Pub Date : 2024-05-15DOI: 10.21741/9781644903131-42
Sarra Oueslati
Abstract. Wire Arc Additive Manufacturing (WAAM) is a promising process for producing medium to large scale metallic parts at a low cost and with a high deposition rate. However, the multitude of process parameters and physical phenomena involved makes it complex and hard to master. Therefore, monitoring the process becomes crucial for unraveling complexities and attaining a more profound comprehension of the intricacies inherent in WAAM, hence ensuring process stability. In order to produce a defect-free part, while keeping a stable process, the operating parameters must be carefully selected. Nonetheless, one of the significant hurdles in WAAM is the variability of the deposited layers height. The accumulation of these geometrical inaccuracies induces instabilities in the process which results into the appearing of defects on the deposited part. The aim of this study is to investigate the correlations between process instabilities and electrical signals obtained by a deposition monitoring system. A monitoring criterion is then extracted from experimental data. Correlation with instabilities will be confirmed using a thermal camera.
{"title":"Multi-sensor in process monitoring for WAAM: Detection of process instability in electrical signals","authors":"Sarra Oueslati","doi":"10.21741/9781644903131-42","DOIUrl":"https://doi.org/10.21741/9781644903131-42","url":null,"abstract":"Abstract. Wire Arc Additive Manufacturing (WAAM) is a promising process for producing medium to large scale metallic parts at a low cost and with a high deposition rate. However, the multitude of process parameters and physical phenomena involved makes it complex and hard to master. Therefore, monitoring the process becomes crucial for unraveling complexities and attaining a more profound comprehension of the intricacies inherent in WAAM, hence ensuring process stability. In order to produce a defect-free part, while keeping a stable process, the operating parameters must be carefully selected. Nonetheless, one of the significant hurdles in WAAM is the variability of the deposited layers height. The accumulation of these geometrical inaccuracies induces instabilities in the process which results into the appearing of defects on the deposited part. The aim of this study is to investigate the correlations between process instabilities and electrical signals obtained by a deposition monitoring system. A monitoring criterion is then extracted from experimental data. Correlation with instabilities will be confirmed using a thermal camera.","PeriodicalId":515987,"journal":{"name":"Materials Research Proceedings","volume":"15 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140974061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-15DOI: 10.21741/9781644903131-54
Z. Liu
Abstract. This paper illustrates the thermoforming process carried out on thermoplastic polymer and magnesium-based fiber metal laminates (FMLs). Flat laminates were formed at elevated temperatures into a hat-shape part. The forming force was acquired and, after forming, the thickness of each constituent of the FMLs in different zones was measured. A non-uniform thickness distribution was found in the formed parts, with a significant reduction of the prepreg thickness at the part bottom radii. Moreover, it was observed that the higher the blank-holder force the higher the forming force and the more significant the prepreg thickness variation.
{"title":"Forming of thermoplastic polymer and magnesium alloy-based fiber metal laminates at elevated temperatures","authors":"Z. Liu","doi":"10.21741/9781644903131-54","DOIUrl":"https://doi.org/10.21741/9781644903131-54","url":null,"abstract":"Abstract. This paper illustrates the thermoforming process carried out on thermoplastic polymer and magnesium-based fiber metal laminates (FMLs). Flat laminates were formed at elevated temperatures into a hat-shape part. The forming force was acquired and, after forming, the thickness of each constituent of the FMLs in different zones was measured. A non-uniform thickness distribution was found in the formed parts, with a significant reduction of the prepreg thickness at the part bottom radii. Moreover, it was observed that the higher the blank-holder force the higher the forming force and the more significant the prepreg thickness variation.","PeriodicalId":515987,"journal":{"name":"Materials Research Proceedings","volume":"2 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140974553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-15DOI: 10.21741/9781644903131-250
M. Sitko
Abstract. Predicting microstructure morphology evolution under hot forming conditions and determining final material properties are essential for optimizing metal-forming processes. Cellular Automata (CA) is a widely employed full-field method for modeling microstructure morphology changes during various metal-forming processes. However, at higher temperatures and under conditions of substantial microstructure evolution, the CA method encounters limitations related to computational domain geometry changes. The use of random cellular automata (RCA) offers a more realistic representation of this phenomenon, although it requires additional effort in algorithm optimization for acceptable execution times. This paper contributes to an overarching research effort focused on developing a discontinuous dynamic recrystallization model (DRX) by directly incorporating RCA into the finite element (FE) framework. Different mesh sizes and their impact on the quality of the results are analyzed, and the minimum number of elements that do not degrade the results in the CA model are selected. The investigation aims to enhance the practicality of the proposed model, striking a balance between realistic microstructure representation and computational efficiency.
