A flank textured cutting tool has been proposed to improve the chatter stability in cutting. Although excellent stability improvement effects have been reported through experimental studies, a simulation method to estimate the effects has not been established so far. In this study, we propose a time-domain simulation method that can take into account the effect of the flank face textures. In order to consider the effect of arbitrary texture geometry on the flank face, the finite element method (FEM) analysis is applied. The relationship between the chatter vibration and the process damping force is modeled, and the process damping coefficients, which represents the process damping effect quantitatively, is obtained. The process damping coefficients are calculated comprehensively by considering the regions where the amplitude and wavelength of chatter vibration can generate. To verify the validity of the proposed method, the face turning experiment was conducted with the prototyped tools consisting of two straight cutting edges. As a result of the verification experiment, it was confirmed that the chatter stability was improved by using a flank-textured tool. The proposed method could demonstrate roughly this chatter stabilization phenomenon.
{"title":"Time Domain Simulation of Turning Operations With Flank Textured Tool","authors":"N. Suzuki, T. Fujinaka, Yu-Fujinami Yokokawa","doi":"10.1115/msec2022-85130","DOIUrl":"https://doi.org/10.1115/msec2022-85130","url":null,"abstract":"\u0000 A flank textured cutting tool has been proposed to improve the chatter stability in cutting. Although excellent stability improvement effects have been reported through experimental studies, a simulation method to estimate the effects has not been established so far. In this study, we propose a time-domain simulation method that can take into account the effect of the flank face textures. In order to consider the effect of arbitrary texture geometry on the flank face, the finite element method (FEM) analysis is applied. The relationship between the chatter vibration and the process damping force is modeled, and the process damping coefficients, which represents the process damping effect quantitatively, is obtained. The process damping coefficients are calculated comprehensively by considering the regions where the amplitude and wavelength of chatter vibration can generate. To verify the validity of the proposed method, the face turning experiment was conducted with the prototyped tools consisting of two straight cutting edges. As a result of the verification experiment, it was confirmed that the chatter stability was improved by using a flank-textured tool. The proposed method could demonstrate roughly this chatter stabilization phenomenon.","PeriodicalId":23676,"journal":{"name":"Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76333524","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}
Digital Image Correlation (DIC), an in situ analysis technique, has gained widespread popularity within the mechanics community over the past two decades. Despite this, accurate computation of strain and displacement fields, especially at interfaces and free surfaces, remains a central challenge. This problem is particularly acute since material flow near free surfaces and interfaces is paramount for understanding the mechanics of several deformation processing configurations, such as machining and forming. Two common DIC implementations exist, and they exploit either local or global information about the deformation. Local techniques suffer from a lack of continuity across subsets, while global methods, despite ensuring continuity, fail to estimate fields at interfaces accurately. Furthermore, global DIC necessitates grid refinement to capture heterogeneous deformation and can often be computationally expensive. Both local and global methods finally use interpolation schemes to obtain continuous displacement fields, along with a finite difference scheme to compute strains. However, these present additional limitations, such as spurious strains at interfaces and loss of experimental data. In this work, we present a random grid-based scheme that uses local correlation search, while simultaneously exploiting global information. Our algorithm is based on a forward 6-parameter (displacement and its first order derivatives) Newton-Raphson (N-R) search. An underlying random grid is first generated and serves to locate subset centers for the correlation scheme. Second derivatives are then computed using a triangulation method. Multiple random grid realizations enable averaging with minimal data loss, thereby eliminating the need for post-processing. The use of second-order derivatives ensures continuous strain fields, which will otherwise need a twelve-parameter (displacement, its first and second derivatives) based correlation search. We establish the validity of our scheme using standard test cases derived from synthetic non-homogeneous displacement fields and demonstrate its utility in practical machining and deformation processing applications.
