Metal matrix composites (MMCs) possess a favorable combinations of mechanical, thermal, physical and metallurgical properties which can be engineered by controlling composition, concentration, size and dispersion of the ceramic particles in the metallic matrix. Laser directed energy deposition (DED) technique has the ability to fabricate MMC coatings with good mechanical properties and sound metallurgical bonding. Owing to those beneficial aspects, LDED has become one of the most important fabrication techniques of MMC. Despite of immense applications of MMCs, there has been very limited research work reported in the literature regarding the development of MMC coatings. In the present study, Inconel 718/Yttria-stabilized zirconia (YSZ) MMC coating is deposited on the H13 steel substrate via laser DED process. This MMC can find its application as ultra-high strength thermal barrier coatings in aerospace, power generation, defense equipment manufacturing and die/mold making industries. Three types of MMCs, Inconel-1 wt. % YSZ, Inconel-2 wt. % YSZ, and Inconel-3 wt. % YSZ are fabricated in order to assess the effect of YSZ weight percentage on the microstructure and mechanical properties (i.e., micro-hardness and porosity) of the MMC. Based on the mechanical properties and microstructural study, the optimum amount of YSZ in MMC is determined and it is observed that Inconel-1 wt. % YSZ composite coating exhibits better mechanical (i.e., hardness = 495 ± 7 HV, and porosity = 4 %) and metallurgical properties.
{"title":"Microstructure and Mechanical Properties of Inconel 718 / Yttria-Stabilized Zirconia (YSZ) Metal Matrix Composite Coating Produced by Laser Directed Energy Deposition Technique","authors":"G. Ghosh, Prakhar Jain, A. Saigal, Ramesh Singh","doi":"10.1115/imece2022-96945","DOIUrl":"https://doi.org/10.1115/imece2022-96945","url":null,"abstract":"\u0000 Metal matrix composites (MMCs) possess a favorable combinations of mechanical, thermal, physical and metallurgical properties which can be engineered by controlling composition, concentration, size and dispersion of the ceramic particles in the metallic matrix. Laser directed energy deposition (DED) technique has the ability to fabricate MMC coatings with good mechanical properties and sound metallurgical bonding. Owing to those beneficial aspects, LDED has become one of the most important fabrication techniques of MMC. Despite of immense applications of MMCs, there has been very limited research work reported in the literature regarding the development of MMC coatings. In the present study, Inconel 718/Yttria-stabilized zirconia (YSZ) MMC coating is deposited on the H13 steel substrate via laser DED process. This MMC can find its application as ultra-high strength thermal barrier coatings in aerospace, power generation, defense equipment manufacturing and die/mold making industries. Three types of MMCs, Inconel-1 wt. % YSZ, Inconel-2 wt. % YSZ, and Inconel-3 wt. % YSZ are fabricated in order to assess the effect of YSZ weight percentage on the microstructure and mechanical properties (i.e., micro-hardness and porosity) of the MMC. Based on the mechanical properties and microstructural study, the optimum amount of YSZ in MMC is determined and it is observed that Inconel-1 wt. % YSZ composite coating exhibits better mechanical (i.e., hardness = 495 ± 7 HV, and porosity = 4 %) and metallurgical properties.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123094081","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}
With rising requirements for digitalization, corporations must increase the speed in which their production and products are digitized. Because of that, there is an increasing demand of software developers which has led to a high skill shortage in Germany. Combined with rising expectations for speed and costs to develop a platform, this led to a problem, that needs to be solved. The goal of this paper is to estimate the benefit of using Low-Code platforms instead of traditional programming languages. Therefore, the elaboration deals with the central research question whether a Low-Code platform can support corporations through the skill shortage and at the same time reduce time and costs that it takes to develop an application. To answer this question, a Value Benefit Analysis was used to specify which platform provides the highest benefit for a use-case in the production of Vitesco Technologies in Dortmund. Thereupon, an example application was built to determine the usability. As final result, it can be concluded that the usage of Low-Code platforms in average leads to less time and costs that is needed for the development. In addition, these platforms are easy to use even without prior knowledge which leads to an advantage that can be used during a skill shortage. On the other hand, it also results in less flexibility which makes it harder to program complex functionalities. This demonstrates that a Low-Code platform can provide a great benefit when used for simple applications, whereas it is not useful for the use of more complex applications.
