Xinyao Zhang, Kareem A. Eltouny, Xiao Liang, S. Behdad
Disassembly is an essential process for the recovery of end-of-life (EOL) electronics in remanufacturing sites. Nevertheless, the process remains labor-intensive due to EOL electronics’ high degree of uncertainty and complexity. The robotic technology can assist in improving disassembly efficiency, however, the characteristics of EOL electronics pose difficulties for robot operation, such as removing small components. For such tasks, detecting small objects is critical for robotic disassembly systems. Screws are widely used as fasteners in ordinary electronic products while having small sizes and varying shapes in a scene. To achieve robotic disassembly of screws, the location information and the required tools need to be predicted. This paper proposes a framework to automatically detect screws and recommend related tools for disassembly. First, the YOLOv4 algorithm is used to detect screw targets in EOL electronic devices, and then a screw image extraction mechanism is executed based on the position coordinates predicted by YOLOv4. Second, after obtaining the screw images, the EfficientNetv2 algorithm is applied for screw shape classification. In addition to proposing a framework for automatic small-object detection, we explore how to modify the object detection algorithm to improve its performance and discuss the sensitivity of tool recommendations to the detection predictions. A case study of three different types of screws is used to evaluate the performance of the proposed framework.
{"title":"Automatic Screw Detection and Tool Recommendation System for Robotic Disassembly","authors":"Xinyao Zhang, Kareem A. Eltouny, Xiao Liang, S. Behdad","doi":"10.1115/msec2022-85403","DOIUrl":"https://doi.org/10.1115/msec2022-85403","url":null,"abstract":"\u0000 Disassembly is an essential process for the recovery of end-of-life (EOL) electronics in remanufacturing sites. Nevertheless, the process remains labor-intensive due to EOL electronics’ high degree of uncertainty and complexity. The robotic technology can assist in improving disassembly efficiency, however, the characteristics of EOL electronics pose difficulties for robot operation, such as removing small components. For such tasks, detecting small objects is critical for robotic disassembly systems. Screws are widely used as fasteners in ordinary electronic products while having small sizes and varying shapes in a scene. To achieve robotic disassembly of screws, the location information and the required tools need to be predicted. This paper proposes a framework to automatically detect screws and recommend related tools for disassembly. First, the YOLOv4 algorithm is used to detect screw targets in EOL electronic devices, and then a screw image extraction mechanism is executed based on the position coordinates predicted by YOLOv4. Second, after obtaining the screw images, the EfficientNetv2 algorithm is applied for screw shape classification. In addition to proposing a framework for automatic small-object detection, we explore how to modify the object detection algorithm to improve its performance and discuss the sensitivity of tool recommendations to the detection predictions. A case study of three different types of screws is used to evaluate the performance of the proposed framework.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":"2013 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86467912","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}
Bioprinting for regenerative medicine has been gaining a lot of popularity in today’s world. Despite being one of the rigorously studied fields, there are still several challenges yet to be solved. Geometric fidelity and mechanical complexities stand as roadblocks when it comes to the printability of the customized scaffolds. Exploring the rheological properties of the compositions helps us understand the physical and mechanical properties of the biomaterials which are closely tied to the printability of the filament and eventually, geometric fidelity of the scaffolds. To ensure the structural integrity of the scaffolds, viscosity enhancers such as Carboxymethyl Cellulose (CMC) and crosslinkers like CaCl2 and CaSO4 were used. These crosslinkers can be used before (pre-crosslinking) and after (post-crosslinking) the extrusion of considered compositions to investigate and compare the outcome. To do this, mixtures of Carboxymethyl Cellulose (CMC, viscosity enhancer), Alginate, and CaCl2 and CaSO4 (crosslinkers) were prepared at various concentrations maintaining minimum solid content (≤ 8%). Each composition was subjected to a set of rheological tests like Flow curve for shear thinning behavior, three-point thixotropic for recovery rate, amplitude test for gelation point, and frequency tests. This research thoroughly investigates compositions when they are introduced to crosslinkers and viscosity enhancers which can be crucial for 3D printing world.
