Amborish Banerjee, L. Da Silva, Hitesh Sharma, A. Platts, S. Rahimi
Inertia friction welding (IFW) is a solid-state welding process utilised for joining engineering materials. In this paper, a 2.5D finite element (FE) model was developed to simulate IFW of MLX®19 maraging steel. The predicted results showed a non-uniform temperature distribution, with a decrease in temperature from the periphery to the centre of weld interface. Higher temperature and lower stress distributions were predicted in the weld zone (WZ) and the adjacent regions in the vicinity of the WZ. The von-Mises effective stress, effective strain and strain-rate were investigated at different time steps of the FE simulation. The effective stress was minimum at the weld interface, and the effective strain and strain-rate attained a quasi-steady state status with the on-going IFW after a threshold time (~6.5 s). The simulated results were validated by comparing the predicted flash morphology with an actual IFW weld, and temperature profiles measured at specific locations using embedded thermo-couples. The difference between the experimental and the simulated results was ~4.7%, implying a good convergence of the model. Microstructural characterisations were performed across different regions and the observed features were found to be in agreement with the expected microstructure based on the simulated thermal profiles, which included almost complete (~90%) and partial transformation of martensite to austenite in the WZ and thermo-mechanically affected zone (TMAZ), respectively. Analyses of crystallographic texture, showed that the material (i.e., both transformed austenite and martensite) underwent pure shear deformation during IFW.
{"title":"Evolution of microstructure in MLX®19 maraging steel during rotary friction welding and finite element modelling of the process","authors":"Amborish Banerjee, L. Da Silva, Hitesh Sharma, A. Platts, S. Rahimi","doi":"10.1115/1.4063090","DOIUrl":"https://doi.org/10.1115/1.4063090","url":null,"abstract":"\u0000 Inertia friction welding (IFW) is a solid-state welding process utilised for joining engineering materials. In this paper, a 2.5D finite element (FE) model was developed to simulate IFW of MLX®19 maraging steel. The predicted results showed a non-uniform temperature distribution, with a decrease in temperature from the periphery to the centre of weld interface. Higher temperature and lower stress distributions were predicted in the weld zone (WZ) and the adjacent regions in the vicinity of the WZ. The von-Mises effective stress, effective strain and strain-rate were investigated at different time steps of the FE simulation. The effective stress was minimum at the weld interface, and the effective strain and strain-rate attained a quasi-steady state status with the on-going IFW after a threshold time (~6.5 s). The simulated results were validated by comparing the predicted flash morphology with an actual IFW weld, and temperature profiles measured at specific locations using embedded thermo-couples. The difference between the experimental and the simulated results was ~4.7%, implying a good convergence of the model. Microstructural characterisations were performed across different regions and the observed features were found to be in agreement with the expected microstructure based on the simulated thermal profiles, which included almost complete (~90%) and partial transformation of martensite to austenite in the WZ and thermo-mechanically affected zone (TMAZ), respectively. Analyses of crystallographic texture, showed that the material (i.e., both transformed austenite and martensite) underwent pure shear deformation during IFW.","PeriodicalId":16299,"journal":{"name":"Journal of Manufacturing Science and Engineering-transactions of The Asme","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2023-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46635748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Although the production of polymer/carbon nanotube (CNT) nanocomposites has grown exponentially over the last years for a variety of applications, the availability of polymer/CNT filaments for the use in commercial 3D printing systems is very limited and, currently, little is known about the printability of recycled polymer/CNT nanocomposites. In this respect, the fused filament fabrication (FFF) of recycled thermoplastic polyurethane/carbon nanotube (TPU/CNT) nanocomposites was investigated with special focus on the piezoresistive behavior. Mechanically recycled and virgin TPU/CNT nanocomposites with different CNT contents (0.5, 1, 3, and 5 wt% by weight) were subjected to filament extrusion and FFF, and the changes induced by mechanical recycling, CNT contents and infill orientation were monitored by melt flow index, thermal, mechanical, electrical and piezoresistive properties. It was found that the recycled TPU nanocomposites exhibit very good printability with mechanical and electrical properties that are generally comparable with those for the virgin nanocomposites, the decrease of the elongation at break at 5 wt% CNTs being the primary challenge for the mechanical recycling of TPU/CNT nanocomposites. The 3D printed recycled TPU/CNT nanocomposites with 3 wt% and 5 wt% CNTs provide very good strain sensing behavior, with sensitivity and stretchability higher than those of the virgin nanocomposites. The findings of this work provide guidance for assessing the potential of using recycled TPU/CNT nanocomposites for 3D printing strain sensors with tuned sensitivity for a wide range of human motions.
