Michael Storchak, Thomas Stehle, Hans-Christian Möhring
Analyzing the cutting process characteristics opens up significant opportunities to improve various material machining processes. Numerical modeling is a well-established, powerful technique for determining various characteristics of cutting processes. The developed spatial finite element model of short hole drilling is used to determine the kinetic characteristics of the machining process, in particular, the components of cutting force and cutting power. To determine the component model parameters for the numerical model of drilling, the constitutive equation parameters, and the parameters of the contact interaction between the drill and the machined material on the example of AISI 1045 steel machining, the orthogonal cutting process was used. These parameters are determined using the inverse method. The DOE (Design of Experiment) sensitivity analysis was applied as a procedure for determining the component models parameters, which is realized by multiple simulations using the developed spatial FEM model of orthogonal cutting and the subsequent determination of generalized values of the required parameters by finding the intersection of the individual value sets of these parameters. The target values for the DOE analysis were experimentally determined kinetic characteristics of the orthogonal cutting process. The constitutive equation and contact interaction parameters were used to simulate the short hole drilling process. The comparison of experimentally determined and simulated values of the kinetic characteristics of the drilling process for a significant range of cutting speed and drill feed changes has established their satisfactory coincidence. The simulated value deviation from the corresponding measured characteristics in the whole range of cutting speed and drill feed variation did not exceed 23%.
分析切削过程特性为改进各种材料加工工艺提供了重要的机会。数值模拟是一种完善的、强大的技术，用于确定切削过程的各种特性。建立了短孔钻削的空间有限元模型，用于确定加工过程的动力学特性，特别是切削力和切削功率的组成。以AISI 1045钢为例，采用正交切削法确定了钻削数值模型的构件模型参数、本构方程参数以及钻削与被加工材料的接触相互作用参数。这些参数是用逆方法确定的。采用DOE (Design of Experiment，试验设计)灵敏度分析方法确定零件模型参数，采用所建立的正交切削空间有限元模型进行多次仿真，并通过求出各参数值集的交点确定所需参数的广义值。DOE分析的目标值是通过实验确定正交切削过程的动力学特性。利用本构方程和接触相互作用参数对短孔钻孔过程进行了模拟。在很大的切削速度和钻头进给量变化范围内，钻孔过程的动力学特性的实验测定值与模拟值的比较证实了它们的一致性。在切削速度和钻头进给量变化的整个范围内，模拟值与相应测量特性的偏差不超过23%。
{"title":"Numerical Modeling of Cutting Characteristics during Short Hole Drilling: Modeling of Kinetic Characteristics","authors":"Michael Storchak, Thomas Stehle, Hans-Christian Möhring","doi":"10.3390/jmmp7060195","DOIUrl":"https://doi.org/10.3390/jmmp7060195","url":null,"abstract":"Analyzing the cutting process characteristics opens up significant opportunities to improve various material machining processes. Numerical modeling is a well-established, powerful technique for determining various characteristics of cutting processes. The developed spatial finite element model of short hole drilling is used to determine the kinetic characteristics of the machining process, in particular, the components of cutting force and cutting power. To determine the component model parameters for the numerical model of drilling, the constitutive equation parameters, and the parameters of the contact interaction between the drill and the machined material on the example of AISI 1045 steel machining, the orthogonal cutting process was used. These parameters are determined using the inverse method. The DOE (Design of Experiment) sensitivity analysis was applied as a procedure for determining the component models parameters, which is realized by multiple simulations using the developed spatial FEM model of orthogonal cutting and the subsequent determination of generalized values of the required parameters by finding the intersection of the individual value sets of these parameters. The target values for the DOE analysis were experimentally determined kinetic characteristics of the orthogonal cutting process. The constitutive equation and contact interaction parameters were used to simulate the short hole drilling process. The comparison of experimentally determined and simulated values of the kinetic characteristics of the drilling process for a significant range of cutting speed and drill feed changes has established their satisfactory coincidence. The simulated value deviation from the corresponding measured characteristics in the whole range of cutting speed and drill feed variation did not exceed 23%.","PeriodicalId":16319,"journal":{"name":"Journal of Manufacturing and Materials Processing","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135773476","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}
Mona A. Aboueleaz, Noha Naeim, Islam H. Abdelgaliel, Mohamed F. Aly, Ahmed Elkaseer