{"title":"Random Grid-Based DIC Analysis of Plastic Flow Near Interfaces in Deformation Processing","authors":"Deepika Gupta, K. Viswanathan","doi":"10.1115/msec2022-85446","DOIUrl":"https://doi.org/10.1115/msec2022-85446","url":null,"abstract":"\u0000 Digital Image Correlation (DIC), an in situ analysis technique, has gained widespread popularity within the mechanics community over the past two decades. Despite this, accurate computation of strain and displacement fields, especially at interfaces and free surfaces, remains a central challenge. This problem is particularly acute since material flow near free surfaces and interfaces is paramount for understanding the mechanics of several deformation processing configurations, such as machining and forming. Two common DIC implementations exist, and they exploit either local or global information about the deformation. Local techniques suffer from a lack of continuity across subsets, while global methods, despite ensuring continuity, fail to estimate fields at interfaces accurately. Furthermore, global DIC necessitates grid refinement to capture heterogeneous deformation and can often be computationally expensive. Both local and global methods finally use interpolation schemes to obtain continuous displacement fields, along with a finite difference scheme to compute strains. However, these present additional limitations, such as spurious strains at interfaces and loss of experimental data. In this work, we present a random grid-based scheme that uses local correlation search, while simultaneously exploiting global information. Our algorithm is based on a forward 6-parameter (displacement and its first order derivatives) Newton-Raphson (N-R) search. An underlying random grid is first generated and serves to locate subset centers for the correlation scheme. Second derivatives are then computed using a triangulation method. Multiple random grid realizations enable averaging with minimal data loss, thereby eliminating the need for post-processing. The use of second-order derivatives ensures continuous strain fields, which will otherwise need a twelve-parameter (displacement, its first and second derivatives) based correlation search. We establish the validity of our scheme using standard test cases derived from synthetic non-homogeneous displacement fields and demonstrate its utility in practical machining and deformation processing applications.","PeriodicalId":23676,"journal":{"name":"Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability","volume":"92 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90421668","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}
R. Gupta, Justin Hijam, Rama Balhara, Madhu Vadali
Micro- and nano-scale surface texture plays a major role in the wetting behavior of various metallic and non-metallic components. Modifying surfaces using lasers has been widely explored to induce periodic surface textures and thus modify the wetting behavior. Most of these modifications are either through addition or ablation material, making the process uneconomical for the industries. This work presents the pulsed laser surface melting (pLSM) based modification of metallic surfaces to change the wetting behavior, wherein the material is neither removed nor added but is redistributed to create micro-scale features. The size and geometry of the redistributed material depend on the incident laser power and pulse duration and thus affect the wetting behavior. Detailed experimental study on an initially near-flat titanium alloy (Ti6Al4V) surface at various laser powers and pulse durations are presented to understand their influence on the wetting behavior. Experiments are carried out at various laser powers ranging from 120W to 300W and various pulse durations ranging from 3μs to 20μs to understand the size and geometry achievable through pLSM. The highest peak to valley height of the pLSM induced feature (2.3μm) was achieved with 10μs long laser pulses at 210W power. This single spot feature was then rastered across the surface with varying spot spacing and line spacing to generate nine textured surfaces. The corresponding transverse contact angles and the orthogonal contact angles are reported. The results show that the textured surfaces are more wettable or hydrophilic than the near-flat untextured surface of Ti6AL4V. In addition, line spacing of the raster scan in the transverse direction has a more significant impact on the contact angle than the spot spacing in the orthogonal direction. The transverse direction has uniform groove-like features, which aid wettability more than the periodic circular features in the orthogonal direction. Nonetheless, pLSM is demonstrated as a potential method to develop micro-scale surface textures to increase the wettability (hydrophilicity) of the Ti6Al4V surface.
