are influenced by process parameters such as laser power, scanning speed, beam diameter, and material properties. This review presents a comprehensive overview of recent advancements in LF, beginning with an analysis of the governing deformation mechanisms and their role in achieving precision and control. It then explores critical microstructural changes including grain refinement, phase transformations, and heat-affected zones (HAZ) that directly impact material behavior and performance. Building upon these foundational aspects, the article highlights current innovations in LF process enhancement through machine learning (ML)-based optimization, real-time thermal feedback, and adaptive control strategies. Challenges such as edge effects, residual stresses, and process repeatability are discussed, along with mitigation approaches Like forced cooling and adaptive scanning. Experimental findings show that forced cooling can increase the bending angle by up to 35.2% and improve energy efficiency by 22.14%. The review Further examines the application of computational models such as ANNs, SVMs, and GAs in predicting bend angles and optimizing process parameters. ANN-based models, for instance, have achieved prediction accuracies of up to 98.9%. The AI tools offer a holistic perspective on future research directions aimed at enhancing process sustainability and broader industrial adoption.</p></div>","PeriodicalId":591,"journal":{"name":"International Journal of Material Forming","volume":"18 4","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12289-025-01943-2.pdf","citationCount":"0","resultStr":"{\"title\":\"Laser forming technology: a comprehensive review of mechanisms, process optimization, and industrial applications\",\"authors\":\"El-Said Salah, Rania Mostafa, M. M. 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It then explores critical microstructural changes including grain refinement, phase transformations, and heat-affected zones (HAZ) that directly impact material behavior and performance. Building upon these foundational aspects, the article highlights current innovations in LF process enhancement through machine learning (ML)-based optimization, real-time thermal feedback, and adaptive control strategies. Challenges such as edge effects, residual stresses, and process repeatability are discussed, along with mitigation approaches Like forced cooling and adaptive scanning. Experimental findings show that forced cooling can increase the bending angle by up to 35.2% and improve energy efficiency by 22.14%. The review Further examines the application of computational models such as ANNs, SVMs, and GAs in predicting bend angles and optimizing process parameters. ANN-based models, for instance, have achieved prediction accuracies of up to 98.9%. The AI tools offer a holistic perspective on future research directions aimed at enhancing process sustainability and broader industrial adoption.</p></div>\",\"PeriodicalId\":591,\"journal\":{\"name\":\"International Journal of Material Forming\",\"volume\":\"18 4\",\"pages\":\"\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2025-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s12289-025-01943-2.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Material Forming\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s12289-025-01943-2\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, MANUFACTURING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Material Forming","FirstCategoryId":"88","ListUrlMain":"https://link.springer.com/article/10.1007/s12289-025-01943-2","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
Laser forming technology: a comprehensive review of mechanisms, process optimization, and industrial applications
Laser forming (LF) is an advanced non-contact manufacturing technique that utilizes laser energy to induce controlled thermal expansion and plastic deformation in metal sheets, enabling the shaping of high-strength and brittle materials with minimal residual stresses. The effectiveness of LF is governed by three primary mechanisms Temperature Gradient Mechanism (TGM), Buckling Mechanism (BM), and Upsetting Mechanism (UM)) which are influenced by process parameters such as laser power, scanning speed, beam diameter, and material properties. This review presents a comprehensive overview of recent advancements in LF, beginning with an analysis of the governing deformation mechanisms and their role in achieving precision and control. It then explores critical microstructural changes including grain refinement, phase transformations, and heat-affected zones (HAZ) that directly impact material behavior and performance. Building upon these foundational aspects, the article highlights current innovations in LF process enhancement through machine learning (ML)-based optimization, real-time thermal feedback, and adaptive control strategies. Challenges such as edge effects, residual stresses, and process repeatability are discussed, along with mitigation approaches Like forced cooling and adaptive scanning. Experimental findings show that forced cooling can increase the bending angle by up to 35.2% and improve energy efficiency by 22.14%. The review Further examines the application of computational models such as ANNs, SVMs, and GAs in predicting bend angles and optimizing process parameters. ANN-based models, for instance, have achieved prediction accuracies of up to 98.9%. The AI tools offer a holistic perspective on future research directions aimed at enhancing process sustainability and broader industrial adoption.
期刊介绍:
The Journal publishes and disseminates original research in the field of material forming. The research should constitute major achievements in the understanding, modeling or simulation of material forming processes. In this respect ‘forming’ implies a deliberate deformation of material.
The journal establishes a platform of communication between engineers and scientists, covering all forming processes, including sheet forming, bulk forming, powder forming, forming in near-melt conditions (injection moulding, thixoforming, film blowing etc.), micro-forming, hydro-forming, thermo-forming, incremental forming etc. Other manufacturing technologies like machining and cutting can be included if the focus of the work is on plastic deformations.
All materials (metals, ceramics, polymers, composites, glass, wood, fibre reinforced materials, materials in food processing, biomaterials, nano-materials, shape memory alloys etc.) and approaches (micro-macro modelling, thermo-mechanical modelling, numerical simulation including new and advanced numerical strategies, experimental analysis, inverse analysis, model identification, optimization, design and control of forming tools and machines, wear and friction, mechanical behavior and formability of materials etc.) are concerned.