{"title":"Investigation on the Printability of Recycled Thermoplastic Polyurethane/Carbon Nanotube Nanocomposites","authors":"F. Stan, I. Sandu, C. Fetecau","doi":"10.1115/1.4063036","DOIUrl":"https://doi.org/10.1115/1.4063036","url":null,"abstract":"\u0000 Although the production of polymer/carbon nanotube (CNT) nanocomposites has grown exponentially over the last years for a variety of applications, the availability of polymer/CNT filaments for the use in commercial 3D printing systems is very limited and, currently, little is known about the printability of recycled polymer/CNT nanocomposites. In this respect, the fused filament fabrication (FFF) of recycled thermoplastic polyurethane/carbon nanotube (TPU/CNT) nanocomposites was investigated with special focus on the piezoresistive behavior. Mechanically recycled and virgin TPU/CNT nanocomposites with different CNT contents (0.5, 1, 3, and 5 wt% by weight) were subjected to filament extrusion and FFF, and the changes induced by mechanical recycling, CNT contents and infill orientation were monitored by melt flow index, thermal, mechanical, electrical and piezoresistive properties. It was found that the recycled TPU nanocomposites exhibit very good printability with mechanical and electrical properties that are generally comparable with those for the virgin nanocomposites, the decrease of the elongation at break at 5 wt% CNTs being the primary challenge for the mechanical recycling of TPU/CNT nanocomposites. The 3D printed recycled TPU/CNT nanocomposites with 3 wt% and 5 wt% CNTs provide very good strain sensing behavior, with sensitivity and stretchability higher than those of the virgin nanocomposites. The findings of this work provide guidance for assessing the potential of using recycled TPU/CNT nanocomposites for 3D printing strain sensors with tuned sensitivity for a wide range of human motions.","PeriodicalId":16299,"journal":{"name":"Journal of Manufacturing Science and Engineering-transactions of The Asme","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48065122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tengteng Tang, Dylan Joralmon, Tochukwu Anyigbo, Xiangjia Li
The artificial cell is a biomimetic microcapsule system wherein biological materials are encapsulated by a thin membrane, which provides valuable information on the metabolism, morphology, development, and signal transduction pathways of the studied cell. However, it is extremely difficult to manufacture such systems. Mostly vesicles such as liposomes, polymersomes, and microcapsules are first produced by a high-pressure homogenizer and microfluidizer as an emulsion and then encapsulated microcapsules by the drop or emulsion method. Currently, acoustic levitation opens up entirely new possibilities for creating artificial cells because of its ability to suspend tiny droplets in an anti-gravity and non-contact manner. Herein, we propose a contactless printing of single-core or multi-core artificial cells based on acoustic levitation. First, the oscillation mode and microscopic morphology of the droplets under different ultrasonic vibration frequencies are shown by simulation, and the curing characteristics of the shell structure under different ultraviolet illumination conditions are quantitatively measured. The feasibility of manufacturing multi-core artificial cells and manufacturing sub-millimeter-scale particles based on oil trapping is extensively studied. To explore the morphological adaptability of artificial cells, ferromagnetic Fe3O4 nanoparticles are used to give cells magnetic responsive properties and the microscopic deformation and motion in microfluidic channels under the magnetic field are characterized. Finally, the proposed printing method proves the versatility of in-space contactless printing of complex 3D beam structures and provides a powerful platform for developing biomedical devices and microrobots and studying morphogenesis and synthetic biological systems
{"title":"Acoustic Levitation assisted Contactless Printing of Microdroplets for Biomedical Applications","authors":"Tengteng Tang, Dylan Joralmon, Tochukwu Anyigbo, Xiangjia Li","doi":"10.1115/1.4062971","DOIUrl":"https://doi.org/10.1115/1.4062971","url":null,"abstract":"\u0000 The artificial cell is a biomimetic microcapsule system wherein biological materials are encapsulated by a thin membrane, which provides valuable information on the metabolism, morphology, development, and signal transduction pathways of the studied cell. However, it is extremely difficult to manufacture such systems. Mostly vesicles such as liposomes, polymersomes, and microcapsules are first produced by a high-pressure homogenizer and microfluidizer as an emulsion and then encapsulated microcapsules by the drop or emulsion method. Currently, acoustic levitation opens up entirely new possibilities for creating artificial cells because of its ability to suspend tiny droplets in an anti-gravity and non-contact manner. Herein, we propose a contactless printing of single-core or multi-core artificial cells based on acoustic levitation. First, the oscillation mode and microscopic morphology of the droplets under different ultrasonic vibration frequencies are shown by simulation, and the curing characteristics of the shell structure