This research investigates the multi-response of both material removal rate (MRR) and surface roughness (Ra) for the wire electrical discharge machining (WEDM) of two stainless steel alloys: AISI 304 and AISI 316. Experimental results are utilized to compare the machining responses obtained for AISI 316 with those obtained for AISI 304, as previously reported in the literature. The experimental work is conducted through a full factorial experimental design of five running parameters with different levels: applied voltage, transverse feed, pulse-on/pulse-off times and current intensity. The machined workpieces are analyzed using an image processing technique in order to evaluate the size of cut slots to allow the calculation of the MRR. Followed by the characterization of the surface roughness along the side walls of the slots. Different mathematical regression techniques were developed to represent the multi-response of both materials using the MATLAB regression toolbox. It was found that WEDM process parameters have a fuzzy influence on the responses of both material models. This allowed for multi-objective optimization of the regression models using four different techniques: multi-objective genetic algorithm (MOGA), multi-objective pareto search algorithm (MOPSA), weighted value grey wolf optimizer (WVGWO) and osprey optimization algorithm (OOA). The optimization results reveal that the optimal WEDM parameters of each response are inconsistent to the others. Hence, the optimal results are considered a compromise between the best results of different responses. Noteworthily, the multi-objective pareto search algorithm outperformed the other candidates. Eventually, the optimal results of both materials share the high voltage, high transverse feed rate and low pulse-off time parameters; however, AISI 304 requires low pulse-on time and current intensity levels while AISI 316 optimal results entail higher pulse-on time and current levels.
{"title":"Wire Electrical Discharge Machining of AISI304 and AISI316 Alloys: A Comparative Assessment of Machining Responses, Empirical Modeling and Multi-Objective Optimization","authors":"Mona A. Aboueleaz, Noha Naeim, Islam H. Abdelgaliel, Mohamed F. Aly, Ahmed Elkaseer","doi":"10.3390/jmmp7060194","DOIUrl":"https://doi.org/10.3390/jmmp7060194","url":null,"abstract":"This research investigates the multi-response of both material removal rate (MRR) and surface roughness (Ra) for the wire electrical discharge machining (WEDM) of two stainless steel alloys: AISI 304 and AISI 316. Experimental results are utilized to compare the machining responses obtained for AISI 316 with those obtained for AISI 304, as previously reported in the literature. The experimental work is conducted through a full factorial experimental design of five running parameters with different levels: applied voltage, transverse feed, pulse-on/pulse-off times and current intensity. The machined workpieces are analyzed using an image processing technique in order to evaluate the size of cut slots to allow the calculation of the MRR. Followed by the characterization of the surface roughness along the side walls of the slots. Different mathematical regression techniques were developed to represent the multi-response of both materials using the MATLAB regression toolbox. It was found that WEDM process parameters have a fuzzy influence on the responses of both material models. This allowed for multi-objective optimization of the regression models using four different techniques: multi-objective genetic algorithm (MOGA), multi-objective pareto search algorithm (MOPSA), weighted value grey wolf optimizer (WVGWO) and osprey optimization algorithm (OOA). The optimization results reveal that the optimal WEDM parameters of each response are inconsistent to the others. Hence, the optimal results are considered a compromise between the best results of different responses. Noteworthily, the multi-objective pareto search algorithm outperformed the other candidates. Eventually, the optimal results of both materials share the high voltage, high transverse feed rate and low pulse-off time parameters; however, AISI 304 requires low pulse-on time and current intensity levels while AISI 316 optimal results entail higher pulse-on time and current levels.","PeriodicalId":16319,"journal":{"name":"Journal of Manufacturing and Materials Processing","volume":"16 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135820826","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}
Benedikt Uhe, Clara-Maria Kuball, Marion Merklein, Gerson Meschut
The sustainability of the manufacturing industry is of special importance to increase the protection of the environment. The production of fasteners like self-piercing rivets, however, is costly, time-consuming and energy-intensive. The heat treatment and the coating, which are mandatory in conventional self-piercing rivets to achieve adequate strength, ductility and corrosion resistance, are especially crucial in this respect. Within this paper, an approach for an increase in the sustainability in fastener production is presented. The use of alternative, high strain hardening stainless steels as rivet material enables a shortening of the process chain, because post treatment of the rivets after they are formed can be omitted. As the change in rivet material and processing causes some issues along the process chain, the focus of this paper is on the holistic evaluation of the challenges within the forming of high strain hardening steel and the impact of the changed rivet properties on the joining result.
