Shenliang Yang, Xiaoliang Jin, S. Engin, Raja Kountanya, Tahany I. El-Wardany
In the machining of high-strength materials, shear localization in serrated chip formation leads to time-varying thermo-mechanical loads exerted by the cutting tool on the machined surface. This results in periodic changes to surface integrity. This paper explains the formation mechanism of machined surface microfeatures and residual stress fluctuations associated with serrated chip formation, based on a finite element model of machining Waspaloy using the coupled Eulerian-Lagrangian method. The model is validated by comparing the simulation results with experimentally measured chip morphologies and machined surface profiles. During machining with a constant chip thickness, the machined surface exhibits a uniformly distributed residual stress pattern along the cutting velocity direction. However, increased cutting velocity and serrated chip formation cause periodic shear bands, leading to time-varying location of the stagnation point on the tool edge. This results in variations in the workpiece material volume and the thermo-mechanical loads in the plowing region. After machining, the periodical variation in the elastic recovery of the plowed material at the bottom of the tool edge creates waveforms on the finished surface, accompanied by fluctuations in residual stress at the same frequency as chip serration. The simulations quantitatively determine the normal/shear contact force at the tool-workpiece interfaces to reveal the effect of the time-varying stagnation point location on surface topographies and residual stress distributions.
{"title":"EFFECT OF SHEAR LOCALIZATION ON SURFACE RESIDUAL STRESS DISTRIBUTION IN MACHINING OF WASPALOY","authors":"Shenliang Yang, Xiaoliang Jin, S. Engin, Raja Kountanya, Tahany I. El-Wardany","doi":"10.1115/1.4066033","DOIUrl":"https://doi.org/10.1115/1.4066033","url":null,"abstract":"\u0000 In the machining of high-strength materials, shear localization in serrated chip formation leads to time-varying thermo-mechanical loads exerted by the cutting tool on the machined surface. This results in periodic changes to surface integrity. This paper explains the formation mechanism of machined surface microfeatures and residual stress fluctuations associated with serrated chip formation, based on a finite element model of machining Waspaloy using the coupled Eulerian-Lagrangian method. The model is validated by comparing the simulation results with experimentally measured chip morphologies and machined surface profiles. During machining with a constant chip thickness, the machined surface exhibits a uniformly distributed residual stress pattern along the cutting velocity direction. However, increased cutting velocity and serrated chip formation cause periodic shear bands, leading to time-varying location of the stagnation point on the tool edge. This results in variations in the workpiece material volume and the thermo-mechanical loads in the plowing region. After machining, the periodical variation in the elastic recovery of the plowed material at the bottom of the tool edge creates waveforms on the finished surface, accompanied by fluctuations in residual stress at the same frequency as chip serration. The simulations quantitatively determine the normal/shear contact force at the tool-workpiece interfaces to reveal the effect of the time-varying stagnation point location on surface topographies and residual stress distributions.","PeriodicalId":507815,"journal":{"name":"Journal of Manufacturing Science and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141821559","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}
M. Michihata, Souki Fujimura, Shuzo Masui, Satoru Takahashi
In this study, we proposed a measurement system that compensates for orthogonality in planar stages and demonstrated its principle. The proposed measurement system consists of a single diffraction grating scale placed diagonally across the stage and two interferometers aligned in a Littrow configuration, which are sensitive only to stage displacement in the optical axis direction. The direction of measurement is determined with high accuracy by the pitch of the diffraction grating and optical wavelength of the laser, allowing orthogonality compensation. In the experiments, we demonstrated that the interferometer aligned at Littrow configuration was capable of measuring the stage displacement component in the optical axis direction. In the discussion, our assessment of orthogonality identified two crucial factors: (1) how accurately the Littrow configuration can be aligned and (2) the accuracy of the pitch of the grating scale.