under different ultraviolet illumination conditions are quantitatively measured. The feasibility of manufacturing multi-core artificial cells and manufacturing sub-millimeter-scale particles based on oil trapping is extensively studied. To explore the morphological adaptability of artificial cells, ferromagnetic Fe3O4 nanoparticles are used to give cells magnetic responsive properties and the microscopic deformation and motion in microfluidic channels under the magnetic field are characterized. Finally, the proposed printing method proves the versatility of in-space contactless printing of complex 3D beam structures and provides a powerful platform for developing biomedical devices and microrobots and studying morphogenesis and synthetic biological systems","PeriodicalId":16299,"journal":{"name":"Journal of Manufacturing Science and Engineering-transactions of The Asme","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41538908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The integration of mobile robots in material handling in flexible manufacturing systems is made possible by the recent advancements in Industry 4.0 and industrial artificial intelligence. However, effectively scheduling these robots in real-time remains a challenge due to the constantly changing, complex and uncertain nature of the shop floor environment. Therefore, this paper studies the robot scheduling problem for a multiproduct flexible production line using a mobile robot for loading/unloading parts among machines and buffers. The problem is formulated as a Markov Decision Process and the Q-learning algorithm is used to find an optimal policy for the robot's movements in handling different product types. The performance of the system is evaluated using a reward function based on permanent production loss and the cost of demand dissatisfaction. The proposed approach is validated through a numerical case study that compares the resulting policy to a first-come-first-served policy, showing a significant improvement in production throughput of approximately 23%.
{"title":"Adaptive Mobile Robot Scheduling in Multiproduct Flexible Manufacturing Systems Using Reinforcement Learning","authors":"Muhammad Waseem, Qing Chang","doi":"10.1115/1.4062941","DOIUrl":"https://doi.org/10.1115/1.4062941","url":null,"abstract":"\u0000 The integration of mobile robots in material handling in flexible manufacturing systems is made possible by the recent advancements in Industry 4.0 and industrial artificial intelligence. However, effectively scheduling these robots in real-time remains a challenge due to the constantly changing, complex and uncertain nature of the shop floor environment. Therefore, this paper studies the robot scheduling problem for a multiproduct flexible production line using a mobile robot for loading/unloading parts among machines and buffers. The problem is formulated as a Markov Decision Process and the Q-learning algorithm is used to find an optimal policy for the robot's movements in handling different product types. The performance of the system is evaluated using a reward function based on permanent production loss and the cost of demand dissatisfaction. The proposed approach is validated through a numerical case study that compares the resulting policy to a first-come-first-served policy, showing a significant improvement in production throughput of approximately 23%.","PeriodicalId":16299,"journal":{"name":"Journal of Manufacturing Science and Engineering-transactions of The Asme","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41726734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bone cutting with high performance material removal is critical for enhancing orthopedic surgery. Ultrasonically assisted cutting (UAC) is an advanced process with the potential to improve the material removal. However, strain and other intermediate variables in bone cutting are difficult to obtain because of the lack of suitable measurement methods, especially for high-frequency vibration-assisted cutting. In this study, digital image correlation (DIC) analysis was applied for the first time to investigate the mechanism of crack development during conventional cutting (CC) and ultrasonically assisted cutting of cortical bone. A novel method for calculating cutting and thrust forces under the mixed fracture mode of bone was also proposed. Extensive experimental results showed that the average strain and strain rate of cortical bone decreased after the application of UAC, but the maximum transient strain rate in UAC was greater than that in CC, and the crack-affected area and shear band width in UAC were smaller than those in CC. In addition, the strain parameters obtained by the DIC analysis were used to calculate the cutting and thrust forces in the hybrid fracture mode. The calculated values of forces matched well with the measured results, indicating the strong feasibility of DIC applications in orthogonal bone cutting research. This study has significant theoretical and practical value since it reveals the fracture mechanism of cortical bone in UAC, demonstrates a non-contact full-field measurement method for tissue strain calculation, and provides inspiration for optimizing the design of innovative orthopedic instruments.