{"title":"The Use of Low-Code During a Skill Shortage","authors":"Aaron Büscher, Daniel Schilberg, Lars Wiegert","doi":"10.1115/imece2022-95505","DOIUrl":"https://doi.org/10.1115/imece2022-95505","url":null,"abstract":"\u0000 With rising requirements for digitalization, corporations must increase the speed in which their production and products are digitized. Because of that, there is an increasing demand of software developers which has led to a high skill shortage in Germany. Combined with rising expectations for speed and costs to develop a platform, this led to a problem, that needs to be solved.\u0000 The goal of this paper is to estimate the benefit of using Low-Code platforms instead of traditional programming languages. Therefore, the elaboration deals with the central research question whether a Low-Code platform can support corporations through the skill shortage and at the same time reduce time and costs that it takes to develop an application.\u0000 To answer this question, a Value Benefit Analysis was used to specify which platform provides the highest benefit for a use-case in the production of Vitesco Technologies in Dortmund. Thereupon, an example application was built to determine the usability.\u0000 As final result, it can be concluded that the usage of Low-Code platforms in average leads to less time and costs that is needed for the development. In addition, these platforms are easy to use even without prior knowledge which leads to an advantage that can be used during a skill shortage. On the other hand, it also results in less flexibility which makes it harder to program complex functionalities.\u0000 This demonstrates that a Low-Code platform can provide a great benefit when used for simple applications, whereas it is not useful for the use of more complex applications.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"26 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129925175","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}
We propose a level-set method for topology optimization to design acoustic structures without unsupported floating structures. The proposed method involves developing an artificial physical model for detecting floating structures and an objective function for eliminating them. As a design problem, we chose acoustic cloaking and formulated a topology optimization problem under geometric constraints. We applied an optimization algorithm that includes finite element analysis for the acoustic system and an artificial physical field. We provide several numerical examples demonstrating the validity and applicability of the proposed method, and we show how it can be used to design a cloaking structure without any floating components.
{"title":"Topology Optimization for Acoustic Structures Without Floating Components","authors":"Y. Noguchi, Yusei Ohta, K. Matsushima, T. Yamada","doi":"10.1115/imece2022-94365","DOIUrl":"https://doi.org/10.1115/imece2022-94365","url":null,"abstract":"\u0000 We propose a level-set method for topology optimization to design acoustic structures without unsupported floating structures. The proposed method involves developing an artificial physical model for detecting floating structures and an objective function for eliminating them. As a design problem, we chose acoustic cloaking and formulated a topology optimization problem under geometric constraints. We applied an optimization algorithm that includes finite element analysis for the acoustic system and an artificial physical field. We provide several numerical examples demonstrating the validity and applicability of the proposed method, and we show how it can be used to design a cloaking structure without any floating components.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130184890","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}
H. Taheri, C. Williams, Russell Krenek, G. Weaver, Mohammad Taheri
Additive manufacturing (AM) techniques are becoming accepted as routine in many industrial fields that include aerospace applications. This ramp up in manufacturing has highlighted a fundamental need for innovative nondestructive testing (NDT) methodologies for AM inspection and qualification purposes. Resonance Ultrasound Spectroscopy (RUS) is beginning to be applied as an innovative NDT inspection technique for AM components to obtain insights from the parts’ structural integrity and because it correlates to mechanical properties. RUS is used to understand sensitivity to detecting internal flaws, resulting in lower than expected failure resistance or fatigue life. Multiple test bar batches using the Ti6Al4V alloy were fabricated by powder bed fusion (PBF) AM technique at different processing conditions. RUS and destructive tests, including tensile and fatigue tests, based on ASTM standards are performed in order to evaluate the mechanical properties and tensile and fatigue strength of the parts. Finally, metallography experiments revealed the microstructure of the parts. The goal of correlation analysis is to establish the defect-NDT-property relationship for the Ti6Al4V by showing the strength and significance of the relationship between the testing data and the properties of the samples. Results show that RUS is a reliable and capable NDT technique to acquire rapid information for this purpose. This information is crucial for expanding the production and application of AM components while making sure that the mechanical properties, their structural integrity, and part safety satisfy the requirement of the lifetime operation.