{"title":"Concept of error compensation for non-orthogonality in two-axis displacement measurement system utilizing single grating scale and Littrow configuration","authors":"M. Michihata, Souki Fujimura, Shuzo Masui, Satoru Takahashi","doi":"10.1115/1.4066035","DOIUrl":"https://doi.org/10.1115/1.4066035","url":null,"abstract":"\u0000 In this study, we proposed a measurement system that compensates for orthogonality in planar stages and demonstrated its principle. The proposed measurement system consists of a single diffraction grating scale placed diagonally across the stage and two interferometers aligned in a Littrow configuration, which are sensitive only to stage displacement in the optical axis direction. The direction of measurement is determined with high accuracy by the pitch of the diffraction grating and optical wavelength of the laser, allowing orthogonality compensation. In the experiments, we demonstrated that the interferometer aligned at Littrow configuration was capable of measuring the stage displacement component in the optical axis direction. In the discussion, our assessment of orthogonality identified two crucial factors: (1) how accurately the Littrow configuration can be aligned and (2) the accuracy of the pitch of the grating scale.","PeriodicalId":507815,"journal":{"name":"Journal of Manufacturing Science and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141821153","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}
Alessandro Fortunato, E. Liverani, Lorenzo Cestone, Flavia Lerra, A. Ascari, Hambal Iqbal, A. Lutey
Gears represent a fundamental component of automotive transmissions, the performance of which is directly influenced by flank surface integrity. With the exception of grinding, gear production does not require the use of lubricants. The elimination of oils in the final finishing phase represents an important opportunity to greatly improve process sustainability and reduce production costs. However, dry grinding presents several challenges, including dimensional tolerances and roughness requirements, microstructural defects due to excessive heat generation, and maintaining the overall surface integrity of flanks such that wear resistance is not compromised. The present work investigates the geometric accuracy, microstructure and wear resistance of FIAT 500 4/6 speed gears manufactured by FCA/Stellantis, comparing conventional wet grinding with two alternative processes including superfinishing and dry grinding. The material and manufacturing processes employed prior to grinding were the same in all cases, with grinding then performed by the same manufacturer. The dimensional accuracy, roughness, microstructure, residual stress state and wear resistance of gear flanks were then analyzed to compare the overall performance of each grinding process. The obtained results show that dry grinding can produce gears with acceptable geometric accuracy, no microstructure defects and greater wear resistance than gears finished with conventional wet grinding or superfinishing. As a result, the complete elimination of lubricant in gear production is possible, leading to a more sustainable process without compromising gear performance.
齿轮是汽车变速器的基本部件，其性能直接受到齿面完整性的影响。除磨削外，齿轮生产不需要使用润滑油。在最后的精加工阶段不使用润滑油是大大提高工艺可持续性和降低生产成本的一个重要机会。然而，干磨也带来了一些挑战，包括尺寸公差和粗糙度要求、过度发热导致的微观结构缺陷，以及保持齿面整体表面完整性以确保耐磨性不受影响。本研究对 FCA/Stellantis 生产的 FIAT 500 4/6 速齿轮的几何精度、微观结构和耐磨性进行了调查，并将传统湿磨与包括超精磨和干磨在内的两种替代工艺进行了比较。在所有情况下，磨削前采用的材料和制造工艺都是相同的，然后由同一制造商进行磨削。然后对齿轮齿面的尺寸精度、粗糙度、微观结构、残余应力状态和耐磨性进行分析，以比较每种磨削工艺的整体性能。结果表明，与传统的湿法磨削或超精加工相比，干法磨削生产的齿轮具有可接受的几何精度、无微观结构缺陷和更高的耐磨性。因此，在齿轮生产过程中完全消除润滑剂是可能的，从而在不影响齿轮性能的情况下实现更可持续的工艺。
{"title":"DRY GRINDING: A MORE SUSTAINABLE MANUFACTURING PROCESS FOR THE PRODUCTION OF AUTOMOTIVE GEARS","authors":"Alessandro Fortunato, E. Liverani, Lorenzo Cestone, Flavia Lerra, A. Ascari, Hambal Iqbal, A. Lutey","doi":"10.1115/1.4066032","DOIUrl":"https://doi.org/10.1115/1.4066032","url":null,"abstract":"\u0000 Gears represent a fundamental component of automotive transmissions, the performance of which is directly influenced by flank surface integrity. With the exception of grinding, gear production does not require the use of lubricants. The elimination of oils in the final finishing phase represents an important opportunity to greatly improve process sustainability and reduce production costs. However, dry grinding presents several challenges, including