{"title":"Design of Micro-Scale Periodic Surface Textures by Pulsed Laser Melting and its Influence on Wettability","authors":"R. Gupta, Justin Hijam, Rama Balhara, Madhu Vadali","doi":"10.1115/msec2022-85829","DOIUrl":"https://doi.org/10.1115/msec2022-85829","url":null,"abstract":"\u0000 Micro- and nano-scale surface texture plays a major role in the wetting behavior of various metallic and non-metallic components. Modifying surfaces using lasers has been widely explored to induce periodic surface textures and thus modify the wetting behavior. Most of these modifications are either through addition or ablation material, making the process uneconomical for the industries. This work presents the pulsed laser surface melting (pLSM) based modification of metallic surfaces to change the wetting behavior, wherein the material is neither removed nor added but is redistributed to create micro-scale features. The size and geometry of the redistributed material depend on the incident laser power and pulse duration and thus affect the wetting behavior. Detailed experimental study on an initially near-flat titanium alloy (Ti6Al4V) surface at various laser powers and pulse durations are presented to understand their influence on the wetting behavior. Experiments are carried out at various laser powers ranging from 120W to 300W and various pulse durations ranging from 3μs to 20μs to understand the size and geometry achievable through pLSM. The highest peak to valley height of the pLSM induced feature (2.3μm) was achieved with 10μs long laser pulses at 210W power. This single spot feature was then rastered across the surface with varying spot spacing and line spacing to generate nine textured surfaces. The corresponding transverse contact angles and the orthogonal contact angles are reported. The results show that the textured surfaces are more wettable or hydrophilic than the near-flat untextured surface of Ti6AL4V. In addition, line spacing of the raster scan in the transverse direction has a more significant impact on the contact angle than the spot spacing in the orthogonal direction. The transverse direction has uniform groove-like features, which aid wettability more than the periodic circular features in the orthogonal direction. Nonetheless, pLSM is demonstrated as a potential method to develop micro-scale surface textures to increase the wettability (hydrophilicity) of the Ti6Al4V surface.","PeriodicalId":23676,"journal":{"name":"Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability","volume":"39 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85997735","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}
F. Quadrini, D. Bellisario, L. Iorio, A. Proietti, N. Gallo, L. Santo
Carbon nanotubes (CNTs) are deposited between prepreg plies of a carbon fiber reinforced (CFR) laminate during lamination to improve laminate strength. An easy manufacturing procedure has been implemented for this aim in laboratory. CNTs are diluted in a solvent, and subsequently sprayed on commercial woven fabric prepregs for aeronautics. Solvent evacuation is carried out at room temperature. Final composite laminates are produced by vacuum bagging and autoclave molding of coated prepreg plies, by following the typical industrial procedure of aeronautic parts. Quasi-isotropic square laminates with 10 plies have been manufactured by using a unidirectional (UD) CFR prepreg tape with 0/90 stacking sequence. After molding, the square laminates (150 × 150 mm2) were cut to extract rectangular specimens. Mechanical tests were made by bending up to break. Results confirm the positive role of the interlaminar CNTs if they are correctly integrated into the final composite structure.
{"title":"Autoclave Molding of Carbon Fiber Laminates With Interlaminar Carbon Nanotubes","authors":"F. Quadrini, D. Bellisario, L. Iorio, A. Proietti, N. Gallo, L. Santo","doi":"10.1115/msec2022-85480","DOIUrl":"https://doi.org/10.1115/msec2022-85480","url":null,"abstract":"\u0000 Carbon nanotubes (CNTs) are deposited between prepreg plies of a carbon fiber reinforced (CFR) laminate during lamination to improve laminate strength. An easy manufacturing procedure has been implemented for this aim in laboratory. CNTs are diluted in a solvent, and subsequently sprayed on commercial woven fabric prepregs for aeronautics. Solvent evacuation is carried out at room temperature. Final composite laminates are produced by vacuum bagging and autoclave molding of coated prepreg plies, by following the typical industrial procedure of aeronautic parts. Quasi-isotropic square laminates with 10 plies have been manufactured by using a unidirectional (UD) CFR prepreg tape with 0/90 stacking sequence. After molding, the square laminates (150 × 150 mm2) were cut to extract rectangular specimens. Mechanical tests were made by bending up to break. Results confirm the positive role of the interlaminar CNTs if they are correctly integrated into the final composite structure.","PeriodicalId":23676,"journal":{"name":"Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability","volume":"134 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89338437","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}
In-Bai Noh, Hye-Kyeong Shin, Youngwoon Choi, Yongho Lee, Yongjae Jeon, Sang Won Lee
Due to inherent drawbacks of metal 3D printing process such poor dimensional accuracy, surface quality, and various defects, a process monitoring system with an appropriate information visualization interface has been required. In the recent technological mega-trend, the 4th industrial revolution, the digital twin technology has received much attention to effectively monitor the process and transfer relevant information to operators. Therefore, in this paper, the interactive digital twin for a directed energy deposition (DED) process, which is one of representative metal 3D printing processes, is developed. First, the DED equipment digital twin is developed by creating a 3D model of the DED machine, and the motions of virtual components are synchronized with physical ones of the machine by attaching an inertial measurement unit (IMU) sensor to the DED head. Next, the DED process digital twin is developed by pooling objects based on the measured shape of the actual deposited parts. Finally, the DED equipment and process digital twins are combined together to simulate exactly the same as the actual system. Furthermore, the process monitoring function is realized by displaying temperature, shape and size of the melt-pool that are measured by a pyrometer and a CCD camera, respectively. In addition, the diagnosis results of the health state of the DED process are shown in the interactive digital twin.