{"title":"Identification of Flaws and Assessment of Mechanical Properties in Additively Manufactured Titanium Parts Using Acoustic Resonance Ultrasound Spectroscopy (RUS)","authors":"H. Taheri, C. Williams, Russell Krenek, G. Weaver, Mohammad Taheri","doi":"10.1115/imece2022-94871","DOIUrl":"https://doi.org/10.1115/imece2022-94871","url":null,"abstract":"\u0000 Additive manufacturing (AM) techniques are becoming accepted as routine in many industrial fields that include aerospace applications. This ramp up in manufacturing has highlighted a fundamental need for innovative nondestructive testing (NDT) methodologies for AM inspection and qualification purposes. Resonance Ultrasound Spectroscopy (RUS) is beginning to be applied as an innovative NDT inspection technique for AM components to obtain insights from the parts’ structural integrity and because it correlates to mechanical properties. RUS is used to understand sensitivity to detecting internal flaws, resulting in lower than expected failure resistance or fatigue life. Multiple test bar batches using the Ti6Al4V alloy were fabricated by powder bed fusion (PBF) AM technique at different processing conditions. RUS and destructive tests, including tensile and fatigue tests, based on ASTM standards are performed in order to evaluate the mechanical properties and tensile and fatigue strength of the parts. Finally, metallography experiments revealed the microstructure of the parts. The goal of correlation analysis is to establish the defect-NDT-property relationship for the Ti6Al4V by showing the strength and significance of the relationship between the testing data and the properties of the samples. Results show that RUS is a reliable and capable NDT technique to acquire rapid information for this purpose. This information is crucial for expanding the production and application of AM components while making sure that the mechanical properties, their structural integrity, and part safety satisfy the requirement of the lifetime operation.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116564796","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}
Munir Zarea, Evan Brown, Allen George, Joshua Kozsey, Tyler Palmgren, Meng-Chien Wu, Sarah Oman, J. Parmigiani, Joseph R. Piacenza, S. Piacenza
Sharks are powerful predators that make long-range migrations across vast swaths of the ocean. Scientists attach satellite telemetry tracking tags to sharks in order to gather data on behavior, movement patterns and habitat usage. However, hydro-dynamic loading from these tags may unintentionally influence the host shark’s behavior, although the extent of the loading is still not well understood. While tag manufacturers have made incremental improvements to make tags lighter and smaller, there is still not a clear understanding between tag design and host animal impacts. This fundamental knowledge gap makes the design of telemetry tags difficult when aiming to minimize hydrodynamic effects. In this paper, we present an approach intended to help inform tag design. In addition, a case study demonstrates this approach using 3D digital models discussed in the introduction. Four different shark species: the great hammerhead (Sphyrna mokarran), shortfin mako (Isurus oxyrinchus), blacktip reef (Carcharhinus limbatus), and Caribbean reef (Carcharhinus perezii). We used computational fluid dynamics (CFD) methods to estimate baseline drag and lift coefficients from a range of angles of attack to simulate the sharks ascending, descending, and swimming horizontally. We solved lift and drag coefficients through force reports integrated into the CFD software, STAR-CCM+. The simulations were solved with the Menter shear stress transport (SST) k-ω turbulence model at steady-state. Across species, the drag and lift coefficients ranged from 0.14 – 0.21 and −0.02 – 0.37, respectively. To visualize the fluid dynamics, we created plots of pressure distribution and fluid flow associated with each shark’s average cruising speeds, providing insight for future researchers investigating optimal tag placement that minimizes the tag’s impact. To validate the computational models, we performed wind tunnel testing by using 3D printed models of each shark, allowing us to empirically measure lift and drag forces. A three-axis sting-balance style measurement system with strain gauges was used, while considering wind speed, fluid density, and matched Reynolds numbers associated with the CFD models for each species. Finally, we statistically compared the computational and wind tunnel measurements. Moving forward, we will explore the changes in drag and lift with different satellite tag models attached to the shark species. Our findings will support development of a methodology to quantify the hydrodynamic impact of different tag designs on sharks. This can be used by future researchers to determine the lift and drag forces a shark experiences with a satellite telemetry tag attached. Ultimately, this information will help to better monitor sharks in their natural environment and provide information that can be useful to the conservation of the species.