dimensional tolerances and roughness requirements, microstructural defects due to excessive heat generation, and maintaining the overall surface integrity of flanks such that wear resistance is not compromised. The present work investigates the geometric accuracy, microstructure and wear resistance of FIAT 500 4/6 speed gears manufactured by FCA/Stellantis, comparing conventional wet grinding with two alternative processes including superfinishing and dry grinding. The material and manufacturing processes employed prior to grinding were the same in all cases, with grinding then performed by the same manufacturer. The dimensional accuracy, roughness, microstructure, residual stress state and wear resistance of gear flanks were then analyzed to compare the overall performance of each grinding process. The obtained results show that dry grinding can produce gears with acceptable geometric accuracy, no microstructure defects and greater wear resistance than gears finished with conventional wet grinding or superfinishing. As a result, the complete elimination of lubricant in gear production is possible, leading to a more sustainable process without compromising gear performance.","PeriodicalId":507815,"journal":{"name":"Journal of Manufacturing Science and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141822746","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}
Rapid investment casting with additively produced molds can offer excellent surface finishes, tight dimensional tolerances, and complex geometries for high-performance metal parts in a rapid fashion. However, there is a long-standing challenge in the investment casting of high-strength aluminum alloy (AA) 7075 due to its hot cracking susceptibility and severe solidification shrinkage. Here, we show the unprecedented rapid investment casting of AA7075 by applying nano-treating technology, whereby a low-volume fraction of nanoparticles is dispersed into metal to modify its solidification behavior and microstructure. TiC nanoparticles were able to effectively modify both primary and secondary phases while suppressing the hot cracking susceptibility of AA7075 during solidification. Despite the low cooling rate, nano-treated AA7075 exhibits fine equiaxed grains with an average size of 47.1 μm, in contrast to the large dendritic grains measuring 714.8 μm in pure AA7075. Nano-treated AA7075 parts produced by rapid investment casting exhibited exceptional tensile strength and ductility in both as-cast and heat-treated conditions. This study highlights the potential of investment casting high-performance alloys which were traditionally considered impossible to fabricate by this method.
{"title":"Nanotechnology-Enabled Rapid Investment Casting of Aluminum Alloy 7075","authors":"Y. Chi, Narayanan Murali, Yuxin Zeng, Xiaochun Li","doi":"10.1115/1.4065912","DOIUrl":"https://doi.org/10.1115/1.4065912","url":null,"abstract":"\u0000 Rapid investment casting with additively produced molds can offer excellent surface finishes, tight dimensional tolerances, and complex geometries for high-performance metal parts in a rapid fashion. However, there is a long-standing challenge in the investment casting of high-strength aluminum alloy (AA) 7075 due to its hot cracking susceptibility and severe solidification shrinkage. Here, we show the unprecedented rapid investment casting of AA7075 by applying nano-treating technology, whereby a low-volume fraction of nanoparticles is dispersed into metal to modify its solidification behavior and microstructure. TiC nanoparticles were able to effectively modify both primary and secondary phases while suppressing the hot cracking susceptibility of AA7075 during solidification. Despite the low cooling rate, nano-treated AA7075 exhibits fine equiaxed grains with an average size of 47.1 μm, in contrast to the large dendritic grains measuring 714.8 μm in pure AA7075. Nano-treated AA7075 parts produced by rapid investment casting exhibited exceptional tensile strength and ductility in both as-cast and heat-treated conditions. This study highlights the potential of investment casting high-performance alloys which were traditionally considered impossible to fabricate by this method.","PeriodicalId":507815,"journal":{"name":"Journal of Manufacturing Science and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141659261","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}