{"title":"Pre-Crosslinked Hybrid Hydrogels for 3D Bio-Printing Process: Rheological Analysis","authors":"Slesha Tuladhar, Cartwright Nelson, Md. Ahasan Habib","doi":"10.1115/msec2022-85700","DOIUrl":"https://doi.org/10.1115/msec2022-85700","url":null,"abstract":"\u0000 Bioprinting for regenerative medicine has been gaining a lot of popularity in today’s world. Despite being one of the rigorously studied fields, there are still several challenges yet to be solved. Geometric fidelity and mechanical complexities stand as roadblocks when it comes to the printability of the customized scaffolds. Exploring the rheological properties of the compositions helps us understand the physical and mechanical properties of the biomaterials which are closely tied to the printability of the filament and eventually, geometric fidelity of the scaffolds. To ensure the structural integrity of the scaffolds, viscosity enhancers such as Carboxymethyl Cellulose (CMC) and crosslinkers like CaCl2 and CaSO4 were used. These crosslinkers can be used before (pre-crosslinking) and after (post-crosslinking) the extrusion of considered compositions to investigate and compare the outcome. To do this, mixtures of Carboxymethyl Cellulose (CMC, viscosity enhancer), Alginate, and CaCl2 and CaSO4 (crosslinkers) were prepared at various concentrations maintaining minimum solid content (≤ 8%). Each composition was subjected to a set of rheological tests like Flow curve for shear thinning behavior, three-point thixotropic for recovery rate, amplitude test for gelation point, and frequency tests. This research thoroughly investigates compositions when they are introduced to crosslinkers and viscosity enhancers which can be crucial for 3D printing world.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":"31 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75891946","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}
Suyog Ghungrad, B. Gould, S. Wolff, Azadeh Haghighi
Prediction of the temperature history of printed paths in additive manufacturing is crucial towards establishing the process-structure-property relationship. Traditional approaches for predictions such as physics-based simulations are computationally costly and time-consuming, whereas data driven approaches are highly dependent on huge, labeled datasets. Moreover, these labeled datasets are mostly scarce and costly in additive manufacturing owing to its unique application domain (mass customization) and complicated data-gathering stage. Recently, model-based or physics-informed artificial intelligence approaches have shown promising potential in overcoming the existing limitations and challenges faced by purely analytical or data driven approaches. In this work, a novel physics-informed artificial intelligent structure for scenarios with limited data is presented and its performance for temperature prediction in the selective laser melting additive manufacturing process is compared with one of the state-of-the-art data driven approaches, namely long short-term memory (LSTM) neural networks. Temperature data for training and testing was extracted from infrared images of single-track layer-based experiments for Ti64 material with different combinations of process parameters. Compared to LSTM, the proposed approach has higher computational efficiency and achieves better accuracy in limited data scenarios, making it a potential candidate for real-time closed-loop control of the additive manufacturing process under limited and sparse data scenarios. In other words, the proposed model is capable to learn more efficiently under such scenarios in comparison to LSTM model.
