Microscale Selective Laser Sintering is an Additive Manufacturing process which involves the creation of parts using nanoparticles, precision substrate motion control, and an optical setup aimed at achieving sub-micron resolution on the printed parts. In order to drive the Microscale Selective Laser Sintering process towards this proposed goal, it is important to understand the kinetics of nanoparticle sintering to be able to make predictions of the properties that can be expected from the manufacturing process. To this end, Phase Field Modelling simulations have been built which model how nanoparticles sinter together when heated. In the past these simulations have yielded measurements such as the densification in the powder bed as a function of temperature and time, however it is extremely difficult to measure the density of parts built from the microscale Selective Laser Sintering system. Electrical resistance is a much more easily quantified property. As such, in order to fully validate these nanoparticle sintering simulations, it is necessary to measure the electrical resistance in the simulation bed and compare these resistance curves against experimentally derived electrical resistance measurements. This paper presents the approach used to extract electrical resistance data from the simulations as well as preliminary resistance results collated from this study.
{"title":"Electrical Resistance Metrology in Nanoparticle Sintering Simulations","authors":"O. Dibua, C. S. Foong, M. Cullinan","doi":"10.1115/msec2022-85997","DOIUrl":"https://doi.org/10.1115/msec2022-85997","url":null,"abstract":"\u0000 Microscale Selective Laser Sintering is an Additive Manufacturing process which involves the creation of parts using nanoparticles, precision substrate motion control, and an optical setup aimed at achieving sub-micron resolution on the printed parts. In order to drive the Microscale Selective Laser Sintering process towards this proposed goal, it is important to understand the kinetics of nanoparticle sintering to be able to make predictions of the properties that can be expected from the manufacturing process. To this end, Phase Field Modelling simulations have been built which model how nanoparticles sinter together when heated. In the past these simulations have yielded measurements such as the densification in the powder bed as a function of temperature and time, however it is extremely difficult to measure the density of parts built from the microscale Selective Laser Sintering system. Electrical resistance is a much more easily quantified property. As such, in order to fully validate these nanoparticle sintering simulations, it is necessary to measure the electrical resistance in the simulation bed and compare these resistance curves against experimentally derived electrical resistance measurements. This paper presents the approach used to extract electrical resistance data from the simulations as well as preliminary resistance results collated from this study.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":"34 8 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76012686","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}
Rui Liu, A. Greeley, Shuhuan Zhang, D. Cormier, Patricia Iglesias Victoria
By introducing local depressions, as small reservoirs for lubricants and wear debris, on a flat surface, the surface texture has been proven to positively affect the friction and wear behavior of lubricated sliding surfaces. However, the effectiveness of the surface texture diminishes and disappears eventually as wear develops at the contact interface. In order to achieve a longer-lasting beneficial effect on the sliding surface, this work develops an approach to print an inherently porous structure up to a certain depth beneath the contact surface to retain the benefits associated with surface texture. A test structure was created from 17-4 PH stainless steel using a metal fused filament fabrication system. The performance of the printed porous structure was evaluated using a steel ball in a ball-on-flat reciprocating tribometer under lubricated conditions with mineral oil. By comparing with the solid sample, it was found that the printed structure with inherent porosity improved the tribological performance by reducing the friction up to 20% and the wear rate up to 90%. The experimental results also indicate that the effectiveness of the printed texture is strongly correlated to the shape and the distribution of the pores on the wear track, which requires further research in the following studies.