Deep learning has impacted defect prediction in Additive Manufacturing (AM), which is important to ensure process stability and part quality. However, its success depends on extensive training, requiring large, homogenous datasets–remaining a challenge for the AM industry, particularly for small- and medium-sized enterprises (SMEs). The unique and varied characteristics of AM parts, along with the limited resources of SMEs, hampers data collection, posing difficulties in the independent training of deep learning models. Addressing these concerns requires enabling knowledge sharing from the similarities in the physics of the AM process and defect formation mechanisms while carefully handling privacy concerns. Federated learning (FL) offers a solution to allow collaborative model training across multiple entities without sharing local data. This paper introduces an FL framework to predict section-wise heat emission during Laser Powder Bed Fusion (LPBF), a vital process signature. It incorporates a customized Long Short-Term Memory (LSTM) model for each client, capturing the dynamic AM process's time series properties without sharing sensitive information. Three advanced FL algorithms are integrated–FedAvg, FedProx, and FedAvgM–to aggregate model weights rather than raw datasets. Experiments demonstrate that the FL framework ensures convergence and maintains prediction performance comparable to individually trained models. This work demonstrates the potential of FL-enabled AM modeling and prediction where SMEs can improve their product quality without compromising data privacy.
深度学习对增材制造（AM）中的缺陷预测产生了影响，这对确保工艺稳定性和零件质量非常重要。然而，深度学习的成功取决于广泛的训练，需要大量的同质数据集，这对增材制造行业，尤其是中小型企业（SMEs）来说仍然是一个挑战。AM 零件独特而多样的特性以及中小企业有限的资源阻碍了数据收集，给深度学习模型的独立训练带来了困难。要解决这些问题，就需要在谨慎处理隐私问题的同时，从 AM 过程和缺陷形成机制的物理相似性中实现知识共享。联合学习（FL）提供了一种解决方案，允许多个实体在不共享本地数据的情况下进行协作模型训练。本文介绍了一种联合学习框架，用于预测激光粉末床融合（LPBF）过程中的热量排放，这是一种重要的工艺特征。它为每个客户定制了一个长短期记忆（LSTM）模型，在不共享敏感信息的情况下捕捉动态 AM 过程的时间序列特性。它集成了三种先进的 FL 算法--FedAvg、FedProx 和 FedAvgM，以汇总模型权重而非原始数据集。实验证明，FL 框架可确保收敛性，并保持与单独训练的模型相当的预测性能。这项工作展示了基于 FL 的 AM 建模和预测的潜力，中小企业可以在不损害数据隐私的情况下提高产品质量。
{"title":"BRIDGING DATA GAPS: A FEDERATED LEARNING APPROACH TO HEAT EMISSION PREDICTION IN LASER POWDER BED FUSION","authors":"Rong Lei, Y.B. Guo, Jiwang Yan, W. Guo","doi":"10.1115/1.4065888","DOIUrl":"https://doi.org/10.1115/1.4065888","url":null,"abstract":"\u0000 Deep learning has impacted defect prediction in Additive Manufacturing (AM), which is important to ensure process stability and part quality. However, its success depends on extensive training, requiring large, homogenous datasets–remaining a challenge for the AM industry, particularly for small- and medium-sized enterprises (SMEs). The unique and varied characteristics of AM parts, along with the limited resources of SMEs, hampers data collection, posing difficulties in the independent training of deep learning models. Addressing these concerns requires enabling knowledge sharing from the similarities in the physics of the AM process and defect formation mechanisms while carefully handling privacy concerns. Federated learning (FL) offers a solution to allow collaborative model training across multiple entities without sharing local data. This paper introduces an FL framework to predict section-wise heat emission during Laser Powder Bed Fusion (LPBF), a vital process signature. It incorporates a customized Long Short-Term Memory (LSTM) model for each client, capturing the dynamic AM process's time series properties without sharing sensitive information. Three advanced FL algorithms are integrated–FedAvg, FedProx, and FedAvgM–to aggregate model weights rather than raw datasets. Experiments demonstrate that the FL framework ensures convergence and maintains prediction performance comparable to individually trained models. This work demonstrates the potential of FL-enabled AM modeling and prediction where SMEs can improve their product quality without compromising data privacy.","PeriodicalId":507815,"journal":{"name":"Journal of Manufacturing Science and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141682177","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}
Ritin Mathews, Arif S Malik, Jaydeep Karandikar, Christopher Tyler, Scott Smith