{"title":"Physics-Informed Artificial Intelligence for Temperature Prediction in Metal Additive Manufacturing: A Comparative Study","authors":"Suyog Ghungrad, B. Gould, S. Wolff, Azadeh Haghighi","doi":"10.1115/msec2022-85159","DOIUrl":"https://doi.org/10.1115/msec2022-85159","url":null,"abstract":"\u0000 Prediction of the temperature history of printed paths in additive manufacturing is crucial towards establishing the process-structure-property relationship. Traditional approaches for predictions such as physics-based simulations are computationally costly and time-consuming, whereas data driven approaches are highly dependent on huge, labeled datasets. Moreover, these labeled datasets are mostly scarce and costly in additive manufacturing owing to its unique application domain (mass customization) and complicated data-gathering stage. Recently, model-based or physics-informed artificial intelligence approaches have shown promising potential in overcoming the existing limitations and challenges faced by purely analytical or data driven approaches. In this work, a novel physics-informed artificial intelligent structure for scenarios with limited data is presented and its performance for temperature prediction in the selective laser melting additive manufacturing process is compared with one of the state-of-the-art data driven approaches, namely long short-term memory (LSTM) neural networks. Temperature data for training and testing was extracted from infrared images of single-track layer-based experiments for Ti64 material with different combinations of process parameters. Compared to LSTM, the proposed approach has higher computational efficiency and achieves better accuracy in limited data scenarios, making it a potential candidate for real-time closed-loop control of the additive manufacturing process under limited and sparse data scenarios. In other words, the proposed model is capable to learn more efficiently under such scenarios in comparison to LSTM model.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":"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":"84719718","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}
Colin Warn, A. Sherehiy, Moath H. A. Alqatamin, Brooke Ritz, Ruoshi Zhang, S. Chowdhury, Danming Wei, D. Popa
In this paper, we propose a method for tracking a microrobot’s three-dimensional position using microscope machine vision. The microrobot, theSolid Articulated Four Axis Microrobot (sAFAM), is being developed to enable the assembly and manipulation of micro and nanoscale objects. In the future, arrays of sAFAMS working together can be integrated into a wafer-scale nanofactory, Prior to use, microrobots in this microfactory need calibration, which can be achieved using the proposed measurement technique. Our approach enables faster and more accurate mapping of microrobot translations and rotations, and orders of magnitude larger datasets can be created by automation. Cameras feeds on a custom microscopy system is fed into a data processing pipeline that enables tracking of the microrobot in real-time. This particular machine vision method was implemented with a help of OpenCV and Python and can be used to track the movement of other micrometer-sized features. Additionally, a script was created to enable automated repeatability tests for each of the six trajectories traversable by the robot. A more precise microrobot workable area was also determined thanks to the significantly larger datasets enabled by the combined automation and machine vision approaches.
{"title":"Machine Vision Tracking and Automation of a Microrobot (sAFAM)","authors":"Colin Warn, A. Sherehiy, Moath H. A. Alqatamin, Brooke Ritz, Ruoshi Zhang, S. Chowdhury, Danming Wei, D. Popa","doi":"10.1115/msec2022-85424","DOIUrl":"https://doi.org/10.1115/msec2022-85424","url":null,"abstract":"\u0000 In this paper, we propose a method for tracking a microrobot’s three-dimensional position using microscope machine vision. The microrobot, theSolid Articulated Four Axis Microrobot (sAFAM), is being developed to enable the assembly and manipulation of micro and nanoscale objects. In the future, arrays of sAFAMS working together can be integrated into a wafer-scale nanofactory, Prior to use, microrobots in this microfactory need calibration, which can be achieved using the proposed measurement technique. Our approach enables faster and more accurate mapping of microrobot translations and rotations, and orders of magnitude larger datasets can be created by automation. Cameras feeds on a custom microscopy system is fed into a data processing pipeline that enables tracking of the microrobot in real-time. This particular machine vision method was implemented with a help of OpenCV and Python and can be used to track the movement of other micrometer-sized features. Additionally, a script was created to enable automated repeatability tests for each of the six trajectories traversable by the robot. A more precise microrobot workable area was also determined thanks to the significantly larger datasets enabled by the combined automation and machine vision approaches.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":"76 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80545364","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 this study, a novel approach is proposed to enhance the performance of the parts optimized by Solid Isotropic Material with Penalization (SIMP) method. SIMP is a topology optimization method that aims the optimum distribution of material in a design domain subjected to predefined loads, constraints and boundary conditions. The method forces every finite element composing the geometry to have a density of either 1 or 0. The main reason behind penalizing is that regions with intermediate densities are difficult to fabricate. However, including these regions in the optimization output may provide better performance results. Based on this idea, a method is proposed to utilize intermediate densities in a manufacturable form and is applied to 3D geometries. Besides, the remodeled topology is checked against any unconnected cells. In contrast to many methods, which delete the unconnected elements, the proposed method provides connectivity by adding cells. The outputs of the proposed method are fabricated by using Electron Beam Melting (EBM) and Stereolithography (SLA) technologies. EBM uses material powder and a heat source to melt and fuse the powders while SLA uses photosensitive resin and an ultraviolet light to cure the resin. A common limitation of both technologies is that powder/resin may remain inside the internal features which do not have access to outer surface of the part through the channels. The proposed method ensures the easy removal of excess powder/resin after fabrication. Performance of the method is compared with the SIMP method through test and analysis.