{"title":"Increased Sustainability in Fastener Production with the Example of Self-Piercing Rivets","authors":"Benedikt Uhe, Clara-Maria Kuball, Marion Merklein, Gerson Meschut","doi":"10.3390/jmmp7060193","DOIUrl":"https://doi.org/10.3390/jmmp7060193","url":null,"abstract":"The sustainability of the manufacturing industry is of special importance to increase the protection of the environment. The production of fasteners like self-piercing rivets, however, is costly, time-consuming and energy-intensive. The heat treatment and the coating, which are mandatory in conventional self-piercing rivets to achieve adequate strength, ductility and corrosion resistance, are especially crucial in this respect. Within this paper, an approach for an increase in the sustainability in fastener production is presented. The use of alternative, high strain hardening stainless steels as rivet material enables a shortening of the process chain, because post treatment of the rivets after they are formed can be omitted. As the change in rivet material and processing causes some issues along the process chain, the focus of this paper is on the holistic evaluation of the challenges within the forming of high strain hardening steel and the impact of the changed rivet properties on the joining result.","PeriodicalId":16319,"journal":{"name":"Journal of Manufacturing and Materials Processing","volume":"18 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135872544","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}
Yorihiro Yamashita, Kholqillah Ardhian Ilman, Takahiro Kunimine, Yuji Sato
Cracks usually generate during the formation of beads composed of a WC-12mass%Co cemented carbide by the laser metal deposition (LMD). Measuring temperatures of the formed bead and substrate during the LMD process is important for realizing crack-free beads. In this study, temperatures of the substrate around the formed bead during the LMD process were measured using a thermoviewer. Temperatures of the formed beads during the LMD process were predicted by simulation based on the thermal conduction analysis using the experimentally measured temperatures of the substrate. The experimental results obtained during forming the WC-12mass%Co cemented carbide beads on JIS SKH51 (ISO HS-6-5-2) substrates showed that the maximal temperatures of the substrates at 0.2 mm away from the center of the formed beads ranged from 229 °C to 341 °C at laser powers ranging from 80 W to 160 W. The predicted maximal temperatures of the formed beads were in the range of 2433 °C to 4491 °C in the simulation using a laser absorption coefficient of 0.35 for the substrate. Validity of these simulation results was discussed based on the melting point of the substrate and microstructures of the formed WC-12mass%Co cemented carbide beads.