{"title":"Analysis of Shark Fluid Dynamics to Guide Satellite Telemetry Tag Development","authors":"Munir Zarea, Evan Brown, Allen George, Joshua Kozsey, Tyler Palmgren, Meng-Chien Wu, Sarah Oman, J. Parmigiani, Joseph R. Piacenza, S. Piacenza","doi":"10.1115/imece2022-94838","DOIUrl":"https://doi.org/10.1115/imece2022-94838","url":null,"abstract":"\u0000 Sharks are powerful predators that make long-range migrations across vast swaths of the ocean. Scientists attach satellite telemetry tracking tags to sharks in order to gather data on behavior, movement patterns and habitat usage. However, hydro-dynamic loading from these tags may unintentionally influence the host shark’s behavior, although the extent of the loading is still not well understood. While tag manufacturers have made incremental improvements to make tags lighter and smaller, there is still not a clear understanding between tag design and host animal impacts. This fundamental knowledge gap makes the design of telemetry tags difficult when aiming to minimize hydrodynamic effects. In this paper, we present an approach intended to help inform tag design. In addition, a case study demonstrates this approach using 3D digital models discussed in the introduction. Four different shark species: the great hammerhead (Sphyrna mokarran), shortfin mako (Isurus oxyrinchus), blacktip reef (Carcharhinus limbatus), and Caribbean reef (Carcharhinus perezii). We used computational fluid dynamics (CFD) methods to estimate baseline drag and lift coefficients from a range of angles of attack to simulate the sharks ascending, descending, and swimming horizontally. We solved lift and drag coefficients through force reports integrated into the CFD software, STAR-CCM+. The simulations were solved with the Menter shear stress transport (SST) k-ω turbulence model at steady-state. Across species, the drag and lift coefficients ranged from 0.14 – 0.21 and −0.02 – 0.37, respectively. To visualize the fluid dynamics, we created plots of pressure distribution and fluid flow associated with each shark’s average cruising speeds, providing insight for future researchers investigating optimal tag placement that minimizes the tag’s impact. To validate the computational models, we performed wind tunnel testing by using 3D printed models of each shark, allowing us to empirically measure lift and drag forces. A three-axis sting-balance style measurement system with strain gauges was used, while considering wind speed, fluid density, and matched Reynolds numbers associated with the CFD models for each species. Finally, we statistically compared the computational and wind tunnel measurements. Moving forward, we will explore the changes in drag and lift with different satellite tag models attached to the shark species. Our findings will support development of a methodology to quantify the hydrodynamic impact of different tag designs on sharks. This can be used by future researchers to determine the lift and drag forces a shark experiences with a satellite telemetry tag attached. Ultimately, this information will help to better monitor sharks in their natural environment and provide information that can be useful to the conservation of the species.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"436 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132557683","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}
Xiaoxu Liu, Yoshiki Tanaka, S. Maegawa, Shingo Ono, F. Itoigawa
With the pursuit of high-precision and high-efficiency machining, laser-assisted machining technology has attracted more and more attention. Especially, ultra-short pulse laser irradiation can facilitate a quite high cooling rate and produce a local active space, which can make the surface modification realized without any removal. In this study, a novel tribo-characteristic improvement technology using ultra-short pulse laser irradiation in oil, with the hydrocarbon composition in oil as a carbon source, was proposed, to realize the surface modification of the workpiece in the same process with machining. Herein, a Ti-6Al-4V disk was irradiated using a pico-second laser in PAO oil under 4 different conditions with changed effective irradiated laser pulses and scanning modes. Besides the uniform laser irradiation, patterning irradiation was also conducted. From the results of the reciprocating friction tests, compared to those uniformed irradiated specimens, patterning irradiation processed surfaces show obviously more stable friction than the as-received metal surface. More importantly, much longer lifetime has been obtained, indicating the enhanced wear resistance. According to the investigation of hardness distribution, laser-induced thermal strain in the patterning irradiation method is considered to be an important factor of wear resistance improvement.