{"title":"Development of an Interactive Digital Twin for Directed Energy Deposition (DED) Process","authors":"In-Bai Noh, Hye-Kyeong Shin, Youngwoon Choi, Yongho Lee, Yongjae Jeon, Sang Won Lee","doi":"10.1115/msec2022-85513","DOIUrl":"https://doi.org/10.1115/msec2022-85513","url":null,"abstract":"\u0000 Due to inherent drawbacks of metal 3D printing process such poor dimensional accuracy, surface quality, and various defects, a process monitoring system with an appropriate information visualization interface has been required. In the recent technological mega-trend, the 4th industrial revolution, the digital twin technology has received much attention to effectively monitor the process and transfer relevant information to operators. Therefore, in this paper, the interactive digital twin for a directed energy deposition (DED) process, which is one of representative metal 3D printing processes, is developed. First, the DED equipment digital twin is developed by creating a 3D model of the DED machine, and the motions of virtual components are synchronized with physical ones of the machine by attaching an inertial measurement unit (IMU) sensor to the DED head. Next, the DED process digital twin is developed by pooling objects based on the measured shape of the actual deposited parts. Finally, the DED equipment and process digital twins are combined together to simulate exactly the same as the actual system. Furthermore, the process monitoring function is realized by displaying temperature, shape and size of the melt-pool that are measured by a pyrometer and a CCD camera, respectively. In addition, the diagnosis results of the health state of the DED process are shown in the interactive digital twin.","PeriodicalId":23676,"journal":{"name":"Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80540703","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}
Disassembly sequence planning plays a crucial role in the reuse and remanufacturing of end-of-life products, which is a combinatorial optimization problem and has been studied by many researchers. However, it is challenging to obtain optimal disassembly sequences due to great uncertainty owing to various unpredictable factors. We note that some of the uncertainties accompanying the products disassembly process are characterized by dynamic changes and can actually be regarded as dynamic disassembly sequence planning problem. Robust Pareto-optimal over time (RPOT) is a good approach to aovid the inconvenience of tracking optimization by finding solutions that remain acceptable over an extended period. Since there are few studies on applying RPOT to combinatorial optimization, the autoregressive prediction model in RPOT is more suitable for continuous search space problems than combinatorial optimization. In this paper, we develop a dynamic disassembly sequence planning problem considering the uncertainty caused by dynamically changing product states. Finding robust Pareto-optimal solutions over time for dynamci disassembly sequence planning to avoid the consumption of frequent switching solutions. To better apply RPOT to combinatorial optimization, online prediction model is proposed to replace the autoregressive prediction model. Experiment is executed in the three scale problems and compared with tracking optimization. The results indicate that online predictors can effectively improve the accuracy of prediction and improve the performance of the algorithm, and RPOT with new predictor is a more practical and time-saving method of addressing dynamic disaseembly sequence planning problem than tracking optimization.