{"title":"Characterization of ultrasonically assisted orthogonal cutting of bone using digital image correlation analysis","authors":"W. Bai, Yuhao Zhai, Jiaqi Zhao, Xuzhe Jia, Guangchao Han, Liming Shu, Dong Wang, Jianfeng Xu","doi":"10.1115/1.4062942","DOIUrl":"https://doi.org/10.1115/1.4062942","url":null,"abstract":"\u0000 Bone cutting with high performance material removal is critical for enhancing orthopedic surgery. Ultrasonically assisted cutting (UAC) is an advanced process with the potential to improve the material removal. However, strain and other intermediate variables in bone cutting are difficult to obtain because of the lack of suitable measurement methods, especially for high-frequency vibration-assisted cutting. In this study, digital image correlation (DIC) analysis was applied for the first time to investigate the mechanism of crack development during conventional cutting (CC) and ultrasonically assisted cutting of cortical bone. A novel method for calculating cutting and thrust forces under the mixed fracture mode of bone was also proposed. Extensive experimental results showed that the average strain and strain rate of cortical bone decreased after the application of UAC, but the maximum transient strain rate in UAC was greater than that in CC, and the crack-affected area and shear band width in UAC were smaller than those in CC. In addition, the strain parameters obtained by the DIC analysis were used to calculate the cutting and thrust forces in the hybrid fracture mode. The calculated values of forces matched well with the measured results, indicating the strong feasibility of DIC applications in orthogonal bone cutting research. This study has significant theoretical and practical value since it reveals the fracture mechanism of cortical bone in UAC, demonstrates a non-contact full-field measurement method for tissue strain calculation, and provides inspiration for optimizing the design of innovative orthopedic instruments.","PeriodicalId":16299,"journal":{"name":"Journal of Manufacturing Science and Engineering-transactions of The Asme","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41893502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Walczyk, Jiachen Yang, Jennifer Gilbert-Jenkins
This paper discusses a new method for decorticating bast fiber stalks through a mastication process without damaging the fiber for use in biocomposites. Conventional automated decortication methods provide high stalk processing throughput, but they significantly damage the bast fibers and adversely affect their performance in biocomposite applications. Initial experiments with industrial hemp using a matched set of tools indicate that indexing the stalk by, at most, half a tooling period for each mastication cycle maximizes both the crushed stalk flexing action and dehurding efficiency. Further process insight was gained through simple stalk crushing experiments (force vs. deflection) between matching teeth with no indexing, where force spikes correspond to initial collapse of the stalk cross section and initial hurd bending fracture along the stalk length. A more extensive experimental design with stiffer tooling reveals that adding spaces in the bottom die for hurd to fall through, and using the smallest practical indexing distance less than half a tooling period and also more teeth maximizes hurding efficiency. However, shorter indexing and more teeth also decreases throughput rate and complicates stalk handling. Future work for optimizing and commercializing the process are suggested.