{"title":"Tiling of Cellular Structures Into 3D Parts According to the Density Values of SIMP Topology Optimization","authors":"Damla Ozkapici Helvaci, U. Yaman","doi":"10.1115/msec2022-85307","DOIUrl":"https://doi.org/10.1115/msec2022-85307","url":null,"abstract":"\u0000 In this study, a novel approach is proposed to enhance the performance of the parts optimized by Solid Isotropic Material with Penalization (SIMP) method. SIMP is a topology optimization method that aims the optimum distribution of material in a design domain subjected to predefined loads, constraints and boundary conditions. The method forces every finite element composing the geometry to have a density of either 1 or 0. The main reason behind penalizing is that regions with intermediate densities are difficult to fabricate. However, including these regions in the optimization output may provide better performance results. Based on this idea, a method is proposed to utilize intermediate densities in a manufacturable form and is applied to 3D geometries. Besides, the remodeled topology is checked against any unconnected cells. In contrast to many methods, which delete the unconnected elements, the proposed method provides connectivity by adding cells.\u0000 The outputs of the proposed method are fabricated by using Electron Beam Melting (EBM) and Stereolithography (SLA) technologies. EBM uses material powder and a heat source to melt and fuse the powders while SLA uses photosensitive resin and an ultraviolet light to cure the resin. A common limitation of both technologies is that powder/resin may remain inside the internal features which do not have access to outer surface of the part through the channels. The proposed method ensures the easy removal of excess powder/resin after fabrication. Performance of the method is compared with the SIMP method through test and analysis.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":"58 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81019838","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}
3D bioprinting has recently gained popularity due to its inherent capability of releasing cell-seeded and cell-laden biomaterials in a defined location to fabricate patient-specific scaffolds. Multi-nozzle extrusion-based 3D bio-printing allows the fabrication of various natural and synthetic biopolymers and the investigations of material to material and cell to material interactions, and eventually with a high percentage of cell viability and proliferation. Although natural hydrogels are demanding candidates for bio-printing because of their biocompatibility and high-water content, ensuring the scaffold’s fidelity with only natural hydrogel polymers is still challenging. Polycaprolactone (PCL) is a potential synthetic bioprinting material that can provide improved mechanical properties for fabricated scaffolds, especially bone and cartilage scaffolds. In this paper, application-oriented structural viability such as 3D printability, shape fidelity, and mechanical properties of the scaffolds fabricated by PCL and other natural hydrogel materials will be investigated. Scaffolds will be fabricated using various natural hybrid hydrogels such as Alginate-Carboxymethyl Cellulose; Alginate-Carboxymethyl Cellulose-TEMPO NFC, and PCL simultaneously using various infill densities, applied pressures, print speeds, and toolpath patterns. Shape fidelities of printed scaffolds will be analyzed. This research can help identify optimum natural-synthetic polymer combinations based on the materials interaction, external and internal geometries, and mechanical properties for large-scale multi-material bio fabrication.