{"title":"A New Tribo-Characteristic Improvement Technique by Ultra-Short Pulsed Laser Irradiation in PAO Oil","authors":"Xiaoxu Liu, Yoshiki Tanaka, S. Maegawa, Shingo Ono, F. Itoigawa","doi":"10.1115/imece2022-95237","DOIUrl":"https://doi.org/10.1115/imece2022-95237","url":null,"abstract":"\u0000 With the pursuit of high-precision and high-efficiency machining, laser-assisted machining technology has attracted more and more attention. Especially, ultra-short pulse laser irradiation can facilitate a quite high cooling rate and produce a local active space, which can make the surface modification realized without any removal. In this study, a novel tribo-characteristic improvement technology using ultra-short pulse laser irradiation in oil, with the hydrocarbon composition in oil as a carbon source, was proposed, to realize the surface modification of the workpiece in the same process with machining. Herein, a Ti-6Al-4V disk was irradiated using a pico-second laser in PAO oil under 4 different conditions with changed effective irradiated laser pulses and scanning modes. Besides the uniform laser irradiation, patterning irradiation was also conducted. From the results of the reciprocating friction tests, compared to those uniformed irradiated specimens, patterning irradiation processed surfaces show obviously more stable friction than the as-received metal surface. More importantly, much longer lifetime has been obtained, indicating the enhanced wear resistance. According to the investigation of hardness distribution, laser-induced thermal strain in the patterning irradiation method is considered to be an important factor of wear resistance improvement.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128083921","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}
Jacob D. O’Donnell, Michael C. Smith, P. Cavallaro
Cold spray is a novel thermal spray process in which a gas at high temperature and pressure deposits solid particles onto a substrate material. Current research utilizes a variety of methods of modeling techniques in order to capture the physics and dynamics of a cold spray particle impact, incorporating elements of the Lagrangian and Eulerian modeling methods. This research modeled the cold spray event of single and multi-particle impacts using Lagrangian and Eulerian methods. The material of both the particle and substrate are a standard Aluminum 6061-T6 alloy. The objectives of the models are to: (1) obtain particle and substrate deformations and residual stresses as functions of particle velocity, particle temperature, and substrate temperature; (2) establish the minimum number of successive particle layers such that the substrate residual stresses reach steady state; and (3) identify numerical limitations in the Lagrangian and Eulerian modeling methods using ABAQUS/Explicit. The Lagrangian method predicted a maximum von Mises stress 23.72% lower than that of the Eulerian. The Lagrangian models allowed for discrete node tracking, however, thus allowing for improved surface definitions and transient material point tracking. The Eulerian models also better handled the plastic deformation and resultant temperature generation within the model, and thus were able to handle multiple particle impacts while the Lagrangian could not. The multi-particle models using the Eulerian method reported that seven particles were required for the substrate steady-state stress to remain independent of subsequent particle impacts. Concentric initial position multi-particle models saw a maximum 42.00% reduction in von Mises stress compared to the single-particle models and a maximum 53.18% reduction compared to multi-particle modes with randomized initial particle positions. Multi-particle impacts demonstrated a reduction in stress when compared to the single particle impact due to the increased thermal softening present.