摘要。预测热成形条件下的微观结构形态演变并确定最终材料性能对于优化金属成形工艺至关重要。细胞自动机（CA）是一种广泛应用的全场方法，用于模拟各种金属成型过程中的微观结构形态变化。然而，在温度较高和微观结构发生重大演变的条件下，CA 方法会遇到与计算域几何形状变化有关的限制。使用随机蜂窝自动机 (RCA) 可以更真实地反映这种现象，但需要额外的算法优化工作，以获得可接受的执行时间。本文通过直接将 RCA 纳入有限元（FE）框架，为开发非连续动态再结晶模型（DRX）的总体研究工作做出了贡献。本文分析了不同的网格尺寸及其对结果质量的影响，并选择了不会降低 CA 模型结果的最小元素数量。该研究旨在提高拟议模型的实用性，在真实的微观结构表示和计算效率之间取得平衡。
{"title":"Mesh sensitivity study in the random cellular automata finite element model of dynamic recrystallization","authors":"M. Sitko","doi":"10.21741/9781644903131-250","DOIUrl":"https://doi.org/10.21741/9781644903131-250","url":null,"abstract":"Abstract. Predicting microstructure morphology evolution under hot forming conditions and determining final material properties are essential for optimizing metal-forming processes. Cellular Automata (CA) is a widely employed full-field method for modeling microstructure morphology changes during various metal-forming processes. However, at higher temperatures and under conditions of substantial microstructure evolution, the CA method encounters limitations related to computational domain geometry changes. The use of random cellular automata (RCA) offers a more realistic representation of this phenomenon, although it requires additional effort in algorithm optimization for acceptable execution times. This paper contributes to an overarching research effort focused on developing a discontinuous dynamic recrystallization model (DRX) by directly incorporating RCA into the finite element (FE) framework. Different mesh sizes and their impact on the quality of the results are analyzed, and the minimum number of elements that do not degrade the results in the CA model are selected. The investigation aims to enhance the practicality of the proposed model, striking a balance between realistic microstructure representation and computational efficiency.","PeriodicalId":515987,"journal":{"name":"Materials Research Proceedings","volume":"138 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140977013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-15DOI: 10.21741/9781644903131-156
D. Dobras
Abstract. Electricity-assisted forming processes can significantly improve material ductility and process efficiency. However, further research into different strain conditions is necessary, for example, in stamping processes. In this study, tensile and deep drawing tests of the 5754 aluminium alloy were carried out with the application of current pulses on a specially constructed experimental setup. The study showed that it is possible to increase the plasticity of the material. The main cause responsible for the increase in plasticity was dynamic recovery.
{"title":"Electrically-assisted forming of 5754 aluminium alloy under different strain conditions","authors":"D. Dobras","doi":"10.21741/9781644903131-156","DOIUrl":"https://doi.org/10.21741/9781644903131-156","url":null,"abstract":"Abstract. Electricity-assisted forming processes can significantly improve material ductility and process efficiency. However, further research into different strain conditions is necessary, for example, in stamping processes. In this study, tensile and deep drawing tests of the 5754 aluminium alloy were carried out with the application of current pulses on a specially constructed experimental setup. The study showed that it is possible to increase the plasticity of the material. The main cause responsible for the increase in plasticity was dynamic recovery.","PeriodicalId":515987,"journal":{"name":"Materials Research Proceedings","volume":"19 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140976033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-15DOI: 10.21741/9781644903131-253
Nikhil Vijay Jagtap
Abstract. This paper presents a data-driven approach to predict the material displacement in open die forging using neural networks. Training data for different process parameters and workpiece geometries is generated using finite element simulations. A neural network architecture is designed that takes the process parameters and the coordinates of a point in the geometry as inputs and outputs the displacement of that point after the deformation. This is systematically implemented for open die forging, using relevant process information. The neural network model is trained and tested on various FEA-simulations for different process parameters and shows good accuracy and generalization. The model is also able to simulate multiple strokes of a single pass in a fast and efficient way. It is demonstrated how the neural network model can enable building a digital material shadow of open die forging processes. The advantages and limitations of the approach are then further discussed.