{"title":"Bast Fiber Decortication for Biocomposites by a Mastication Process","authors":"D. Walczyk, Jiachen Yang, Jennifer Gilbert-Jenkins","doi":"10.1115/1.4062913","DOIUrl":"https://doi.org/10.1115/1.4062913","url":null,"abstract":"\u0000 This paper discusses a new method for decorticating bast fiber stalks through a mastication process without damaging the fiber for use in biocomposites. Conventional automated decortication methods provide high stalk processing throughput, but they significantly damage the bast fibers and adversely affect their performance in biocomposite applications. Initial experiments with industrial hemp using a matched set of tools indicate that indexing the stalk by, at most, half a tooling period for each mastication cycle maximizes both the crushed stalk flexing action and dehurding efficiency. Further process insight was gained through simple stalk crushing experiments (force vs. deflection) between matching teeth with no indexing, where force spikes correspond to initial collapse of the stalk cross section and initial hurd bending fracture along the stalk length. A more extensive experimental design with stiffer tooling reveals that adding spaces in the bottom die for hurd to fall through, and using the smallest practical indexing distance less than half a tooling period and also more teeth maximizes hurding efficiency. However, shorter indexing and more teeth also decreases throughput rate and complicates stalk handling. Future work for optimizing and commercializing the process are suggested.","PeriodicalId":16299,"journal":{"name":"Journal of Manufacturing Science and Engineering-transactions of The Asme","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2023-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48109170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Robert O. Jung, F. Bleicher, S. Krall, Christian Juricek, Rainer Lottes, Karoline Steinschuetz, T. Reininger
Deep Drawing is an essential manufacturing technology for car body parts. High process stability is a key for reducing scrap and therefore the ecological footprint during the production. To deal with an unknown fluctuation of the incoming material properties and uncertainties considering the friction, an adaptive process needs to be implemented. Various approaches have been pursued in the past, but not all of them are suited for an industrial series production with high demands for equipment durability, cost efficiency and flexibility. For this reason, a new concept for cyber physical production systems (CPPS) in deep drawing is presented, linking the data from the simulation, tool, press, material and finished part quality. Two common application scenarios are distinguished. These are firstly large outer parts with a complex geometry and high value, typically produced with tandem presses. Secondly smaller structural parts from high strength steel for the body in white (BIW), usually produced through a transfer or progressive die. Non destructive material testing, supplier material certificates and data measured directly in the forming tool are considered regarding the input. A variation of the servo curve and blank holder force (BHF) operate as control instances. Within the two application scenarios, a reactive and a preventive solution are characterized. As a first step towards the implementation of the CPPS, material inflow and force sensors are installed in an industrially relevant deep drawing tool.
{"title":"Cyber Physical Production Systems for Deep Drawing","authors":"Robert O. Jung, F. Bleicher, S. Krall, Christian Juricek, Rainer Lottes, Karoline Steinschuetz, T. Reininger","doi":"10.1115/1.4062903","DOIUrl":"https://doi.org/10.1115/1.4062903","url":null,"abstract":"\u0000 Deep Drawing is an essential manufacturing technology for car body parts. High process stability is a key for reducing scrap and therefore the ecological footprint during the production. To deal with an unknown fluctuation of the incoming material properties and uncertainties considering the friction, an adaptive process needs to be implemented. Various approaches have been pursued in the past, but not all of them are suited for an industrial series production with high demands for equipment durability, cost efficiency and flexibility. For this reason, a new concept for cyber physical production systems (CPPS) in deep drawing is presented, linking the data from the simulation, tool, press, material and finished part quality. Two common application scenarios are distinguished. These are firstly large outer parts with a complex geometry and high value, typically produced with tandem presses. Secondly smaller structural parts from high strength steel for the body in white (BIW), usually produced through a transfer or progressive die. Non destructive material testing, supplier material certificates and data measured directly in the forming tool are considered regarding the input. A variation of the servo curve and blank holder force (BHF) operate as control instances. Within the two application scenarios, a reactive and a preventive solution are characterized. As a first step towards the implementation of the CPPS, material inflow and force sensors are installed in an industrially relevant deep drawing tool.","PeriodicalId":16299,"journal":{"name":"Journal of Manufacturing Science and Engineering-transactions of The Asme","volume":"1 1","pages":""},"PeriodicalIF":4.0,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"63504257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pee-Yew Lee, H. Huang, T. Ko, Ying-Lun Hung, Li-Yan Wu, Jianhua Fan, Yung-Sheng Lin
Abstract The fluoride-assisted galvanic replacement reaction is a conventional method for fabricating metallic dendrites on silicon wafers. However, whether bubbles affect manufacturing metallic dendrites is unclear. This study investigated the effects of bubbles on manufacturing Au dendrites and silicon nanowires through metal-assisted chemical etching. The results of manufacture under three conditions (standard, shaking, and vacuum conditions) were compared. Synchronous growth of Au dendrites and silicon nanowires were observed on the silicon wafers. The Au dendrite deposition rate was higher than the silicon etching rate. Compared with the standard condition, the vacuum condition increased the synthesis rates of Au dendrites and silicon nanowires by 1.1 and 0.2 μm/min, respectively. Therefore, the elimination of bubbles by vacuum can considerably accelerate manufacturing Au dendrites and silicon nanowires.