{"title":"Finding Robust Pareto-Optimal Solutions Over Time for Dynamic Disassembly Sequence Planning","authors":"Xin Zhang, Yilin Fang, QUAN LIU","doi":"10.1115/msec2022-85358","DOIUrl":"https://doi.org/10.1115/msec2022-85358","url":null,"abstract":"\u0000 Disassembly sequence planning plays a crucial role in the reuse and remanufacturing of end-of-life products, which is a combinatorial optimization problem and has been studied by many researchers. However, it is challenging to obtain optimal disassembly sequences due to great uncertainty owing to various unpredictable factors. We note that some of the uncertainties accompanying the products disassembly process are characterized by dynamic changes and can actually be regarded as dynamic disassembly sequence planning problem. Robust Pareto-optimal over time (RPOT) is a good approach to aovid the inconvenience of tracking optimization by finding solutions that remain acceptable over an extended period. Since there are few studies on applying RPOT to combinatorial optimization, the autoregressive prediction model in RPOT is more suitable for continuous search space problems than combinatorial optimization. In this paper, we develop a dynamic disassembly sequence planning problem considering the uncertainty caused by dynamically changing product states. Finding robust Pareto-optimal solutions over time for dynamci disassembly sequence planning to avoid the consumption of frequent switching solutions. To better apply RPOT to combinatorial optimization, online prediction model is proposed to replace the autoregressive prediction model. Experiment is executed in the three scale problems and compared with tracking optimization. The results indicate that online predictors can effectively improve the accuracy of prediction and improve the performance of the algorithm, and RPOT with new predictor is a more practical and time-saving method of addressing dynamic disaseembly sequence planning problem than tracking optimization.","PeriodicalId":23676,"journal":{"name":"Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability","volume":"52 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79134248","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}
As for the first time in the advanced manufacturing research and development sector, the nano range bubbles (i.e., UFB) were injected to the coconut oil-based metal working fluid (COCO) to facilitate better cooling and lubrication condition for machining difficult to cut materials. Higher heat transfer characteristics, and better purification properties of the UFB were incorporated to the higher free fatty acid contained COCO to facilitate a favorable machining condition. Moreover, COCO ensures health and environmental friendliness and express higher potential to replace the toxic and hazardous synthetic oil based MWF (SynO) from the machining process. In this study, the cooling and lubrication performance of the UFB inserted novel COCO was clarified and benchmarked with a commercially available high performance SynO for machining Ti-6Al-4V. Eighteen percent cutting force reduction was obtained due to the hybrid effect of UFB and free fatty acid. Additionally, lower work tool interface temperature, surface roughness, and tool wear were obtained at the UFB inserted COCO compared to the SynO. Hence, the excellent tribological and rheological properties of the UFB inserted novel COCO has concluded high performance sustainable machining and provided a promising solution to conquer the challenges (i.e., low machinability index and sustainability) of machining Ti-6Al-4V.
{"title":"Ultra-Fine Bubbles (UFB) Inserted Novel Coconut Oil Based Metal Working Fluid (MWF) As a Sustainable Lubricant for Turning of Ti-6Al-4V","authors":"K. Wickramasinghe, H. Sasahara","doi":"10.1115/msec2022-85026","DOIUrl":"https://doi.org/10.1115/msec2022-85026","url":null,"abstract":"\u0000 As for the first time in the advanced manufacturing research and development sector, the nano range bubbles (i.e., UFB) were injected to the coconut oil-based metal working fluid (COCO) to facilitate better cooling and lubrication condition for machining difficult to cut materials. Higher heat transfer characteristics, and better purification properties of the UFB were incorporated to the higher free fatty acid contained COCO to facilitate a favorable machining condition. Moreover, COCO ensures health and environmental friendliness and express higher potential to replace the toxic and hazardous synthetic oil based MWF (SynO) from the machining process. In this study, the cooling and lubrication performance of the UFB inserted novel COCO was clarified and benchmarked with a commercially available high performance SynO for machining Ti-6Al-4V. Eighteen percent cutting force reduction was obtained due to the hybrid effect of UFB and free fatty acid. Additionally, lower work tool interface temperature, surface roughness, and tool wear were obtained at the UFB inserted COCO compared to the SynO. Hence, the excellent tribological and rheological properties of the UFB inserted novel COCO has concluded high performance sustainable machining and provided a promising solution to conquer the challenges (i.e., low machinability index and sustainability) of machining Ti-6Al-4V.","PeriodicalId":23676,"journal":{"name":"Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability","volume":"69 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73437942","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}
Brandt J. Ruszkiewicz, E. Breidenbaugh, G. Simpson
Automotive OEMs continue to lightweight their fleets to increase fuel economy and electric drive range to meet government requirements and consumer expectations. This push towards lightweighting has led to increasing use of advanced high strength steels in both car body and safety critical systems, such as seats. These steels present different challenges for traditional joining technologies, especially thread forming fasteners. Thread forming fasteners are externally threaded fasteners like machine screws that are driven into a pilot hole where they form their own threads and then tighten down to secure the target joint. Traditional thread forming fastener designs struggle to form threads into steels with tensile strengths greater than 600MPa. This paper utilizes simulation coupled with experimental validation to evaluate one of the most popular traditional thread forming fasteners that is currently used in low strength steel to determine why it fails to form threads in high strength steels. A new thread forming fastener design targeted for high strength steels is developed through simulation. The new fastener design is manufactured and evaluated across three different screw diameters, and six different high strength steels (> 600MPa tensile strength) using the same heat treatments, materials, and platings as traditional thread forming fasteners. Validation tests for the new fastener include drive-to-failure to identify a target tightening torque and clamp load at the target tightening torque. Both tests are conducted across a hole size tolerance window. It is shown that the new thread forming fastener design performs well in steels up to 1200MPa without any special heat treatments but can benefit from specialized heat treatments in steels of tensile strength 1200MPa or higher.