Residual stress (RS) significantly impacts the mechanical performance of components. Measurement of RS often provides incomplete data in terms of components of stress and spatial density. Employing such fields in finite element simulations results in significant modification of the field to achieve equilibrium and compatibility among strains. To overcome this, an iterative stress reconstruction algorithm (ISRA) is developed to estimate 3D RS fields that satisfy equilibrium, are stress component-wise complete, and represent the characterized data sampled. An Al 7075-T651 plate and an additively manufactured (AM) A36 steel wall are considered for RS reconstruction using measurement data from the literature. A maximum variation of ~2.5 MPa in the Al plate, and ~10 MPa in the steel wall are observed between the reconstructed and measured stresses. Furthermore, unknown stress components emerge and reach significant magnitudes (upto ~2.3 MPa in the Al plate and ~45 MPa in the AM wall) during ISRA. Indeed, it is found that minor errors in measurement or data processing are eliminated through the physical requirements during ISRA. Employing a reconstructed RS field is hence not just more accurate given its compatibility, but it additionally corrects for minor errors in measurement. Furthermore, it is found that spatially dense measurement data results in convergence with fewer iterations. Finally, although ISRA yields a non-unique solution dependent on boundary conditions, measurement errors, fitting errors, and mesh density, it accommodates for uncertainties and inaccuracies in measurement, as opposed to failing to reach a physically realistic converged solution.
{"title":"Iterative stress reconstruction algorithm to estimate 3D residual stress fields in manufactured components","authors":"Ritin Mathews, Arif S Malik, Jaydeep Karandikar, Christopher Tyler, Scott Smith","doi":"10.1115/1.4065848","DOIUrl":"https://doi.org/10.1115/1.4065848","url":null,"abstract":"\u0000 Residual stress (RS) significantly impacts the mechanical performance of components. Measurement of RS often provides incomplete data in terms of components of stress and spatial density. Employing such fields in finite element simulations results in significant modification of the field to achieve equilibrium and compatibility among strains. To overcome this, an iterative stress reconstruction algorithm (ISRA) is developed to estimate 3D RS fields that satisfy equilibrium, are stress component-wise complete, and represent the characterized data sampled. An Al 7075-T651 plate and an additively manufactured (AM) A36 steel wall are considered for RS reconstruction using measurement data from the literature. A maximum variation of ~2.5 MPa in the Al plate, and ~10 MPa in the steel wall are observed between the reconstructed and measured stresses. Furthermore, unknown stress components emerge and reach significant magnitudes (upto ~2.3 MPa in the Al plate and ~45 MPa in the AM wall) during ISRA. Indeed, it is found that minor errors in measurement or data processing are eliminated through the physical requirements during ISRA. Employing a reconstructed RS field is hence not just more accurate given its compatibility, but it additionally corrects for minor errors in measurement. Furthermore, it is found that spatially dense measurement data results in convergence with fewer iterations. Finally, although ISRA yields a non-unique solution dependent on boundary conditions, measurement errors, fitting errors, and mesh density, it accommodates for uncertainties and inaccuracies in measurement, as opposed to failing to reach a physically realistic converged solution.","PeriodicalId":507815,"journal":{"name":"Journal of Manufacturing Science and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141695365","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}
Multi-component injection molding industry is experiencing a growth due to its ability to reduce production costs and streamline processes. However, compared to single injection, multi-component injection molding introduces interface regions where multiple engineering polymers meet. Consequently, it is essential to comprehend and enhance the adhesive bonding strength properties of these polymers. This study investigates the adhesive bond strength of polymer–polymer multi-material molding using two-shot bi-injection and overmolding techniques. The research also emphasizes the influence of injection molding process parameters of mold temperature and melt temperature on the adhesive bond strength of polycarbonate (PC), polycarbonate-acrylonitrile butadiene styrene (PC-ABS), acrylonitrile butadiene styrene (ABS), and styrene ethylene butadiene styrene (SEBS). Tensile strength results revealed that bi-injection method yields the highest interface strength, approximately 10 MPa lower than the reference value for single-material hard-hard plastics. Results from overmolded samples for both injection sequences are presented, indicating that material with low melting temperature was found to be the first injected part for better adhesion strength. Empirical equations for estimating adhesion strength were derived as a function of interface temperature obtained from CAE numerical simulations and polymer glass transition temperatures. The proposed equation achieved R2 values greater than 0.96. This empirically derived equation will serve as a guide for multi-injection manufacturing processes.
{"title":"Experimental Investigation of Processing Temperature Effect on Adhesive Bond Strength Between Engineering Thermoplastics in the Plastic Injection Molding Process","authors":"Ali Özel, Emrecan Soylemez","doi":"10.1115/1.4065847","DOIUrl":"https://doi.org/10.1115/1.4065847","url":null,"abstract":"\u0000 Multi-component injection molding industry is experiencing a growth due to its ability to reduce production costs and streamline processes. However, compared to single injection, multi-component injection molding introduces interface regions where multiple engineering polymers meet. Consequently, it is essential to comprehend and enhance the adhesive bonding strength properties of these polymers. This study investigates the adhesive bond strength of polymer–polymer multi-material molding using two-shot bi-injection and overmolding techniques. The research also emphasizes the influence of injection molding process parameters of mold temperature and melt temperature on the adhesive bond strength of polycarbonate (PC), polycarbonate-acrylonitrile butadiene styrene (PC-ABS), acrylonitrile butadiene styrene (ABS), and styrene ethylene butadiene styrene (SEBS). Tensile strength results revealed that bi-injection method yields the highest interface strength, approximately 10 MPa lower than the reference value for single-material hard-hard plastics. Results from overmolded samples for both injection sequences are presented, indicating that material with low melting temperature was found to be the first injected part for better adhesion strength. Empirical equations for estimating adhesion strength were derived as a function of interface temperature obtained from CAE numerical simulations and polymer glass transition temperatures. The proposed equation achieved R2 values greater than 0.96. This empirically derived equation will serve as a guide for multi-injection manufacturing processes.","PeriodicalId":507815,"journal":{"name":"Journal of Manufacturing Science and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141700926","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}
Currently, numerous studies have applied gear skiving processes to produce face gear. However, there remains a significant challenge in achieving a flexible computing model for manufacturing a precise tooth surface for face gear. This study proposes a novel mathematical model that combines the cutter modification method and CNC-axis motion modification methods within a unified “closed-loop optimization.” This approach aims to enhance the tooth surface accuracy of skived helical face gears by determining optimal coefficients. Applying the Levenberg-Marquardt algorithm and sensitivity matrix enables the calculation of new polynomial coefficients, ensuring the attainment of gear surfaces with an accuracy grade of B6 (according to the ANSI/AGMA 2009-B01 standard) for each target surface. The proposed methodology involves the generation of a helical skiving cutter using a corrected rack. Subsequently, the cutting path on the CNC machine is optimized by incorporating additional motions expressed in polynomials. A comprehensive skiving simulation is conducted to achieve the desired face gear surface, which is corrected by specified polynomial coefficients. The proposed model is validated through numerical and machining simulations using VERICUT software. The results affirm the practicality and efficacy of our approach in achieving the desired accuracy in producing helical face gears through power skiving processes.