{"title":"Effects of bubbles on manufacturing gold dendrites and silicon nanowires through the fluoride-assisted galvanic replacement reaction","authors":"Pee-Yew Lee, H. Huang, T. Ko, Ying-Lun Hung, Li-Yan Wu, Jianhua Fan, Yung-Sheng Lin","doi":"10.1115/1.4062878","DOIUrl":"https://doi.org/10.1115/1.4062878","url":null,"abstract":"\u0000 Abstract The fluoride-assisted galvanic replacement reaction is a conventional method for fabricating metallic dendrites on silicon wafers. However, whether bubbles affect manufacturing metallic dendrites is unclear. This study investigated the effects of bubbles on manufacturing Au dendrites and silicon nanowires through metal-assisted chemical etching. The results of manufacture under three conditions (standard, shaking, and vacuum conditions) were compared. Synchronous growth of Au dendrites and silicon nanowires were observed on the silicon wafers. The Au dendrite deposition rate was higher than the silicon etching rate. Compared with the standard condition, the vacuum condition increased the synthesis rates of Au dendrites and silicon nanowires by 1.1 and 0.2 μm/min, respectively. Therefore, the elimination of bubbles by vacuum can considerably accelerate manufacturing Au dendrites and silicon nanowires.","PeriodicalId":16299,"journal":{"name":"Journal of Manufacturing Science and Engineering-transactions of The Asme","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47974110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper summarizes the perspectives from a manufacturing engineer on how the government policy, global partnership, and diversity of the United States (US), Japanese, European, and traditional Chinese cultures in Taiwan have created a workforce of semiconductor manufacturing talent in the past five decades. The complex interwoven events of Covid-19 pandemic, supply chain resilience, national security, and geopolitical conflicts have made semiconductor manufacturing a key focus of government policy. As a world leader in integrated circuit (IC) design, design software, equipment, and research, the US has struggled in the past few years on the high yield volume manufacturing of the most advanced logic IC and failed to translate research innovations to quality production. Manufacturing, not innovation or equipment, is a key barrier of the US semiconductor industry. Two models for excellence in advanced manufacturing are described. Three pillars of government policy, global collaboration, and multicultural diversity empower semiconductor manufacturing excellence in Taiwan is described. An approach to evaluate, select, educate, and train manufacturing talents is proposed. Directions for semiconductor manufacturing research are discussed. There is no genius in semiconductor manufacturing, which requires extensive experience and continuous improvement without shortcuts to be competitive. The steadfast good government policy, multicultural diversity workforce, and global technology collaboration to achieve semiconductor manufacturing excellence are the focus of the conclusion.