{"title":"Temperature Evaluation of Cladding Beads and the Surrounding Area during the Laser Metal Deposition Process","authors":"Yorihiro Yamashita, Kholqillah Ardhian Ilman, Takahiro Kunimine, Yuji Sato","doi":"10.3390/jmmp7060192","DOIUrl":"https://doi.org/10.3390/jmmp7060192","url":null,"abstract":"Cracks usually generate during the formation of beads composed of a WC-12mass%Co cemented carbide by the laser metal deposition (LMD). Measuring temperatures of the formed bead and substrate during the LMD process is important for realizing crack-free beads. In this study, temperatures of the substrate around the formed bead during the LMD process were measured using a thermoviewer. Temperatures of the formed beads during the LMD process were predicted by simulation based on the thermal conduction analysis using the experimentally measured temperatures of the substrate. The experimental results obtained during forming the WC-12mass%Co cemented carbide beads on JIS SKH51 (ISO HS-6-5-2) substrates showed that the maximal temperatures of the substrates at 0.2 mm away from the center of the formed beads ranged from 229 °C to 341 °C at laser powers ranging from 80 W to 160 W. The predicted maximal temperatures of the formed beads were in the range of 2433 °C to 4491 °C in the simulation using a laser absorption coefficient of 0.35 for the substrate. Validity of these simulation results was discussed based on the melting point of the substrate and microstructures of the formed WC-12mass%Co cemented carbide beads.","PeriodicalId":16319,"journal":{"name":"Journal of Manufacturing and Materials Processing","volume":"23 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136232682","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}
This article investigates the surface hardening capability of a metastable austenitic TRansformation Induced Plasticity (TRIP) stainless steel, particularly on AISI 301LN, by laser texturing. This technology produces microstructural surface changes in terms of both phase transformation and grain size modification and, as a direct consequence, the laser influences the surface characteristics, mainly hardness and roughness. In this sense, the key parameters (laser power, scanning speed and position of the focal length) were investigated by using a Design of Experiments (DoE) in detail to better understand the correlation between texturing parameters, microstructural and mechanical changes, always at the superficial level. From all the aforementioned information, the results show that the maximum surface hardening is obtained by increasing the laser power and decreasing the scanning speed. Furthermore, by reducing the focal distance, the depth of the microstructural evolution layer is more significant, while the width is less affected. Finally, a suitable model was developed to correlate the processing parameters here investigated with the resulting surface integrity, in terms of mechanical properties, by means of a regression equation.
{"title":"Exploring the Effects of Laser Surface Modification on AISI 301LN Steel: A Micro-Mechanical Study","authors":"Mohammad Rezayat, Antonio Mateo, Joan Josep Roa","doi":"10.3390/jmmp7060191","DOIUrl":"https://doi.org/10.3390/jmmp7060191","url":null,"abstract":"This article investigates the surface hardening capability of a metastable austenitic TRansformation Induced Plasticity (TRIP) stainless steel, particularly on AISI 301LN, by laser texturing. This technology produces microstructural surface changes in terms of both phase transformation and grain size modification and, as a direct consequence, the laser influences the surface characteristics, mainly hardness and roughness. In this sense, the key parameters (laser power, scanning speed and position of the focal length) were investigated by using a Design of Experiments (DoE) in detail to better understand the correlation between texturing parameters, microstructural and mechanical changes, always at the superficial level. From all the aforementioned information, the results show that the maximum surface hardening is obtained by increasing the laser power and decreasing the scanning speed. Furthermore, by reducing the focal distance, the depth of the microstructural evolution layer is more significant, while the width is less affected. Finally, a suitable model was developed to correlate the processing parameters here investigated with the resulting surface integrity, in terms of mechanical properties, by means of a regression equation.","PeriodicalId":16319,"journal":{"name":"Journal of Manufacturing and Materials Processing","volume":"23 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134906861","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 development of the additive manufacturing (AM) technology proffers challenging requirements for forming accuracy and efficiency. In this paper, a hybrid additive manufacturing technology combining fusion-based selective laser melting (SLM) and solid-state cold spraying (CS) was proposed in order to enable the fast production of near-net-shape metal parts. The idea is to fabricate a bulk deposit with a rough contour first via the “fast” CS process and then add fine structures and complex features through “slow” SLM. The experimental results show that it is feasible to deposit an SLM part onto a CS part with good interfacial bonding. However, the CS parts must be subject to heat treatment to improve their cohesion strength before being sending for SLM processing. Otherwise, the high tensile residual stress generated during the SLM process will cause fractures and cracks in the CS part. After heat treatment, pure copper deposited by CS undergoes grain growth and recrystallization, resulting in improved cohesive strength and the release of the residual stress in the CS parts. The tensile test on the SLM/CS interfacial region indicates that the bonding strength increased by 38% from 45 ± 7 MPa to 62 ± 1 MPa after the CS part is subject to heat treatment, and the SLM/CS interfacial bonding strength is higher than the CS parts. This study demonstrates that the proposed hybrid AM process is feasible and promising for manufacturing free-standing SLM-CS components.