{"title":"A Mathematical Modeling of CNC Skiving Process for Manufacturing Helical Face Gears Using Sensitivity Matrix Combined with Levenberg-Marquardt Algorithm","authors":"Khoe-Qui Le, Yu-Ren Wu, T. Luu","doi":"10.1115/1.4065725","DOIUrl":"https://doi.org/10.1115/1.4065725","url":null,"abstract":"\u0000 Currently, numerous studies have applied gear skiving processes to produce face gear. However, there remains a significant challenge in achieving a flexible computing model for manufacturing a precise tooth surface for face gear. This study proposes a novel mathematical model that combines the cutter modification method and CNC-axis motion modification methods within a unified “closed-loop optimization.” This approach aims to enhance the tooth surface accuracy of skived helical face gears by determining optimal coefficients. Applying the Levenberg-Marquardt algorithm and sensitivity matrix enables the calculation of new polynomial coefficients, ensuring the attainment of gear surfaces with an accuracy grade of B6 (according to the ANSI/AGMA 2009-B01 standard) for each target surface. The proposed methodology involves the generation of a helical skiving cutter using a corrected rack. Subsequently, the cutting path on the CNC machine is optimized by incorporating additional motions expressed in polynomials. A comprehensive skiving simulation is conducted to achieve the desired face gear surface, which is corrected by specified polynomial coefficients. The proposed model is validated through numerical and machining simulations using VERICUT software. The results affirm the practicality and efficacy of our approach in achieving the desired accuracy in producing helical face gears through power skiving processes.","PeriodicalId":507815,"journal":{"name":"Journal of Manufacturing Science and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141353579","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}
The machining mechanics of carbon fiber reinforced polymer (CFRP) materials is influenced by the coupled effects of the workpiece anisotropy, tool edge geometry, and cutting parameters. Predicting the chip formation mechanism is crucial for optimizing cutting parameters, reducing tool wear, and improving efficiency and surface quality. This study quantitatively evaluates the effect of main CFRP failure criteria on the chip formation mechanism in modeling the machining mechanics of CFRP. The results show that the Hashin-Puck and Davila criteria excel at capturing chip formation across all fiber orientations because of the incorporation of ‘internal friction’ concept, while others only achieve accurate predictions in specific fiber orientation ranges due to improper shear strength consideration. The sources of the prediction similarities, differences, and limitations of failure criteria are experimentally validated. Sensitivity analyses quantitatively determine the effect of the tool rake angle on the machining energy consumption and cutting forces across the fiber orientation range. This research can be used to select the optimal failure criteria, design proper cutting tool geometry, and inform the cutting parameter choices for CFRP machining operations.