{"title":"The Development and Validation of a Novel Thread Forming Fastener for High Strength Steel Applications","authors":"Brandt J. Ruszkiewicz, E. Breidenbaugh, G. Simpson","doi":"10.1115/msec2022-81781","DOIUrl":"https://doi.org/10.1115/msec2022-81781","url":null,"abstract":"\u0000 Automotive OEMs continue to lightweight their fleets to increase fuel economy and electric drive range to meet government requirements and consumer expectations. This push towards lightweighting has led to increasing use of advanced high strength steels in both car body and safety critical systems, such as seats. These steels present different challenges for traditional joining technologies, especially thread forming fasteners. Thread forming fasteners are externally threaded fasteners like machine screws that are driven into a pilot hole where they form their own threads and then tighten down to secure the target joint. Traditional thread forming fastener designs struggle to form threads into steels with tensile strengths greater than 600MPa. This paper utilizes simulation coupled with experimental validation to evaluate one of the most popular traditional thread forming fasteners that is currently used in low strength steel to determine why it fails to form threads in high strength steels. A new thread forming fastener design targeted for high strength steels is developed through simulation. The new fastener design is manufactured and evaluated across three different screw diameters, and six different high strength steels (> 600MPa tensile strength) using the same heat treatments, materials, and platings as traditional thread forming fasteners. Validation tests for the new fastener include drive-to-failure to identify a target tightening torque and clamp load at the target tightening torque. Both tests are conducted across a hole size tolerance window. It is shown that the new thread forming fastener design performs well in steels up to 1200MPa without any special heat treatments but can benefit from specialized heat treatments in steels of tensile strength 1200MPa or higher.","PeriodicalId":23676,"journal":{"name":"Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability","volume":"37 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86462320","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}
Digital Twin technology can be effectively employed for prognosis and predictive maintenance tasks by establishing interconnections between manufacturing equipment and its virtual counterpart. This paper presents the Tool State Prognosis (TSP) model based on Digital Twin philosophy to perceive the state of a twist drill during the drilling operation. The TSP model estimates the state of a twist drill viz. initial, intermediate, or worn during the operation rather than obtaining the precise wear value. The Digital Twin collects input information as time-series data by establishing an appropriate connection protocol with a drilling machine using vibration and acoustic emission sensors. The Root Mean Square (RMS) approach and Quadratic Support Vector Machine (QSVM) are employed for feature extraction and recognizing the twist drill status with Remaining Useful Life (RUL) prediction from the time-series data. The model also includes integrating a Human Machine Interface (HMI) unit for displaying tool status and RUL information to assist operators in tool replacement decisions. The developed model can be integrated as an edge-level solution with manual and CNC drilling machines without significant hardware changes for perceiving the status of a twist drill. The prediction abilities of the digital twin are corroborated by performing a set of drilling experiments for various cutting tool-workpiece combinations. The confusion matrices demonstrated the effectiveness and generalization abilities of the developed model by comparing predicted and actual classes for each combination. The developed Digital Twin model can quickly respond to tool status and failure with enhanced man-machine interactions and improved prognosis abilities for the drilling machines.