{"title":"Printing Cu on a Cold-Sprayed Cu Plate via Selective Laser Melting—Hybrid Additive Manufacturing","authors":"Qing Chai, Chaoxin Jiang, Chunjie Huang, Yingchun Xie, Xingchen Yan, Rocco Lupoi, Chao Zhang, Peter Rusinov, Shuo Yin","doi":"10.3390/jmmp7060188","DOIUrl":"https://doi.org/10.3390/jmmp7060188","url":null,"abstract":"The development of the additive manufacturing (AM) technology proffers challenging requirements for forming accuracy and efficiency. In this paper, a hybrid additive manufacturing technology combining fusion-based selective laser melting (SLM) and solid-state cold spraying (CS) was proposed in order to enable the fast production of near-net-shape metal parts. The idea is to fabricate a bulk deposit with a rough contour first via the “fast” CS process and then add fine structures and complex features through “slow” SLM. The experimental results show that it is feasible to deposit an SLM part onto a CS part with good interfacial bonding. However, the CS parts must be subject to heat treatment to improve their cohesion strength before being sending for SLM processing. Otherwise, the high tensile residual stress generated during the SLM process will cause fractures and cracks in the CS part. After heat treatment, pure copper deposited by CS undergoes grain growth and recrystallization, resulting in improved cohesive strength and the release of the residual stress in the CS parts. The tensile test on the SLM/CS interfacial region indicates that the bonding strength increased by 38% from 45 ± 7 MPa to 62 ± 1 MPa after the CS part is subject to heat treatment, and the SLM/CS interfacial bonding strength is higher than the CS parts. This study demonstrates that the proposed hybrid AM process is feasible and promising for manufacturing free-standing SLM-CS components.","PeriodicalId":16319,"journal":{"name":"Journal of Manufacturing and Materials Processing","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135273437","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}
Tiago Santos, Miguel Belbut, João Amaral, Vitor Amaral, Nelson Ferreira, Nuno Alves, Paula Pascoal-Faria
In fused deposition modeling (FDM), the cooling history impacts the bonding between filaments and layers. The existence of thermal gradients can cause non-homogeneous properties and localized stress points that may affect the individual filaments, resulting in distortion and detachment. Thermal analysis can aid in understanding the manufacturing flaw, providing necessary tools for the optimization of the printing trajectory. The present work is intended to deepen understanding of the thermal phenomena occurring during the extrusion of polymeric materials, aiming at more efficient three-dimensional (3D) printing methods. A one-dimensional (1D) finite differential method was implemented using MATLAB to simulate the temperature evolution of an extruded filament, and the results were compared with two-dimensional (2D) COMSOL Multiphysics simulations, and experimentally validated using infrared thermography. Acrylonitrile–butadiene–styrene (ABS) was used as a test material. The energy dissipation includes forced convection and radiation heat losses to the surrounding medium.