{"title":"Fast prediction of the material displacement in open die forging using neural networks","authors":"Nikhil Vijay Jagtap","doi":"10.21741/9781644903131-253","DOIUrl":"https://doi.org/10.21741/9781644903131-253","url":null,"abstract":"Abstract. This paper presents a data-driven approach to predict the material displacement in open die forging using neural networks. Training data for different process parameters and workpiece geometries is generated using finite element simulations. A neural network architecture is designed that takes the process parameters and the coordinates of a point in the geometry as inputs and outputs the displacement of that point after the deformation. This is systematically implemented for open die forging, using relevant process information. The neural network model is trained and tested on various FEA-simulations for different process parameters and shows good accuracy and generalization. The model is also able to simulate multiple strokes of a single pass in a fast and efficient way. It is demonstrated how the neural network model can enable building a digital material shadow of open die forging processes. The advantages and limitations of the approach are then further discussed.","PeriodicalId":515987,"journal":{"name":"Materials Research Proceedings","volume":"142 29","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140976459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-15DOI: 10.21741/9781644903131-255
Mina Ghobrial
Abstract. In the rapidly evolving landscape of manufacturing and material forming, innovative strategies are imperative for maintaining a competitive edge. Augmented Reality (AR) has emerged as a groundbreaking technology, offering new dimensions in how information is displayed and interacted with. It holds particular promise in the panel of instructional guides for complex machinery, potentially enhance traditional methods of knowledge transfer and operator training. Material forming, a key discipline within mechanical engineering, requires high-precision and skill, making it an ideal candidate for the integration of advanced instructional technologies like AR. This study aims to explore the efficiency of three distinct types of user manuals—video, paper, and augmented reality (AR)—on performance and acceptability in a material forming workshop environment. The focus will be on how AR can be specifically applied to improve task execution and understanding in material forming operations. Participants are mechanical engineering students specializing in material forming. They will engage in a series of standardized tasks related to machining processes. Performance will be gauged by metrics like task completion time and error rates, while task load will be assessed via the NASA Task Load Index (NASA-TLX) [1]. Acceptability of each manual type will be evaluated using the System Usability Scale (SUS) [2]. By comparing these various instructional formats, this research seeks to shed light on the most effective mediums for enhancing both operator performance and experience.
摘要在快速发展的制造和材料成型领域，创新战略是保持竞争优势的当务之急。增强现实技术（AR）已成为一项突破性技术，为信息的显示和交互方式提供了新的维度。它在为复杂机械提供指导面板方面大有可为，有可能加强传统的知识传授和操作员培训方法。材料成型是机械工程中的一门关键学科，需要高精度和高技能，因此是集成 AR 等先进教学技术的理想选择。本研究旨在探索三种不同类型的用户手册（视频、纸质和增强现实（AR））在材料成型车间环境中对性能和可接受性的影响。重点将放在如何具体应用 AR 来改进材料成型操作中的任务执行和理解。参与者是材料成型专业的机械工程学生。他们将参与一系列与加工过程相关的标准化任务。任务完成时间和错误率等指标将衡量任务执行情况，而任务负荷将通过 NASA 任务负荷指数（NASA-TLX）[1] 进行评估。每种手册类型的可接受性将使用系统可用性量表 (SUS) [2] 进行评估。通过比较这些不同的教学形式，本研究试图揭示提高操作员绩效和经验的最有效媒介。
{"title":"Effectiveness of machining equipment user guides: A comparative study of augmented reality and traditional media","authors":"Mina Ghobrial","doi":"10.21741/9781644903131-255","DOIUrl":"https://doi.org/10.21741/9781644903131-255","url":null,"abstract":"Abstract. In the rapidly evolving landscape of manufacturing and material forming, innovative strategies are imperative for maintaining a competitive edge. Augmented Reality (AR) has emerged as a groundbreaking technology, offering new dimensions in how information is displayed and interacted with. It holds particular promise in the panel of instructional guides for complex machinery, potentially enhance traditional methods of knowledge transfer and operator training. Material forming, a key discipline within mechanical engineering, requires high-precision and skill, making it an ideal candidate for the integration of advanced instructional technologies like AR. This study aims to explore the efficiency of three distinct types of user manuals—video, paper, and augmented reality (AR)—on performance and acceptability in a material forming workshop environment. The focus will be on how AR can be specifically applied to improve task execution and understanding in material forming operations. Participants are mechanical engineering students