{"title":"Effect of Inherently Porous Structure Produced by Metal Fused Filament Fabrication on the Tribological Behavior of Lubricated Steel-Steel Contact","authors":"Rui Liu, A. Greeley, Shuhuan Zhang, D. Cormier, Patricia Iglesias Victoria","doi":"10.1115/msec2022-85584","DOIUrl":"https://doi.org/10.1115/msec2022-85584","url":null,"abstract":"\u0000 By introducing local depressions, as small reservoirs for lubricants and wear debris, on a flat surface, the surface texture has been proven to positively affect the friction and wear behavior of lubricated sliding surfaces. However, the effectiveness of the surface texture diminishes and disappears eventually as wear develops at the contact interface. In order to achieve a longer-lasting beneficial effect on the sliding surface, this work develops an approach to print an inherently porous structure up to a certain depth beneath the contact surface to retain the benefits associated with surface texture. A test structure was created from 17-4 PH stainless steel using a metal fused filament fabrication system. The performance of the printed porous structure was evaluated using a steel ball in a ball-on-flat reciprocating tribometer under lubricated conditions with mineral oil. By comparing with the solid sample, it was found that the printed structure with inherent porosity improved the tribological performance by reducing the friction up to 20% and the wear rate up to 90%. The experimental results also indicate that the effectiveness of the printed texture is strongly correlated to the shape and the distribution of the pores on the wear track, which requires further research in the following studies.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":"12 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73937745","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}
Hao Fu, Hong Lu, Yongquan Zhang, Zidong Wu, He Huang, Shijie Liu, Shaojun Wang
Large-type rotary machinery is the core components of national major projects which is widely used aviation, electric power, metallurgy, energy and construction machinery industries. Surface defects of Large-type rotary machinery such as cracks and pits are usually processed into groove with a certain shape first, and then the processed groove is repaired by manual welding. This manual welding repair method has a low level of automation, and the repair quality of the groove is difficult to guarantee. Therefore, this paper proposes a novel welding method for repairing surface defects of Large-type rotary machinery which uses the Kollmorgen Joint Modular Robot to complete the welding repair of the processed groove. Firstly, the groove point cloud data collected by Line structured light sensor is processed by the designed algorithm to obtain the contour characteristics of the groove. Then, the arrangement of welding pass is completed based on contour characteristics of the groove. Finally, the trajectory of the welding robot is determined by the position of welding pass. The planned trajectory verification is completed on the simulation experiment platform and the result shows the accuracy and reliability of the planned trajectory which has certain theoretical and practical significance for realizing the automation of on-site maintenance of Large-type rotary machinery.
{"title":"A Novel Welding Method for Repairing Surface Defects of Large-Type Rotary Machinery Based on Line Structured Light Detection","authors":"Hao Fu, Hong Lu, Yongquan Zhang, Zidong Wu, He Huang, Shijie Liu, Shaojun Wang","doi":"10.1115/msec2022-85527","DOIUrl":"https://doi.org/10.1115/msec2022-85527","url":null,"abstract":"\u0000 Large-type rotary machinery is the core components of national major projects which is widely used aviation, electric power, metallurgy, energy and construction machinery industries. Surface defects of Large-type rotary machinery such as cracks and pits are usually processed into groove with a certain shape first, and then the processed groove is repaired by manual welding. This manual welding repair method has a low level of automation, and the repair quality of the groove is difficult to guarantee. Therefore, this paper proposes a novel welding method for repairing surface defects of Large-type rotary machinery which uses the Kollmorgen Joint Modular Robot to complete the welding repair of the processed groove. Firstly, the groove point cloud data collected by Line structured light sensor is processed by the designed algorithm to obtain the contour characteristics of the groove. Then, the arrangement of welding pass is completed based on contour characteristics of the groove. Finally, the trajectory of the welding robot is determined by the position of welding pass. The planned trajectory verification is completed on the simulation experiment platform and the result shows the accuracy and reliability of the planned trajectory which has certain theoretical and practical significance for realizing the automation of on-site maintenance of Large-type rotary machinery.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":"17 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84426616","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 manufacturing industries, spherical micro-particles are commonly used as (e.g., brazing powder, metal filler, and 3D printing powder) which are produced with droplet-based particle fabrication techniques. Such processes create spherical morphology but introduce polydispersity and follow a continuous exponential pattern commonly expressed with Rosin-Rammler expression. Sorting those micro-particles in a narrower size range is an important but difficult, costly, and challenging process. Here we demonstrate the successful separation of the particles from a poly-disperse mixture with a particle volume fraction of 10% by dipping process. Nickel-based micro-particles (avg. dia. 5.69 μm) are added in a binder-based liquid carrier system. To encounter the gravitational force, external kinetic energy in the form of agitation is applied to ensure the uniform dispersion of the particles. The cylindrical substrate is prepared and dipped in the ‘pseudo suspension’ to separate the particles by adhering to it. The substrate is dried, and images are taken to characterize the separated particles using image J software. A clear size distribution can be observed which is also plotted. Additionally, a relationship between the process parameter and sorted particles has been established. The proposed method is quick, controllable, and easy to implement, which can be a useful tool for sorting wide-range poly-disperse particles.