生物3D打印由于其在特定位置释放细胞种子和细胞负载生物材料以制造患者特异性支架的固有能力，最近获得了普及。基于多喷嘴挤出的3D生物打印允许制造各种天然和合成生物聚合物，以及材料与材料和细胞与材料相互作用的研究，最终具有高比例的细胞活力和增殖。尽管天然水凝胶因其生物相容性和高含水量而成为生物打印的候选材料，但仅用天然水凝胶聚合物确保支架的保真度仍然具有挑战性。聚己内酯(PCL)是一种有潜力的合成生物打印材料，它可以为制备支架，特别是骨和软骨支架提供更好的力学性能。本文将研究PCL和其他天然水凝胶材料制备的支架的3D打印性、形状保真度和力学性能等面向应用的结构可行性。支架将使用各种天然混合水凝胶，如海藻酸盐-羧甲基纤维素;海藻酸盐-羧甲基纤维素- tempo NFC和PCL同时使用不同的填充密度、应用压力、打印速度和刀具轨迹模式。将分析打印支架的形状保真度。这项研究可以帮助确定基于材料相互作用、外部和内部几何形状以及大规模多材料生物制造的机械性能的最佳天然合成聚合物组合。
{"title":"3D Co-Printability of PCL and Hybrid Hydrogels","authors":"Connor Quigley, Md. Ahasan Habib","doi":"10.1115/msec2022-85685","DOIUrl":"https://doi.org/10.1115/msec2022-85685","url":null,"abstract":"\u0000 3D bioprinting has recently gained popularity due to its inherent capability of releasing cell-seeded and cell-laden biomaterials in a defined location to fabricate patient-specific scaffolds. Multi-nozzle extrusion-based 3D bio-printing allows the fabrication of various natural and synthetic biopolymers and the investigations of material to material and cell to material interactions, and eventually with a high percentage of cell viability and proliferation. Although natural hydrogels are demanding candidates for bio-printing because of their biocompatibility and high-water content, ensuring the scaffold’s fidelity with only natural hydrogel polymers is still challenging. Polycaprolactone (PCL) is a potential synthetic bioprinting material that can provide improved mechanical properties for fabricated scaffolds, especially bone and cartilage scaffolds. In this paper, application-oriented structural viability such as 3D printability, shape fidelity, and mechanical properties of the scaffolds fabricated by PCL and other natural hydrogel materials will be investigated. Scaffolds will be fabricated using various natural hybrid hydrogels such as Alginate-Carboxymethyl Cellulose; Alginate-Carboxymethyl Cellulose-TEMPO NFC, and PCL simultaneously using various infill densities, applied pressures, print speeds, and toolpath patterns. Shape fidelities of printed scaffolds will be analyzed. This research can help identify optimum natural-synthetic polymer combinations based on the materials interaction, external and internal geometries, and mechanical properties for large-scale multi-material bio fabrication.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":"109 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81203515","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}
High strength and lightweight continuous carbon fiber reinforced composites are desirable structural materials for applications in various industries including aerospace, automotive, and defense. Additive manufacturing (AM) of such important materials may provide multiple benefits including reduced cost, improved manufacturing efficiency, and the ability to fabricate complex structures not possible with traditional methods. Despite these benefits, a significant challenge with AM of continuous carbon fiber composites is poor impregnation of the fiber bundle with matrix material. When there is a lack of matrix material, voids develop within the fiber bundle and reduce mechanical properties of the composite including strength and stiffness. To minimize void formation, low speed manufacturing is typically necessary to facilitate impregnation. In this work, it was shown that fiber bundle impregnation can be significantly improved by applying thin, nanoporous coatings to the continuous fiber bundle. Using an electrophoretic deposition process, the coating microstructure, including thickness and nano pore size, was easily controlled through effective tuning of process parameters. Ultimately, individually coated carbon fibers were obtained and provided improvements in fiber bundle impregnation without sacrificing the flexibility of the fiber bundle. A highly absorbent yet flexible fiber bundle was desirable for 3D printing applications and would facilitate fabrication of complex geometries. With such tailored nanoporous coatings, fifteen-fold improvement in resin absorption time due was observed due to improved wicking by the nanoporous structure. Such improvements in absorption characteristics have a great potential for drop on demand or other resin-based 3D printing techniques. Furthermore, mechanical characterization demonstrated the potential of nanoporous coatings for additive manufacturing of high performance carbon fiber reinforced composites.