specializing in material forming. They will engage in a series of standardized tasks related to machining processes. Performance will be gauged by metrics like task completion time and error rates, while task load will be assessed via the NASA Task Load Index (NASA-TLX) [1]. Acceptability of each manual type will be evaluated using the System Usability Scale (SUS) [2]. By comparing these various instructional formats, this research seeks to shed light on the most effective mediums for enhancing both operator performance and experience.","PeriodicalId":515987,"journal":{"name":"Materials Research Proceedings","volume":"59 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140973583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-15DOI: 10.21741/9781644903131-207
Greta Seneci
Abstract. This work deals with the modeling of micro-milling processes by considering the phenomena generated by the transition from conventional size to the micro-scale machining. The concomitant effects of different cutting regimes, and the deviation of the cutting edges from their theoretical trajectories due to tool run-out, are important aspects to be considered during the process modeling. Several models are available in literature to describe how ploughing and shearing regimes influence cutting forces and how the tool run-out impacts on the actual chip thickness. In a previous authors research, a comprehensive model was published achieving a good agreement with the experimental data, but its calibration requires the measurement of the width of the micro-milled slots. This practice is time consuming and subjected to experimental errors, while a calibration of the model based only on the elaboration of the cutting force signal appears a promising strategy. Starting from the mathematical description of the geometrical model, a new equation to compute the tool run-out parameters was found. The parameters depend on eight variables that must be calculated from tool geometry, material composition, cutting parameters and the cutting force signal. An experimental procedure was developed to compare the prediction achieved by the new method and the conventional technique.
{"title":"An innovative method to model run-out phenomena in micro-milling by using cutting force signal","authors":"Greta Seneci","doi":"10.21741/9781644903131-207","DOIUrl":"https://doi.org/10.21741/9781644903131-207","url":null,"abstract":"Abstract. This work deals with the modeling of micro-milling processes by considering the phenomena generated by the transition from conventional size to the micro-scale machining. The concomitant effects of different cutting regimes, and the deviation of the cutting edges from their theoretical trajectories due to tool run-out, are important aspects to be considered during the process modeling. Several models are available in literature to describe how ploughing and shearing regimes influence cutting forces and how the tool run-out impacts on the actual chip thickness. In a previous authors research, a comprehensive model was published achieving a good agreement with the experimental data, but its calibration requires the measurement of the width of the micro-milled slots. This practice is time consuming and subjected to experimental errors, while a calibration of the model based only on the elaboration of the cutting force signal appears a promising strategy. Starting from the mathematical description of the geometrical model, a new equation to compute the tool run-out parameters was found. The parameters depend on eight variables that must be calculated from tool geometry, material composition, cutting parameters and the cutting force signal. An experimental procedure was developed to compare the prediction achieved by the new method and the conventional technique.","PeriodicalId":515987,"journal":{"name":"Materials Research Proceedings","volume":"7 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140974434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-15DOI: 10.21741/9781644903131-50
Baptiste Lacroix
Abstract. Draping and forming of textile reinforcements are usually performed thanks to finite element models with continuous media assumption. The specific purpose of mesoscale model is to faithfully reproduces defects like yarn buckling or gapping during the process. Such defects are crucial outputs because they have huge impacts on mechanical and permeability properties of the whole textile. However, mesoscopic analysis usually leads to expensive computation cost and needs to be optimized to propose a cost-effective response to this problem. Thus, this document aims to develop a solid-beam approach for mesoscale model, with coarse geometric assumption but with finite element and constitutive law formulation taking into account the fibrous aspect of the fabric.