{"title":"Size-Based Filtration of Poly-Disperse Micro-Particle by Dipping","authors":"M. Khalil, Bashir Khoda","doi":"10.1115/msec2022-85680","DOIUrl":"https://doi.org/10.1115/msec2022-85680","url":null,"abstract":"\u0000 In manufacturing industries, spherical micro-particles are commonly used as (e.g., brazing powder, metal filler, and 3D printing powder) which are produced with droplet-based particle fabrication techniques. Such processes create spherical morphology but introduce polydispersity and follow a continuous exponential pattern commonly expressed with Rosin-Rammler expression. Sorting those micro-particles in a narrower size range is an important but difficult, costly, and challenging process. Here we demonstrate the successful separation of the particles from a poly-disperse mixture with a particle volume fraction of 10% by dipping process. Nickel-based micro-particles (avg. dia. 5.69 μm) are added in a binder-based liquid carrier system. To encounter the gravitational force, external kinetic energy in the form of agitation is applied to ensure the uniform dispersion of the particles. The cylindrical substrate is prepared and dipped in the ‘pseudo suspension’ to separate the particles by adhering to it. The substrate is dried, and images are taken to characterize the separated particles using image J software. A clear size distribution can be observed which is also plotted. Additionally, a relationship between the process parameter and sorted particles has been established. The proposed method is quick, controllable, and easy to implement, which can be a useful tool for sorting wide-range poly-disperse particles.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":"87 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73113123","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}
Shilun Du, Murong Li, Tian Xu, Yingda Hu, Zhen Wang, Yong Lei
3D needle insertion is important both in theoretical research and clinic practice. In literature, most needle insertion experiments use 2D experiment platforms. A few studies use 3D experiment platforms based on ultrasound or traditional stereo camera. The ultrasound has low resolution and traditional stereo camera is difficult to reconstruct objects without textures, which is not suitable for markers reconstruction. Hence, it is needed to design a 3D needle insertion experiment platform with high resolution and 3D reconstruction ability. In this paper, we design a 3D needle insertion platform based on the orthogonal-arranged dual camera. Error analysis and accuracy verification are carried out as well. First, experiment platform framework is designed and essential modules are introduced. Second, the error analyses based on Frechet distance are carried out to quantify the error led by the bevel facing angle and insertion angle. Third, to verify the 3D reconstruction accuracy, the 2D distance sensitivity experiments and 3D reconstruction experiments are carried out for the dual camera system. The accuracy of 3D reconstruction in the region of interest has been verified. To optimize the 3D needle insertion platform, a needle holder to ensure concentricity is applied. Besides, pre-insertion process and orthogonal-arranged double chessboard calibration are introduced into setup procedures. Finally, a 3D needle insertion experiment platform is designed and validated through needle path planning algorithm verification. Results show that the proposed experiment platform can steer the needle accurately and reconstruct the needle path and markers in acceptable accuracy.
{"title":"Design and Analysis of a Novel Experiment Platform for 3D Needle Insertion Based on Orthogonally Arranged Dual Camera","authors":"Shilun Du, Murong Li, Tian Xu, Yingda Hu, Zhen Wang, Yong Lei","doi":"10.1115/msec2022-85764","DOIUrl":"https://doi.org/10.1115/msec2022-85764","url":null,"abstract":"\u0000 3D needle insertion is important both in theoretical research and clinic practice. In literature, most needle insertion experiments use 2D experiment platforms. A few studies use 3D experiment platforms based on ultrasound or traditional stereo camera. The ultrasound has low resolution and traditional stereo camera is difficult to reconstruct objects without textures, which is not suitable for markers reconstruction. Hence, it is needed to design a 3D needle insertion experiment platform with high resolution and 3D reconstruction ability. In this paper, we design a 3D needle insertion platform based on the orthogonal-arranged dual camera. Error analysis and accuracy verification are carried out as well. First, experiment platform framework is designed and essential modules are introduced. Second, the error analyses based on Frechet distance are carried out to quantify the error led by the bevel facing angle and insertion angle. Third, to verify the 3D reconstruction accuracy, the 2D distance sensitivity experiments and 3D reconstruction experiments are carried out for the dual camera system. The accuracy of 3D reconstruction in the region of interest has been verified. To optimize the 3D needle insertion platform, a needle holder to ensure concentricity is applied. Besides, pre-insertion process and orthogonal-arranged double chessboard calibration are introduced into setup procedures. Finally, a 3D needle insertion experiment platform is designed and validated through needle path planning algorithm verification. Results show that the proposed experiment platform can steer the needle accurately and reconstruct the needle path and markers in acceptable accuracy.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79802299","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}
Metal additive manufacturing technology that uses arc welding technology to deposit material is called wire arc additive manufacturing. Robotic manipulators that have a large workspace to size ratio are used to enable wire arc additive manufacturing. Wire arc additive manufacturing is gaining popularity due to the fast build time achieved by the high material deposition rates. It can build large-scale parts at a faster speed compared to other metal additive manufacturing processes. Utilizing a tilting build platform along with a robotic manipulator referred to as a multi-axis setup can enhance the capability of wire arc additive manufacturing. It will allow the setup to build complex supportless geometries that are not possible otherwise. However, maintaining a constant layer height while performing multi-axis wire arc additive manufacturing is challenging due to the forces involved in the process. This paper presents a new sensor-based two-step process along with the tool trajectory generation for maintaining constant layer height while performing multi-axis wire arc additive manufacturing. As the first step, we regulate the tool trajectory velocity to minimize the variation in the layer height. In the second step, we develop a sensor-based intervention scheme to fix the variation in the layer height by introducing additional height compensation layers. Finally, we test our approach by building a few parts, including a tool for the composite layup process.