{"title":"Insights into Temperature Simulation and Validation of Fused Deposition Modeling Processes","authors":"Tiago Santos, Miguel Belbut, João Amaral, Vitor Amaral, Nelson Ferreira, Nuno Alves, Paula Pascoal-Faria","doi":"10.3390/jmmp7060189","DOIUrl":"https://doi.org/10.3390/jmmp7060189","url":null,"abstract":"In fused deposition modeling (FDM), the cooling history impacts the bonding between filaments and layers. The existence of thermal gradients can cause non-homogeneous properties and localized stress points that may affect the individual filaments, resulting in distortion and detachment. Thermal analysis can aid in understanding the manufacturing flaw, providing necessary tools for the optimization of the printing trajectory. The present work is intended to deepen understanding of the thermal phenomena occurring during the extrusion of polymeric materials, aiming at more efficient three-dimensional (3D) printing methods. A one-dimensional (1D) finite differential method was implemented using MATLAB to simulate the temperature evolution of an extruded filament, and the results were compared with two-dimensional (2D) COMSOL Multiphysics simulations, and experimentally validated using infrared thermography. Acrylonitrile–butadiene–styrene (ABS) was used as a test material. The energy dissipation includes forced convection and radiation heat losses to the surrounding medium.","PeriodicalId":16319,"journal":{"name":"Journal of Manufacturing and Materials Processing","volume":"78 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135265891","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}
Maria Emanuela Palmieri, Andrea Nono Dachille, Luigi Tricarico
During the forming process, variations in noise parameters can negatively impact product quality. To prevent waste from these fluctuations, this study suggests a method for the in-line optimisation of the deep drawing process. The noise parameter considered is the friction coefficient, assuming the variability in lubrication conditions at the blank–tool interface. The proposed approach estimates the noise factor variability during the process by tracking the draw-in of the blank at critical points. Using this estimation, the optimal blank holder force (BHF) is calculated and then adjusted in-line to modify blank sliding and prevent critical issues on the component. For this purpose, a Finite Element (FE) model of a deep drawing case study was developed, and numerical simulation results were used to construct surrogate models while estimating both the friction coefficient and optimal BHF. The FE model’s predictive capability was verified through preliminary experimental tests, and the control logic was numerically validated. Results show the effectiveness of this control type. By adjusting the BHF just once, a defect-free component is achieved. This method overcomes the limitations of feedback controls, which often need multiple adjustment steps. The time required to estimate the friction coefficient and the maximum time available for adjusting the BHF without causing defects was identified.
{"title":"Identification of the Optimal Blank Holder Force through In-Line Measurement of Blank Draw-In in a Deep Drawing Process","authors":"Maria Emanuela Palmieri, Andrea Nono Dachille, Luigi Tricarico","doi":"10.3390/jmmp7060190","DOIUrl":"https://doi.org/10.3390/jmmp7060190","url":null,"abstract":"During the forming process, variations in noise parameters can negatively impact product quality. To prevent waste from these fluctuations, this study suggests a method for the in-line optimisation of the deep drawing process. The noise parameter considered is the friction coefficient, assuming the variability in lubrication conditions at the blank–tool interface. The proposed approach estimates the noise factor variability during the process by tracking the draw-in of the blank at critical points. Using this estimation, the optimal blank holder force (BHF) is calculated and then adjusted in-line to modify blank sliding and prevent critical issues on the component. For this purpose, a Finite Element (FE) model of a deep drawing case study was developed, and numerical simulation results were used to construct surrogate models while estimating both the friction coefficient and optimal BHF. The FE model’s predictive capability was verified through preliminary experimental tests, and the control logic was numerically validated. Results show the effectiveness of this control type. By adjusting the BHF just once, a defect-free component is achieved. This method overcomes the limitations of feedback controls, which often need multiple adjustment steps. The time required to estimate the friction coefficient and the maximum time available for adjusting the BHF without causing defects was identified.","PeriodicalId":16319,"journal":{"name":"Journal of Manufacturing and Materials Processing","volume":"22 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135266045","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}
Thabiso Moral Thobane, Sujeet Kumar Chaubey, Kapil Gupta
The present research investigated the turning of AZ31B magnesium alloy in a dry environment using carbide tool inserts coated with tungsten carbonitride (TiCn) and thin alumina (Al2O3). A Box–Behnken design based on fifteen experiments showed a proportional increasing trend of flank wear with all three machining parameters, i.e., cutting speed, feed rate, and depth of cut. The most influential parameter is the cutting speed. A maximum flank wear of 299.34 µm due to excessive adhesion of work material on the tool face was observed at a high cutting speed. Machining at low speed resulted in a significant reduction in tool wear due to less chipping. The tool wear and chip morphology study confirmed the results.