{"title":"Comparison of Residual Stresses in Cold Spray Coatings: Lagrangian vs. Eulerian Finite Element Methods","authors":"Jacob D. O’Donnell, Michael C. Smith, P. Cavallaro","doi":"10.1115/imece2022-93902","DOIUrl":"https://doi.org/10.1115/imece2022-93902","url":null,"abstract":"\u0000 Cold spray is a novel thermal spray process in which a gas at high temperature and pressure deposits solid particles onto a substrate material. Current research utilizes a variety of methods of modeling techniques in order to capture the physics and dynamics of a cold spray particle impact, incorporating elements of the Lagrangian and Eulerian modeling methods. This research modeled the cold spray event of single and multi-particle impacts using Lagrangian and Eulerian methods. The material of both the particle and substrate are a standard Aluminum 6061-T6 alloy. The objectives of the models are to: (1) obtain particle and substrate deformations and residual stresses as functions of particle velocity, particle temperature, and substrate temperature; (2) establish the minimum number of successive particle layers such that the substrate residual stresses reach steady state; and (3) identify numerical limitations in the Lagrangian and Eulerian modeling methods using ABAQUS/Explicit.\u0000 The Lagrangian method predicted a maximum von Mises stress 23.72% lower than that of the Eulerian. The Lagrangian models allowed for discrete node tracking, however, thus allowing for improved surface definitions and transient material point tracking. The Eulerian models also better handled the plastic deformation and resultant temperature generation within the model, and thus were able to handle multiple particle impacts while the Lagrangian could not. The multi-particle models using the Eulerian method reported that seven particles were required for the substrate steady-state stress to remain independent of subsequent particle impacts. Concentric initial position multi-particle models saw a maximum 42.00% reduction in von Mises stress compared to the single-particle models and a maximum 53.18% reduction compared to multi-particle modes with randomized initial particle positions. Multi-particle impacts demonstrated a reduction in stress when compared to the single particle impact due to the increased thermal softening present.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117295341","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}
Powder bed fusion (PBF) is a widely used metal additive manufacturing method. There is strong evidence that the performance of the final part built using PBF depends on the dispersive quality of the particle bed. Understanding this process through computational modeling and machine learning is an efficient low-cost way for process design. Discrete element method (DEM) is an effective tool for analyzing the particle flow behavior. However, one challenge for parametric modeling of highly multivariate powder spreading process through DEM is the high computational cost, for traversing the large parameter space. We address this problem through innovative use of parallel computing using GNU parallel, and by developing a machine learning algorithm to correlate the process parameters and spread quality. We first perform DEM simulations systematically varying four parameters, the particle size, the coefficient of friction, the spread layer thickness, and the recoating velocity. The dataset containing inputs with spread parameters and target variables that measure the spread quality are fed to a finely-tuned artificial neural network (ANN). We observe that the neural network presents at least 95% accuracy in predicting the test data. Ultimately this approach provides the parameter combinations that produce high quality compaction before sintering.
{"title":"An Artificial Neural Network for Parametric Analysis of Metallic Additive Manufacturing Using Discrete Element Method","authors":"Yuxuan Wu, S. Namilae","doi":"10.1115/imece2022-95117","DOIUrl":"https://doi.org/10.1115/imece2022-95117","url":null,"abstract":"\u0000 Powder bed fusion (PBF) is a widely used metal additive manufacturing method. There is strong evidence that the performance of the final part built using PBF depends on the dispersive quality of the particle bed. Understanding this process through computational modeling and machine learning is an efficient low-cost way for process design. Discrete element method (DEM) is an effective tool for analyzing the particle flow behavior. However, one challenge for parametric modeling of highly multivariate powder spreading process through DEM is the high computational cost, for traversing the large parameter space. We address this problem through innovative use of parallel computing using GNU parallel, and by developing a machine learning algorithm to correlate the process parameters and spread quality. We first perform DEM simulations systematically varying four parameters, the particle size, the coefficient of friction, the spread layer thickness, and the recoating velocity. The dataset containing inputs with spread parameters and target variables that measure the spread quality are fed to a finely-tuned artificial neural network (ANN). We observe that the neural network presents at least 95% accuracy in predicting the test data. Ultimately this approach provides the parameter combinations that produce high quality compaction before sintering.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131901189","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}
Quality control is a crucial component of every manufacturing process. Quality production can be done by removing the defective pieces before reaching the packaging line. Several innovative systems have proven the use of visual input and advanced computer processing to fulfill various production goals during the last several years. Product inspection technologies based on machine vision are extensively researched to increase the quality of the product and save expenses. Computer vision and Deep learning have recently evolved, resulting in powerful data analysis tools with excellent scanning quality and resilience. Authors have attempted in this direction using such a method to detect flaws present in the dimensions of the bottles, which are traveling continually on the conveyor belt. Using pictures collected from the camera, the Yolov5 object detection method is used to localize the bottle in the image. Then, the image is passed for pre-processing, such as image cropping, image gray scaling, and smoothening of the image. The next step of this algorithm uses canny edge detection to detect edges present in the image. The image with detected edges is in the form of a binary image. All the pixels are extracted from this binary image in the form of an array. After performing some mathematical calculations on the output array, the dimensions of the bottle can be determined. The bottles were inspected for any faults in the dimensions in the manufacturing. Any bottles with flaws in the dimensions are discarded and separated from the manufactured bottles. The first step of the algorithm is object detection; here, the model has achieved the mean average precision of nearly 99.5 percent for the confidence threshold set to 50 percent to 95 percent. The following entire algorithm runs in less than 847 milliseconds. Such a high-speed algorithm allows manufacturers to increase and decrease the manufacturing speed according to their needs. This algorithm can check any shape of bottle, and this algorithm is not limited to bottles, but it can also work for any shape of object. As this model is only trained on the images of the bottles, the model cannot instantly work on the other objects, but one can use transfer learning to use this model on different object. This algorithm can also detect defects in multiple objects in the production line containing the manufacturing of multiple objects in the same line. The model can classify the objects from the production line and can also be used to classify them wherever required.