{"title":"Robot Trajectory Generation for Multi-Axis Wire Arc Additive Manufacturing","authors":"P. Bhatt, Zachary McNulty, S. Gupta","doi":"10.1115/msec2022-85701","DOIUrl":"https://doi.org/10.1115/msec2022-85701","url":null,"abstract":"\u0000 Metal additive manufacturing technology that uses arc welding technology to deposit material is called wire arc additive manufacturing. Robotic manipulators that have a large workspace to size ratio are used to enable wire arc additive manufacturing. Wire arc additive manufacturing is gaining popularity due to the fast build time achieved by the high material deposition rates. It can build large-scale parts at a faster speed compared to other metal additive manufacturing processes. Utilizing a tilting build platform along with a robotic manipulator referred to as a multi-axis setup can enhance the capability of wire arc additive manufacturing. It will allow the setup to build complex supportless geometries that are not possible otherwise. However, maintaining a constant layer height while performing multi-axis wire arc additive manufacturing is challenging due to the forces involved in the process. This paper presents a new sensor-based two-step process along with the tool trajectory generation for maintaining constant layer height while performing multi-axis wire arc additive manufacturing. As the first step, we regulate the tool trajectory velocity to minimize the variation in the layer height. In the second step, we develop a sensor-based intervention scheme to fix the variation in the layer height by introducing additional height compensation layers. Finally, we test our approach by building a few parts, including a tool for the composite layup process.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":"52 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79858874","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}
Jiwei Zhou, Jorge D. Camba, N. Hartman, Zhongtian Li
As organizations embrace Industry 4.0 and its corresponding digital transformation, new technologies and practices are enabling more resilient, integrated, and sustainable approaches to product development. Researchers have explored the information flows and data relationships between requirements management (RQM) practices and Computer-Aided Design (CAD) to improve New Product Development (NPD) processes. Similarly, Life Cycle Assessment (LCA) tools can be used to assess the environmental impact of a product at the early stages of development. In this paper, we propose a novel approach to integrate RQM, CAD, and LCA in the NPD process in a manner that extends the “digital thread” of information from the definition of design requirements to the geometry of the digital product model. Specifically, we demonstrate the seeding of mechanical design models directly from design requirements as a starting point for parametrization, the linking of data items to facilitate subsequent design changes involving geometry, and the use of data connections between requirements and 3D models for continuous design verification. Our approach is supported by a Product Lifecycle Management (PLM) system and involves a workflow with several stages and various inputs from stakeholders. We validate our approach through the implementation of a case study involving a mechanical assembly and a commercial PLM system.