{"title":"Nanoporous Carbon Nanotube Coating for 3D Printing of High-Performance Continuous Fiber Reinforced Polymer Composites","authors":"J. M. Pappas, Xiangyang Dong","doi":"10.1115/msec2022-85758","DOIUrl":"https://doi.org/10.1115/msec2022-85758","url":null,"abstract":"\u0000 High strength and lightweight continuous carbon fiber reinforced composites are desirable structural materials for applications in various industries including aerospace, automotive, and defense. Additive manufacturing (AM) of such important materials may provide multiple benefits including reduced cost, improved manufacturing efficiency, and the ability to fabricate complex structures not possible with traditional methods. Despite these benefits, a significant challenge with AM of continuous carbon fiber composites is poor impregnation of the fiber bundle with matrix material. When there is a lack of matrix material, voids develop within the fiber bundle and reduce mechanical properties of the composite including strength and stiffness. To minimize void formation, low speed manufacturing is typically necessary to facilitate impregnation. In this work, it was shown that fiber bundle impregnation can be significantly improved by applying thin, nanoporous coatings to the continuous fiber bundle. Using an electrophoretic deposition process, the coating microstructure, including thickness and nano pore size, was easily controlled through effective tuning of process parameters. Ultimately, individually coated carbon fibers were obtained and provided improvements in fiber bundle impregnation without sacrificing the flexibility of the fiber bundle. A highly absorbent yet flexible fiber bundle was desirable for 3D printing applications and would facilitate fabrication of complex geometries. With such tailored nanoporous coatings, fifteen-fold improvement in resin absorption time due was observed due to improved wicking by the nanoporous structure. Such improvements in absorption characteristics have a great potential for drop on demand or other resin-based 3D printing techniques. Furthermore, mechanical characterization demonstrated the potential of nanoporous coatings for additive manufacturing of high performance carbon fiber reinforced composites.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":"23 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83731018","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}
Connor Ferris, Dilan Ratnayake, Alexander Curry, Danming Wei, Erin Gerber, T. Druffel, K. Walsh
Aerosol Jet Printing is a novel micron-scale printing technology capable of handling a variety of materials due to a large print material viscosity range and high substrate standoff distance of 3–5 mm. To finalize the properties of printed materials, a form of post-processing is often required. A current widely applicable post-processing technique exists in traditional oven curing. However, oven curing greatly restricts the viable substrates as well as curing time. Intense Pulsed Light (IPL) offers the chance to greatly expand this substrate variety and decrease curing time. However, limited models currently exist to relate the finished material properties to the unique settings of current IPL technology. In this paper, an experiment is developed through a General Full Factorial Design of Experiments (DOE) model to characterize conductivity of Ag ink using IPL as a post processing technique. This is conducted through Novacentrix Ag ink (JSA426) by 3 × 3 mm Van der Pauw sensor pads cured using IPL. Sample pads were generated in triplicate over a range of Energy Levels, Counts and Durations for IPL and the resulting conductivity measured. The collected conductivity data was then analyzed using ANOVA to determine the significant interactions. From this, a regression model is developed to predict the conductivity for any Energy-Count-Duration value. The methods employed are applicable to any post-processing technique, and further optimization of the model is proposed for future work.