{"title":"Multicultural Diversity Workforce and Global Technology Collaboration Empowered Semiconductor Manufacturing Excellence in Taiwan: A Manufacturing Engineer’s Perspective","authors":"A. Shih","doi":"10.1115/1.4062729","DOIUrl":"https://doi.org/10.1115/1.4062729","url":null,"abstract":"\u0000 This paper summarizes the perspectives from a manufacturing engineer on how the government policy, global partnership, and diversity of the United States (US), Japanese, European, and traditional Chinese cultures in Taiwan have created a workforce of semiconductor manufacturing talent in the past five decades. The complex interwoven events of Covid-19 pandemic, supply chain resilience, national security, and geopolitical conflicts have made semiconductor manufacturing a key focus of government policy. As a world leader in integrated circuit (IC) design, design software, equipment, and research, the US has struggled in the past few years on the high yield volume manufacturing of the most advanced logic IC and failed to translate research innovations to quality production. Manufacturing, not innovation or equipment, is a key barrier of the US semiconductor industry. Two models for excellence in advanced manufacturing are described. Three pillars of government policy, global collaboration, and multicultural diversity empower semiconductor manufacturing excellence in Taiwan is described. An approach to evaluate, select, educate, and train manufacturing talents is proposed. Directions for semiconductor manufacturing research are discussed. There is no genius in semiconductor manufacturing, which requires extensive experience and continuous improvement without shortcuts to be competitive. The steadfast good government policy, multicultural diversity workforce, and global technology collaboration to achieve semiconductor manufacturing excellence are the focus of the conclusion.","PeriodicalId":16299,"journal":{"name":"Journal of Manufacturing Science and Engineering-transactions of The Asme","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47829756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Human-robot collaboration has become a hotspot in smart manufacturing, and it also has shown the potential for surface defect inspection. The robot can release workload, while human collaboration can help to recheck the uncertain defects. However, the human-robot collaboration-based defect inspection can be hardly realized unless some bottlenecks have been solved, and one of them is that the current methods cannot decide which samples to be rechecked, and the workers can only recheck all of the samples to improve inspection results. To overcome this problem and realize the human-robot collaboration-based surface defect inspection, a two-stage Transformer model with focal loss is proposed. The proposed method divides the traditional inspection process into detection and recognition, designs a collaboration rule to allow workers to collaborate and recheck the defects, and introduces the focal loss into the model to improve the recognition results. With these improvements, the proposed method can collaborate with workers by rechecking the defects, and improve surface quality. The experimental results on the public dataset have shown the effectiveness of the proposed method, the accuracies are significantly improved by the human collaboration, which are 1.70%~4.18%. Moreover, the proposed method has been implemented into a human-robot collaboration-based prototype to inspect the carton surface defects, and the results also verify the effectiveness. Meanwhile, the proposed method has a good ability for visualization to find the defect area, and it is also conducive to defect analysis and rechecking.
{"title":"A Two-stage Focal Transformer for Human-Robot Collaboration-based Surface Defect Inspection","authors":"Yiping Gao, Liang Gao, Xinyu Li","doi":"10.1115/1.4062860","DOIUrl":"https://doi.org/10.1115/1.4062860","url":null,"abstract":"\u0000 Human-robot collaboration has become a hotspot in smart manufacturing, and it also has shown the potential for surface defect inspection. The robot can release workload, while human collaboration can help to recheck the uncertain defects. However, the human-robot collaboration-based defect inspection can be hardly realized unless some bottlenecks have been solved, and one of them is that the current methods cannot decide which samples to be rechecked, and the workers can only recheck all of the samples to improve inspection results. To overcome this problem and realize the human-robot collaboration-based surface defect inspection, a two-stage Transformer model with focal loss is proposed. The proposed method divides the traditional inspection process into detection and recognition, designs a collaboration rule to allow workers to collaborate and recheck the defects, and introduces the focal loss into the model to improve the recognition results. With these improvements, the proposed method can collaborate with workers by rechecking the defects, and improve surface quality. The experimental results on the public dataset have shown the effectiveness of the proposed method, the accuracies are significantly improved by the human collaboration, which are 1.70%~4.18%. Moreover, the proposed method has been implemented into a human-robot collaboration-based prototype to inspect the carton surface defects, and the results also verify the effectiveness. Meanwhile, the proposed method has a good ability for visualization to find the defect area, and it is also conducive to defect analysis and rechecking.","PeriodicalId":16299,"journal":{"name":"Journal of Manufacturing Science and Engineering-transactions of The Asme","volume":" ","pages":""},"PeriodicalIF":4.0,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44282921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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