{"title":"An Approach to Extend the Digital Thread From Requirements to Model Geometry","authors":"Jiwei Zhou, Jorge D. Camba, N. Hartman, Zhongtian Li","doi":"10.1115/msec2022-80857","DOIUrl":"https://doi.org/10.1115/msec2022-80857","url":null,"abstract":"\u0000 As organizations embrace Industry 4.0 and its corresponding digital transformation, new technologies and practices are enabling more resilient, integrated, and sustainable approaches to product development. Researchers have explored the information flows and data relationships between requirements management (RQM) practices and Computer-Aided Design (CAD) to improve New Product Development (NPD) processes. Similarly, Life Cycle Assessment (LCA) tools can be used to assess the environmental impact of a product at the early stages of development. In this paper, we propose a novel approach to integrate RQM, CAD, and LCA in the NPD process in a manner that extends the “digital thread” of information from the definition of design requirements to the geometry of the digital product model. Specifically, we demonstrate the seeding of mechanical design models directly from design requirements as a starting point for parametrization, the linking of data items to facilitate subsequent design changes involving geometry, and the use of data connections between requirements and 3D models for continuous design verification. Our approach is supported by a Product Lifecycle Management (PLM) system and involves a workflow with several stages and various inputs from stakeholders. We validate our approach through the implementation of a case study involving a mechanical assembly and a commercial PLM system.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":"33 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80755553","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}
Chih-yu Chen, Leonard Freißmuth, Suat Mert Altug, D. Colin, Matthias Feuchtgruber, K. Drechsler
Fused filament fabrication (FFF), a type of extrusion-based additive manufacturing method, has proven its suitability for the production of highly complex components without costly tooling. However, traditional FFF systems are restricted to planar layer deposition, which results in poor surface smoothness and a reduction in strength and stiffness along the layer-stacking direction. Recent advancements in the FFF process have made it possible to reinforce and strengthen the printed parts with continuous fibers, which significantly increases the material’s anisotropy. Therefore, non-planar printing is necessary to optimize the anisotropic material behavior. This paper proposes a non-planar slicing method for optimizing the performance of continuous fiber-reinforced FFF parts printed using a 6-DOF industrial robot. The computational framework allows for the deposition of material on non-planar surfaces along the direction of the largest principal stress obtained from a finite element analysis following topology optimization. Three parts were successfully sliced and printed in a non-planar manner to generate stress-oriented toolpaths for continuous fiber-reinforced FFF using a 6-DOF robotic arm.
{"title":"Non-Planar Slicing Method for Maximizing the Anisotropic Behavior of Continuous Fiber-Reinforced Fused Filament Fabricated Parts","authors":"Chih-yu Chen, Leonard Freißmuth, Suat Mert Altug, D. Colin, Matthias Feuchtgruber, K. Drechsler","doi":"10.1115/msec2022-78670","DOIUrl":"https://doi.org/10.1115/msec2022-78670","url":null,"abstract":"\u0000 Fused filament fabrication (FFF), a type of extrusion-based additive manufacturing method, has proven its suitability for the production of highly complex components without costly tooling. However, traditional FFF systems are restricted to planar layer deposition, which results in poor surface smoothness and a reduction in strength and stiffness along the layer-stacking direction. Recent advancements in the FFF process have made it possible to reinforce and strengthen the printed parts with continuous fibers, which significantly increases the material’s anisotropy. Therefore, non-planar printing is necessary to optimize the anisotropic material behavior. This paper proposes a non-planar slicing method for optimizing the performance of continuous fiber-reinforced FFF parts printed using a 6-DOF industrial robot. The computational framework allows for the deposition of material on non-planar surfaces along the direction of the largest principal stress obtained from a finite element analysis following topology optimization. Three parts were successfully sliced and printed in a non-planar manner to generate stress-oriented toolpaths for continuous fiber-reinforced FFF using a 6-DOF robotic arm.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":"6 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83695487","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}
Finite element analysis (FEA) of fused deposition modeling (FDM) has recently been recognized in additive manufacturing (AM) for predictions in temperature gradient of three-dimensions (3D) printed components. These predictions can be invaluable for making corrections to the printing process to improve quality of printed components. However, FEA has its limitations. For example, models with fine mesh (small element size) yield more accurate results than ones with coarse mesh (large element size). Comparing with the coarse mesh model, a fine mesh model can take considerably longer computational times and discourages most manufacturers from using FEA. In this work, an innovative deep-learning (DL) based super-resolution approach is used to improve the result accuracy of a coarse mesh model to the higher accuracy level of a fine mesh model and reduce the computational time. The element in the FEA was treated as the physical pixel in an image, so the fine temperature grid and coarse temperature grid in the FEA were analogous to high resolution (HR) images and low resolution (LR) images, respectively. The result shows that the difference value HS between HR image and super resolution (SR) image is much smaller than the one HL between HR image and LR image, which demonstrated that our proposed DL-based super-resolution approach was effective to enhance the result accuracy of the coarse mesh model. Besides, both the increased Peak Signal-to-Nosie Ratio (PSNR) value and Structural Similarity Index (SSIM) value indicated that the quality of the images was also improved through the super-resolution approach.