{"title":"In-Process Intelligent Inspection of the Specimen Using Machine Vision","authors":"Adarsh Mahor, R. Yadav","doi":"10.1115/imece2022-95347","DOIUrl":"https://doi.org/10.1115/imece2022-95347","url":null,"abstract":"\u0000 Quality control is a crucial component of every manufacturing process. Quality production can be done by removing the defective pieces before reaching the packaging line. Several innovative systems have proven the use of visual input and advanced computer processing to fulfill various production goals during the last several years. Product inspection technologies based on machine vision are extensively researched to increase the quality of the product and save expenses. Computer vision and Deep learning have recently evolved, resulting in powerful data analysis tools with excellent scanning quality and resilience. Authors have attempted in this direction using such a method to detect flaws present in the dimensions of the bottles, which are traveling continually on the conveyor belt. Using pictures collected from the camera, the Yolov5 object detection method is used to localize the bottle in the image. Then, the image is passed for pre-processing, such as image cropping, image gray scaling, and smoothening of the image. The next step of this algorithm uses canny edge detection to detect edges present in the image. The image with detected edges is in the form of a binary image. All the pixels are extracted from this binary image in the form of an array. After performing some mathematical calculations on the output array, the dimensions of the bottle can be determined. The bottles were inspected for any faults in the dimensions in the manufacturing. Any bottles with flaws in the dimensions are discarded and separated from the manufactured bottles. The first step of the algorithm is object detection; here, the model has achieved the mean average precision of nearly 99.5 percent for the confidence threshold set to 50 percent to 95 percent. The following entire algorithm runs in less than 847 milliseconds. Such a high-speed algorithm allows manufacturers to increase and decrease the manufacturing speed according to their needs. This algorithm can check any shape of bottle, and this algorithm is not limited to bottles, but it can also work for any shape of object. As this model is only trained on the images of the bottles, the model cannot instantly work on the other objects, but one can use transfer learning to use this model on different object. This algorithm can also detect defects in multiple objects in the production line containing the manufacturing of multiple objects in the same line. The model can classify the objects from the production line and can also be used to classify them wherever required.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129762316","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}
Jianfeng Ma, M. Karim, Muhammud P. Jahan, S. Shim, S. Lei
Nickel-Titanium based Shape Memory Alloys (Ni-Ti SMAs), a group of special advanced engineering materials, are gaining popularity in industrial engineering and biomedical engineering for their superior properties. for example, amazing shape memory effects (SME), high strength, excellent corrosion and wear resistance, pseudoelasticity, outstanding biocompatibility and biodegradability. Industrial applications of Nickel-Titanium based SMAs include phone antennas, sensors and actuators in aerospace industry, automotive industries, and robotics. Biomedical engineering applications of this group of SMAs include cardiovascular field, neurosurgical field, orthodontic and orthopedic field. The fact that this group of SMAs are very sensitive to stress and mechanical tension makes it very difficult to be machined using conventional manufacturing processes. As a result, many research studies have focused on improving the machinability of this SMA using non-traditional manufacturing processes. In this study, the Continuum Surelite Class III nanosecond laser system with 1064 nm wavelength and 5 nanosecond pulse width is used to modify the surface of a Nickel-Titanium based SMA. The effects of laser pulse energy level and lens-to-samples distance on the crater and slot forming are evaluated. Single shot mode of the laser system is used to generate craters, and totally six laser pulse energy levels are used. In addition, three lens-to-sample