{"title":"Effects of Failure Criteria on Quantitatively Determining the Machining Mechanics for CFRP with Different Tool Rake Angles","authors":"Chunlei Song, Xiaoliang Jin","doi":"10.1115/1.4065726","DOIUrl":"https://doi.org/10.1115/1.4065726","url":null,"abstract":"\u0000 The machining mechanics of carbon fiber reinforced polymer (CFRP) materials is influenced by the coupled effects of the workpiece anisotropy, tool edge geometry, and cutting parameters. Predicting the chip formation mechanism is crucial for optimizing cutting parameters, reducing tool wear, and improving efficiency and surface quality. This study quantitatively evaluates the effect of main CFRP failure criteria on the chip formation mechanism in modeling the machining mechanics of CFRP. The results show that the Hashin-Puck and Davila criteria excel at capturing chip formation across all fiber orientations because of the incorporation of ‘internal friction’ concept, while others only achieve accurate predictions in specific fiber orientation ranges due to improper shear strength consideration. The sources of the prediction similarities, differences, and limitations of failure criteria are experimentally validated. Sensitivity analyses quantitatively determine the effect of the tool rake angle on the machining energy consumption and cutting forces across the fiber orientation range. This research can be used to select the optimal failure criteria, design proper cutting tool geometry, and inform the cutting parameter choices for CFRP machining operations.","PeriodicalId":507815,"journal":{"name":"Journal of Manufacturing Science and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141352011","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}
Dongyang Yi, Nathan Landry, Samuel Blake, John Baron, Lei Chen
Chronically implanting microelectrodes for high-resolution action potential recording is critical for understanding the brain. The smallest and most flexible electrodes, most suitable for chronic recordings, are also the most difficult to insert due to buckling against the thin but hard-to-penetrate brain meninges. To address such implantation challenges without introducing further damage to the brain, this paper presents our design and prototype of an inchworm-type insertion device that conducts a grip-feed-release incremental motion for planar microelectrode insertion. To optimize the operating parameters of the developed inchworm insertion device, experimental studies were conducted on PVC-based brain-mimicking phantom to investigate the effects of (1) incremental insertion depth, (2) inserter drive shaft rotary speed, and (3) the resulting inchworm insertion speed, on the phantom (1) penetration rupture force and (2) dimpling depth at rupture. Analysis showed that all three factors had a statistically significant impact on the rupture force and dimpling depth. A moderate level of the resulting insertion speed yielded the lowest rupture force and dimpling depth at rupture. Low insertion speed levels were associated with higher rupture force while high insertion speeds led to a large variance in dimpling depth and potential insertion failure. To achieve such a moderate insertion speed, it would be preferred for both the incremental insertion depth and the drive shaft rotary speed to be at a moderate level. Such findings lay the foundation for enabling previously impossible buckling-free insertion of miniaturized flexible planar microelectrodes deep into the brain.
{"title":"An Experimental Study of Incremental Buckling-Resistant Inchworm-Type Insertion of Microwire Neural Electrodes","authors":"Dongyang Yi, Nathan Landry, Samuel Blake, John Baron, Lei Chen","doi":"10.1115/1.4065693","DOIUrl":"https://doi.org/10.1115/1.4065693","url":null,"abstract":"\u0000 Chronically implanting microelectrodes for high-resolution action potential recording is critical for understanding the brain. The smallest and most flexible electrodes, most suitable for chronic recordings, are also the most difficult to insert due to buckling against the thin but hard-to-penetrate brain meninges. To address such implantation challenges without introducing further damage to the brain, this paper presents our design and prototype of an inchworm-type insertion device that conducts a grip-feed-release incremental motion for planar microelectrode insertion. To optimize the operating parameters of the developed inchworm insertion device, experimental studies were conducted on PVC-based brain-mimicking phantom to investigate the effects of (1) incremental insertion depth, (2) inserter drive shaft rotary speed, and (3) the resulting inchworm insertion speed, on the phantom (1) penetration rupture force and (2) dimpling depth at rupture. Analysis showed that all three factors had a statistically significant impact on the rupture force and dimpling depth. A moderate level of the resulting insertion speed yielded the lowest rupture force and dimpling depth at rupture. Low insertion speed levels were associated with higher rupture force while high insertion speeds led to a large variance in dimpling depth and potential insertion failure. To achieve such a moderate insertion speed, it would be preferred for both the incremental insertion depth and the drive shaft rotary speed to be at a moderate level. Such findings lay the foundation for enabling previously impossible buckling-free insertion of miniaturized flexible planar microelectrodes deep into the brain.","PeriodicalId":507815,"journal":{"name":"Journal of Manufacturing Science and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141363203","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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