气溶胶喷射印刷是一种新型的微米级印刷技术，由于印刷材料粘度范围大，基材距离高，可达3-5毫米，因此能够处理各种材料。为了最终确定印刷材料的特性，通常需要一种形式的后处理。传统烘箱腌制是目前应用广泛的后处理技术。然而，烘箱固化极大地限制了可行的基材以及固化时间。强脉冲光(IPL)提供了机会，大大扩大这种基板的品种和减少固化时间。然而，目前存在的有限模型将成品材料属性与当前IPL技术的独特设置联系起来。本文通过实验的一般全析因设计(DOE)模型，利用IPL作为后处理技术来表征银油墨的电导率。这是通过Novacentrix Ag油墨(JSA426)通过3 × 3 mm的Van der Pauw传感器衬垫进行的，使用IPL固化。样品垫在IPL的能级，计数和持续时间范围内生成三份，并测量由此产生的电导率。然后使用方差分析分析收集的电导率数据，以确定显著的相互作用。由此，开发了一个回归模型来预测任何能量计数-持续时间值的电导率。所采用的方法适用于任何后处理技术，并为今后的工作提出了进一步优化模型的建议。
{"title":"Characterizing the Conductivity of Aerosol Jet Printed Silver Traces on Glass Using Intense Pulsed Light (IPL)","authors":"Connor Ferris, Dilan Ratnayake, Alexander Curry, Danming Wei, Erin Gerber, T. Druffel, K. Walsh","doi":"10.1115/msec2022-85649","DOIUrl":"https://doi.org/10.1115/msec2022-85649","url":null,"abstract":"\u0000 Aerosol Jet Printing is a novel micron-scale printing technology capable of handling a variety of materials due to a large print material viscosity range and high substrate standoff distance of 3–5 mm. To finalize the properties of printed materials, a form of post-processing is often required. A current widely applicable post-processing technique exists in traditional oven curing. However, oven curing greatly restricts the viable substrates as well as curing time. Intense Pulsed Light (IPL) offers the chance to greatly expand this substrate variety and decrease curing time. However, limited models currently exist to relate the finished material properties to the unique settings of current IPL technology. In this paper, an experiment is developed through a General Full Factorial Design of Experiments (DOE) model to characterize conductivity of Ag ink using IPL as a post processing technique. This is conducted through Novacentrix Ag ink (JSA426) by 3 × 3 mm Van der Pauw sensor pads cured using IPL. Sample pads were generated in triplicate over a range of Energy Levels, Counts and Durations for IPL and the resulting conductivity measured. The collected conductivity data was then analyzed using ANOVA to determine the significant interactions. From this, a regression model is developed to predict the conductivity for any Energy-Count-Duration value. The methods employed are applicable to any post-processing technique, and further optimization of the model is proposed for future work.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":"1947 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91210235","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}
Porosity is a major quality issue in additively manufactured (AM) materials due to improper selection of raw material or process parameters. While porosity is kept to a minimum for structural applications, parts with intentional (engineered) porosity find applications in prosthetics, sound dampeners & mufflers, catalytic converters, electrodes, heat exchangers, filters, etc. During post-processing of additive manufactured components using secondary machining to obtain required dimensional tolerance and/or surface quality, part porosity could lead to fluctuating cutting forces and reduced tool life. The machinability of the porous AM material is poor compared to the homogenous wrought material due to the intermittent cutting and anisotropy of AM materials. The cutting parameters for machining are generally optimized for continuous wrought material and are not applicable for porous AM material. Micromilling experiments were carried out on AM Ti6Al4V alloy with different porosity levels and cutting speed using a 1 mm diameter end mill. The progression of tool wear and associated mechanisms during micro-milling of additive manufactured Ti6Al4V samples with different porosity levels are experimentally investigated. Insights into tool-workpiece interaction during micro-machining are obtained in cases where pore size could be comparable to the cutting tool diameter. This research could lead to efficient hybrid additive-subtractive manufacturing technologies with improved tool life and reduced costs.