{"title":"Deep Learning-Based Super-Resolution for the Finite Element Analysis of Additive Manufacturing Process","authors":"Yi Zhang, E. Freeman","doi":"10.1115/msec2022-79992","DOIUrl":"https://doi.org/10.1115/msec2022-79992","url":null,"abstract":"\u0000 Finite element analysis (FEA) of fused deposition modeling (FDM) has recently been recognized in additive manufacturing (AM) for predictions in temperature gradient of three-dimensions (3D) printed components. These predictions can be invaluable for making corrections to the printing process to improve quality of printed components. However, FEA has its limitations. For example, models with fine mesh (small element size) yield more accurate results than ones with coarse mesh (large element size). Comparing with the coarse mesh model, a fine mesh model can take considerably longer computational times and discourages most manufacturers from using FEA. In this work, an innovative deep-learning (DL) based super-resolution approach is used to improve the result accuracy of a coarse mesh model to the higher accuracy level of a fine mesh model and reduce the computational time. The element in the FEA was treated as the physical pixel in an image, so the fine temperature grid and coarse temperature grid in the FEA were analogous to high resolution (HR) images and low resolution (LR) images, respectively. The result shows that the difference value HS between HR image and super resolution (SR) image is much smaller than the one HL between HR image and LR image, which demonstrated that our proposed DL-based super-resolution approach was effective to enhance the result accuracy of the coarse mesh model. Besides, both the increased Peak Signal-to-Nosie Ratio (PSNR) value and Structural Similarity Index (SSIM) value indicated that the quality of the images was also improved through the super-resolution approach.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":"3 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89534887","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}
Olalekan O. Olowo, Ruoshi Zhang, A. Sherehiy, B. Goulet, Alexander Curry, Danming Wei, Zhong Yang, Moath H. A. Alqatamin, D. Popa
Enhancing physical human-robot interaction requires the improvement in the tactile perception of physical touch. Robot skin sensors exhibiting piezoresistive behavior can be used in conjunction with collaborative robots. In past work, fabrication of these tactile arrays was done using cleanroom techniques such as spin coating, photolithography, sputtering, wet and dry etching onto flexible polymers. In this paper, we present an addictive, non-cleanroom improved process of depositing PEDOT: PSS, which is the organic polymer responsible for the piezoresistive phenomenon of the robot skin sensor arrays. This publication details the patterning of the robot skin sensor structures and the adaptation of the inkjet printing technology to the fabrication process. This increases the possibility of scaling the production output while reducing the cleanroom fabrication cost and time from an approximately five-hour PEDOT: PSS deposition process to five minutes. Furthermore, the testing of these skin sensor arrays is carried out on a testing station equipped with a force plunger and an integrated circuit designed to provide perception feedback on various force load profiles controlled in an automated process. The results show uniform deposition of the PEDOT: PSS, consistent resistance measurement, and appropriate tactile response across an array of 16 sensors.
{"title":"Inkjet Printing of PEDOT:PSS Inks for Robotic Skin Sensors","authors":"Olalekan O. Olowo, Ruoshi Zhang, A. Sherehiy, B. Goulet, Alexander Curry, Danming Wei, Zhong Yang, Moath H. A. Alqatamin, D. Popa","doi":"10.1115/msec2022-80989","DOIUrl":"https://doi.org/10.1115/msec2022-80989","url":null,"abstract":"\u0000 Enhancing physical human-robot interaction requires the improvement in the tactile perception of physical touch. Robot skin sensors exhibiting piezoresistive behavior can be used in conjunction with collaborative robots. In past work, fabrication of these tactile arrays was done using cleanroom techniques such as spin coating, photolithography, sputtering, wet and dry etching onto flexible polymers. In this paper, we present an addictive, non-cleanroom improved process of depositing PEDOT: PSS, which is the organic polymer responsible for the piezoresistive phenomenon of the robot skin sensor arrays. This publication details the patterning of the robot skin sensor structures and the adaptation of the inkjet printing technology to the fabrication process. This increases the possibility of scaling the production output while reducing the cleanroom fabrication cost and time from an approximately five-hour PEDOT: PSS deposition process to five minutes. Furthermore, the testing of these skin sensor arrays is carried out on a testing station equipped with a force plunger and an integrated circuit designed to provide perception feedback on various force load profiles controlled in an automated process. The results show uniform deposition of the PEDOT: PSS, consistent resistance measurement, and appropriate tactile response across an array of 16 sensors.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":"7 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90834437","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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