{"title":"A solid-beam approach for mesoscopic analysis of textile reinforcements forming simulation","authors":"Baptiste Lacroix","doi":"10.21741/9781644903131-50","DOIUrl":"https://doi.org/10.21741/9781644903131-50","url":null,"abstract":"Abstract. Draping and forming of textile reinforcements are usually performed thanks to finite element models with continuous media assumption. The specific purpose of mesoscale model is to faithfully reproduces defects like yarn buckling or gapping during the process. Such defects are crucial outputs because they have huge impacts on mechanical and permeability properties of the whole textile. However, mesoscopic analysis usually leads to expensive computation cost and needs to be optimized to propose a cost-effective response to this problem. Thus, this document aims to develop a solid-beam approach for mesoscale model, with coarse geometric assumption but with finite element and constitutive law formulation taking into account the fibrous aspect of the fabric.","PeriodicalId":515987,"journal":{"name":"Materials Research Proceedings","volume":"16 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140974885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-15DOI: 10.21741/9781644903131-91
A. Gopakumar
Abstract. The shrinkage porosities produced during the casting of steel blooms has to be fixed by the subsequent hot rolling process. To design the rolling route, finite element simulations integrating void closure models are necessary. However, these models have to be validated by experimental results. Because experiments under industrial conditions are hardly achievable, experimental simulations at lower scale can be considered. However, the experiment must be designed so as to reproduce industrial like conditions concerning the thermomechanical loading and microstructure with respect to void closure. Among the main parameters driving void closure are the equivalent plastic strain and the mean triaxiality. This paper is dedicated to the design of an experimental simulator of void closure during hot rolling. The simulator consists of several strokes performed on a sample containing a real shrinkage porosity, between shaped anvils and with alternations of the forming direction.
{"title":"Design of an experimental simulator of void closure during hot rolling process","authors":"A. Gopakumar","doi":"10.21741/9781644903131-91","DOIUrl":"https://doi.org/10.21741/9781644903131-91","url":null,"abstract":"Abstract. The shrinkage porosities produced during the casting of steel blooms has to be fixed by the subsequent hot rolling process. To design the rolling route, finite element simulations integrating void closure models are necessary. However, these models have to be validated by experimental results. Because experiments under industrial conditions are hardly achievable, experimental simulations at lower scale can be considered. However, the experiment must be designed so as to reproduce industrial like conditions concerning the thermomechanical loading and microstructure with respect to void closure. Among the main parameters driving void closure are the equivalent plastic strain and the mean triaxiality. This paper is dedicated to the design of an experimental simulator of void closure during hot rolling. The simulator consists of several strokes performed on a sample containing a real shrinkage porosity, between shaped anvils and with alternations of the forming direction.","PeriodicalId":515987,"journal":{"name":"Materials Research Proceedings","volume":"139 14","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140976458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-15DOI: 10.21741/9781644903131-151
B. Arian
Abstract. In manufacturing, property control ensures efficient part production. However, in reverse flow forming, current practices focus on geometry control rather than property control. To address the complexity of the process and tool machine interaction, process control is crucial for defined component properties. This study focuses on controlling local α’ martensite content in reverse flow forming of seamless AISI 304L steel tubes. Strategies and systems are presented to influence α’ martensite content, creating unique microstructure profiles for 1D and 2D Gradings, with tangible component outcomes.
摘要在制造过程中，属性控制可确保高效的零件生产。然而，在反向流动成形中，目前的做法侧重于几何控制而非属性控制。为了应对工艺和工具机相互作用的复杂性，工艺控制对于确定零件属性至关重要。本研究的重点是控制 AISI 304L 无缝钢管反向流动成形过程中的局部 α' 马氏体含量。研究提出了影响 α' 马氏体含量的策略和系统，为一维和二维分级创造了独特的微观结构剖面，并取得了切实的部件成果。
{"title":"Thermomechanical reverse flow forming of AISI 304L","authors":"B. Arian","doi":"10.21741/9781644903131-151","DOIUrl":"https://doi.org/10.21741/9781644903131-151","url":null,"abstract":"Abstract. In manufacturing, property control ensures efficient part production. However, in reverse flow forming, current practices focus on geometry control rather than property control. To address the complexity of the process and tool machine interaction, process control is crucial for defined component properties. This study focuses on controlling local α’ martensite content in reverse flow forming of seamless AISI 304L steel tubes. Strategies and systems are presented to influence α’ martensite content, creating unique microstructure profiles for 1D and 2D Gradings, with tangible component outcomes.","PeriodicalId":515987,"journal":{"name":"Materials Research Proceedings","volume":"41 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140973398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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