{"title":"Digital Twin-Based Tool State Prognosis Model for Drilling Machines","authors":"Sunidhi Dayam, K. A. Desai","doi":"10.1115/msec2022-85449","DOIUrl":"https://doi.org/10.1115/msec2022-85449","url":null,"abstract":"\u0000 Digital Twin technology can be effectively employed for prognosis and predictive maintenance tasks by establishing interconnections between manufacturing equipment and its virtual counterpart. This paper presents the Tool State Prognosis (TSP) model based on Digital Twin philosophy to perceive the state of a twist drill during the drilling operation. The TSP model estimates the state of a twist drill viz. initial, intermediate, or worn during the operation rather than obtaining the precise wear value. The Digital Twin collects input information as time-series data by establishing an appropriate connection protocol with a drilling machine using vibration and acoustic emission sensors. The Root Mean Square (RMS) approach and Quadratic Support Vector Machine (QSVM) are employed for feature extraction and recognizing the twist drill status with Remaining Useful Life (RUL) prediction from the time-series data. The model also includes integrating a Human Machine Interface (HMI) unit for displaying tool status and RUL information to assist operators in tool replacement decisions. The developed model can be integrated as an edge-level solution with manual and CNC drilling machines without significant hardware changes for perceiving the status of a twist drill. The prediction abilities of the digital twin are corroborated by performing a set of drilling experiments for various cutting tool-workpiece combinations. The confusion matrices demonstrated the effectiveness and generalization abilities of the developed model by comparing predicted and actual classes for each combination. The developed Digital Twin model can quickly respond to tool status and failure with enhanced man-machine interactions and improved prognosis abilities for the drilling machines.","PeriodicalId":23676,"journal":{"name":"Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90156503","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}
Friction Stir Welding (FSW) of aluminum and steel is often encountered with the formation of weld defects due to the improper material flow in the process. This also leads to the formation of inhomogeneous microstructures and non-uniform thickness of inter-metallic layers at the weld interface. The defects, heterogeneous size and orientations of grains, and thickness of intermetallics can be reduced in underwater friction stir welding but cannot be avoided. The destructive tests involved for the identification of weld defects is expensive and time consuming. The prediction of weld defects can also be carried out by the application of signal processing approach on the welding signals such as axial force and spindle torque. In the present work, the discrete wavelet transformation, a signal processing approach has been applied on the axial force and torque which decompose signals into detail and approximate coefficients through filter banks in time-frequency domain. Later different frequency components have been calculated to predict the weld defects. The results have been verified with optical micrographs and X-ray tomography results. Tensile shear strength and hardness of FSWed have been investigated. In addition, microstructures of the welded samples have been studied to understand the variations in the hardness of weld regions.
{"title":"Prediction of Weld Defects in Underwater Friction Stir Welding of Dissimilar Materials","authors":"R. P. Mahto, A. Dutta, D. Mishra","doi":"10.1115/msec2022-85574","DOIUrl":"https://doi.org/10.1115/msec2022-85574","url":null,"abstract":"\u0000 Friction Stir Welding (FSW) of aluminum and steel is often encountered with the formation of weld defects due to the improper material flow in the process. This also leads to the formation of inhomogeneous microstructures and non-uniform thickness of inter-metallic layers at the weld interface. The defects, heterogeneous size and orientations of grains, and thickness of intermetallics can be reduced in underwater friction stir welding but cannot be avoided. The destructive tests involved for the identification of weld defects is expensive and time consuming. The prediction of weld defects can also be carried out by the application of signal processing approach on the welding signals such as axial force and spindle torque. In the present work, the discrete wavelet transformation, a signal processing approach has been applied on the axial force and torque which decompose signals into detail and approximate coefficients through filter banks in time-frequency domain. Later different frequency components have been calculated to predict the weld defects. The results have been verified with optical micrographs and X-ray tomography results. Tensile shear strength and hardness of FSWed have been investigated. In addition, microstructures of the welded samples have been studied to understand the variations in the hardness of weld regions.","PeriodicalId":23676,"journal":{"name":"Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability","volume":"48 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82611575","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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