distance values are selected. These six energy levels are 0.053 J, 0.122 J, 0.296 J, 0.415 J, 0.526 J, and 0.662 J, respectively. The three different lens-to-sample distance values are 150 mm, 170 mm, and 190 mm, respectively. The focal length of the lens is 150 mm. Continuous shot mode of the laser system is used to machine slots on the Ni-Ti based SMA. For slot forming, two energy levels (0.296 J and 0.662 J) and two lens-to-sample distance values (150 mm and 190 mm) along with two different overlapping ratios (0.75 and 0.95) are used. A 3D surface profilometer is used to study the variation of crater depth with laser parameters. The scanning electron microscope (SEM) and energy dispersive X-ray spectroscopy (EDS) analyses are used to investigate surface topography, surface modification, and laser-induced elemental composition on the Ni-Ti based SMA surfaces. The crater diameter and depth were found to vary with the laser energy levels and lens-to-sample distances. The surface finish and topography were also found to be influenced by the laser parameters. Finally, a suitable range of parameters for improved surface finish and targeted surface modification have been identified for nanosecond laser processing of Nickel-Titanium based SMA.
{"title":"Nanosecond Laser Modification of Nickel-Titanium Based Shape Memory Alloys","authors":"Jianfeng Ma, M. Karim, Muhammud P. Jahan, S. Shim, S. Lei","doi":"10.1115/imece2022-95292","DOIUrl":"https://doi.org/10.1115/imece2022-95292","url":null,"abstract":"\u0000 Nickel-Titanium based Shape Memory Alloys (Ni-Ti SMAs), a group of special advanced engineering materials, are gaining popularity in industrial engineering and biomedical engineering for their superior properties. for example, amazing shape memory effects (SME), high strength, excellent corrosion and wear resistance, pseudoelasticity, outstanding biocompatibility and biodegradability. Industrial applications of Nickel-Titanium based SMAs include phone antennas, sensors and actuators in aerospace industry, automotive industries, and robotics. Biomedical engineering applications of this group of SMAs include cardiovascular field, neurosurgical field, orthodontic and orthopedic field. The fact that this group of SMAs are very sensitive to stress and mechanical tension makes it very difficult to be machined using conventional manufacturing processes. As a result, many research studies have focused on improving the machinability of this SMA using non-traditional manufacturing processes. In this study, the Continuum Surelite Class III nanosecond laser system with 1064 nm wavelength and 5 nanosecond pulse width is used to modify the surface of a Nickel-Titanium based SMA. The effects of laser pulse energy level and lens-to-samples distance on the crater and slot forming are evaluated. Single shot mode of the laser system is used to generate craters, and totally six laser pulse energy levels are used. In addition, three lens-to-sample distance values are selected. These six energy levels are 0.053 J, 0.122 J, 0.296 J, 0.415 J, 0.526 J, and 0.662 J, respectively. The three different lens-to-sample distance values are 150 mm, 170 mm, and 190 mm, respectively. The focal length of the lens is 150 mm. Continuous shot mode of the laser system is used to machine slots on the Ni-Ti based SMA. For slot forming, two energy levels (0.296 J and 0.662 J) and two lens-to-sample distance values (150 mm and 190 mm) along with two different overlapping ratios (0.75 and 0.95) are used. A 3D surface profilometer is used to study the variation of crater depth with laser parameters. The scanning electron microscope (SEM) and energy dispersive X-ray spectroscopy (EDS) analyses are used to investigate surface topography, surface modification, and laser-induced elemental composition on the Ni-Ti based SMA surfaces. The crater diameter and depth were found to vary with the laser energy levels and lens-to-sample distances. The surface finish and topography were also found to be influenced by the laser parameters. Finally, a suitable range of parameters for improved surface finish and targeted surface modification have been identified for nanosecond laser processing of Nickel-Titanium based SMA.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130003238","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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