{"title":"Analysis of Tool Wear and Chip Morphology during Turning of AZ31B Magnesium Alloy under Dry Environment","authors":"Thabiso Moral Thobane, Sujeet Kumar Chaubey, Kapil Gupta","doi":"10.3390/jmmp7050187","DOIUrl":"https://doi.org/10.3390/jmmp7050187","url":null,"abstract":"The present research investigated the turning of AZ31B magnesium alloy in a dry environment using carbide tool inserts coated with tungsten carbonitride (TiCn) and thin alumina (Al2O3). A Box–Behnken design based on fifteen experiments showed a proportional increasing trend of flank wear with all three machining parameters, i.e., cutting speed, feed rate, and depth of cut. The most influential parameter is the cutting speed. A maximum flank wear of 299.34 µm due to excessive adhesion of work material on the tool face was observed at a high cutting speed. Machining at low speed resulted in a significant reduction in tool wear due to less chipping. The tool wear and chip morphology study confirmed the results.","PeriodicalId":16319,"journal":{"name":"Journal of Manufacturing and Materials Processing","volume":"38 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135462222","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}
Zijie Liu, Gerardo A. Mazzei Capote, Evan Grubis, Apoorv Pandey, Juan C. Blanco Campos, Graydon R. Hegge, Tim A. Osswald
Fused filament fabrication (FFF), colloquially known as 3D-printing, has gradually expanded from the laboratory to the industrial and household realms due to its suitability for producing highly customized products with complex geometries. However, it is difficult to evaluate the mechanical performance of samples produced by this method of additive manufacturing (AM) due to the high number of combinations of printing parameters, which have been shown to significantly impact the final structural integrity of the part. This implies that using experimental data attained through destructive testing is not always viable. In this study, predictive models based on the rapid prediction of the required extrusion force and mechanical properties of printed parts are proposed, selecting a subset of the most representative printing parameters during the printing process as the domain of interest. Data obtained from the in-line sensor-equipped 3D printers were used to train several different predictive models. By comparing the coefficient of determination (R2) of the response surface method (RSM) and five different machine learning models, it is found that the support vector regressor (SVR) has the best performance in this data volume case. Ultimately, the ML resources developed in this work can potentially support the application of AM technology in the assessment of part structural integrity through simulation and can also be integrated into a control loop that can pause or even correct a failing print if the expected filament force-speed pairing is trailing outside a tolerance zone stemming from ML predictions.
{"title":"Predicting Properties of Fused Filament Fabrication Parts through Sensors and Machine Learning","authors":"Zijie Liu, Gerardo A. Mazzei Capote, Evan Grubis, Apoorv Pandey, Juan C. Blanco Campos, Graydon R. Hegge, Tim A. Osswald","doi":"10.3390/jmmp7050186","DOIUrl":"https://doi.org/10.3390/jmmp7050186","url":null,"abstract":"Fused filament fabrication (FFF), colloquially known as 3D-printing, has gradually expanded from the laboratory to the industrial and household realms due to its suitability for producing highly customized products with complex geometries. However, it is difficult to evaluate the mechanical performance of samples produced by this method of additive manufacturing (AM) due to the high number of combinations of printing parameters, which have been shown to significantly impact the final structural integrity of the part. This implies that using experimental data attained through destructive testing is not always viable. In this study, predictive models based on the rapid prediction of the required extrusion force and mechanical properties of printed parts are proposed, selecting a subset of the most representative printing parameters during the printing process as the domain of interest. Data obtained from the in-line sensor-equipped 3D printers were used to train several different predictive models. By comparing the coefficient of determination (R2) of the response surface method (RSM) and five different machine learning models, it is found that the support vector regressor (SVR) has the best performance in this data volume case. Ultimately, the ML resources developed in this work can potentially support the application of AM technology in the assessment of part structural integrity through simulation and can also be integrated into a control loop that can pause or even correct a failing print if the expected filament force-speed pairing is trailing outside a tolerance zone stemming from ML predictions.","PeriodicalId":16319,"journal":{"name":"Journal of Manufacturing and Materials Processing","volume":"224 5-6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136033577","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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