{"title":"Effect of Porosity on Tool Wear During Micromachining of Additive Manufactured Titanium Alloy","authors":"V. Varghese, Soham Mujumdar","doi":"10.1115/msec2022-80096","DOIUrl":"https://doi.org/10.1115/msec2022-80096","url":null,"abstract":"\u0000 Porosity is a major quality issue in additively manufactured (AM) materials due to improper selection of raw material or process parameters. While porosity is kept to a minimum for structural applications, parts with intentional (engineered) porosity find applications in prosthetics, sound dampeners & mufflers, catalytic converters, electrodes, heat exchangers, filters, etc. During post-processing of additive manufactured components using secondary machining to obtain required dimensional tolerance and/or surface quality, part porosity could lead to fluctuating cutting forces and reduced tool life. The machinability of the porous AM material is poor compared to the homogenous wrought material due to the intermittent cutting and anisotropy of AM materials. The cutting parameters for machining are generally optimized for continuous wrought material and are not applicable for porous AM material. Micromilling experiments were carried out on AM Ti6Al4V alloy with different porosity levels and cutting speed using a 1 mm diameter end mill. The progression of tool wear and associated mechanisms during micro-milling of additive manufactured Ti6Al4V samples with different porosity levels are experimentally investigated. Insights into tool-workpiece interaction during micro-machining are obtained in cases where pore size could be comparable to the cutting tool diameter. This research could lead to efficient hybrid additive-subtractive manufacturing technologies with improved tool life and reduced costs.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":"31 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86911894","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}
Direct energy deposition (DED) has been widely used for additive manufacturing of metallic components toward a variety of applications. Surface characteristics of DED-fabricated components play key roles in determining the property and performance. Besides the average surface roughness which has been extensively investigated in literature, surface skewness and kurtosis are critical for surface integrity, particularly its durability due to stress concentration points. In this work, surface skewness and kurtosis of DED-fabricated 316L stainless steel as affected by processing parameters are investigated. In particular, the surface quality is measured using a microscopic structured light scanning (SLS) system, which is a relatively fast, low-cost, high-efficiency dimensional inspection metrology as compared to other methods. The results demonstrated the correlations between the printing parameters (laser power and scanning speed) and the surface topography of DED printed parts. It is found that the skewness and kurtosis of the surface are more sensitive to the change in scanning speed within a relatively low laser power range. Skewness is positively correlated with the scanning speed, while kurtosis shows a negative correlation with the scanning speed. Given a high scanning speed, Kurtosis and Skewness are more sensitive to the changes of scanning speed. Understanding the relationship between DED processing parameters and areal surface characteristics provides guidance and insights for process optimization and post-processing design towards additive manufacturing of high-performance metallic components.
{"title":"Real-Time Structured Light Scanning Characterization of Surface Topography of Direct Energy Deposited 316L Stainless Steel","authors":"Weijun Shen, Xing Zhang, Y. Liao, Beiwen Li","doi":"10.1115/msec2022-85783","DOIUrl":"https://doi.org/10.1115/msec2022-85783","url":null,"abstract":"\u0000 Direct energy deposition (DED) has been widely used for additive manufacturing of metallic components toward a variety of applications. Surface characteristics of DED-fabricated components play key roles in determining the property and performance. Besides the average surface roughness which has been extensively investigated in literature, surface skewness and kurtosis are critical for surface integrity, particularly its durability due to stress concentration points. In this work, surface skewness and kurtosis of DED-fabricated 316L stainless steel as affected by processing parameters are investigated. In particular, the surface quality is measured using a microscopic structured light scanning (SLS) system, which is a relatively fast, low-cost, high-efficiency dimensional inspection metrology as compared to other methods. The results demonstrated the correlations between the printing parameters (laser power and scanning speed) and the surface topography of DED printed parts. It is found that the skewness and kurtosis of the surface are more sensitive to the change in scanning speed within a relatively low laser power range. Skewness is positively correlated with the scanning speed, while kurtosis shows a negative correlation with the scanning speed. Given a high scanning speed, Kurtosis and Skewness are more sensitive to the changes of scanning speed. Understanding the relationship between DED processing parameters and areal surface characteristics provides guidance and insights for process optimization and post-processing design towards additive manufacturing of high-performance metallic components.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":"16 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86179941","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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