K. Alqosaibi, Mohammed Alemmrani, Ahmed Almalki, A. Duhduh, J. Coulter
A novel invention to advanced hot runner-based injection molding called Rheodrop technology is introduced. The technology allows control over the melt rheology inside the hot drops during/between injection molding cycles. The concept is to rotate the valve pin inside the hot drop to apply a controlled shear rate to the polymer melt. Doing so eliminated the incomplete filling defects associated with molding thin-walled parts and allowed processing at a lower melt temperature. The applied shear stress by Rheodrop technology was investigated utilizing ANSYS fluent software. The maximum shear stress that the polymer gets exposed to during the injection molding cycle was specified using Moldflow software. The results showed that the Rheodrop applies less shear stress than what the polymer gets exposed to during the injection molding cycle. Thus, utilizing Rheodrop does not cause additional damage to the polymer melt. Rheometric analyses were performed to investigate the polymer degradation for ABS. The reduction rate of viscosity was the same for samples that were injection molded conventionally and samples that were molded using Rheodrop technology.
{"title":"Numerical and Experimental Investigation of Rheodrop Technology","authors":"K. Alqosaibi, Mohammed Alemmrani, Ahmed Almalki, A. Duhduh, J. Coulter","doi":"10.1115/imece2022-94952","DOIUrl":"https://doi.org/10.1115/imece2022-94952","url":null,"abstract":"\u0000 A novel invention to advanced hot runner-based injection molding called Rheodrop technology is introduced. The technology allows control over the melt rheology inside the hot drops during/between injection molding cycles. The concept is to rotate the valve pin inside the hot drop to apply a controlled shear rate to the polymer melt. Doing so eliminated the incomplete filling defects associated with molding thin-walled parts and allowed processing at a lower melt temperature. The applied shear stress by Rheodrop technology was investigated utilizing ANSYS fluent software. The maximum shear stress that the polymer gets exposed to during the injection molding cycle was specified using Moldflow software. The results showed that the Rheodrop applies less shear stress than what the polymer gets exposed to during the injection molding cycle. Thus, utilizing Rheodrop does not cause additional damage to the polymer melt. Rheometric analyses were performed to investigate the polymer degradation for ABS. The reduction rate of viscosity was the same for samples that were injection molded conventionally and samples that were molded using Rheodrop technology.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"77 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":"124694298","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}
Timofey Dragun, Seth Mascaro, J. Blanchard, Vedang Chauhan
Industrial automation is a prominent process that has been around for many years and is continuing to evolve. An important aspect of automation is industrial robots. This paper focuses on an automated circuit board assembly process. Components of the assembly are described and identified, as well as a completed assembly is shown with 3D printed components. Important camera setup steps are documented and discussed in addition to the iRVision Geometric Pattern Matching (GPM) tool which is used to teach the camera how to find parts. The process was first developed using ROBOGUIDE simulation software, once validated the program was implemented on a physical FANUC LR Mate 200iD/4s robot. Trial runs were completed with both the physical robot and the ROBOGUIDE simulation, with the data being analyzed to determine the system performance. Comparing the physical robot to the ROBOGUIDE simulation has revealed that the physical robot can perform as well as the simulation in terms of part detection, but suffers when it comes to speed. Simulation in the virtual software is a quick and easy way to visualize and analyze the robotic work cell before investing money into implementing it in the real world.
工业自动化是一个突出的过程，已经存在了很多年，并且还在继续发展。自动化的一个重要方面是工业机器人。本文主要研究电路板的自动化装配过程。组件的组件被描述和识别，以及一个完整的组件显示与3D打印组件。除了iRVision几何模式匹配(GPM)工具外，还记录和讨论了重要的相机设置步骤，该工具用于教相机如何查找零件。该流程首先使用ROBOGUIDE仿真软件进行开发，一旦验证，该程序将在FANUC LR Mate 200iD/4s物理机器人上实施。通过物理机器人和ROBOGUIDE模拟完成了试运行，并对数据进行了分析以确定系统性能。将物理机器人与ROBOGUIDE仿真进行比较，发现物理机器人在零件检测方面可以表现得与仿真一样好，但在速度方面则受到影响。在投入资金在现实世界中实现机器人工作单元之前，虚拟软件中的仿真是一种快速简便的方法来可视化和分析机器人工作单元。
{"title":"Assembly Automation Using an Industrial Robot","authors":"Timofey Dragun, Seth Mascaro, J. Blanchard, Vedang Chauhan","doi":"10.1115/imece2022-94986","DOIUrl":"https://doi.org/10.1115/imece2022-94986","url":null,"abstract":"\u0000 Industrial automation is a prominent process that has been around for many years and is continuing to evolve. An important aspect of automation is industrial robots. This paper focuses on an automated circuit board assembly process. Components of the assembly are described and identified, as well as a completed assembly is shown with 3D printed components. Important camera setup steps are documented and discussed in addition to the iRVision Geometric Pattern Matching (GPM) tool which is used to teach the camera how to find parts. The process was first developed using ROBOGUIDE simulation software, once validated the program was implemented on a physical FANUC LR Mate 200iD/4s robot. Trial runs were completed with both the physical robot and the ROBOGUIDE simulation, with the data being analyzed to determine the system performance. Comparing the physical robot to the ROBOGUIDE simulation has revealed that the physical robot can perform as well as the simulation in terms of part detection, but suffers when it comes to speed. Simulation in the virtual software is a quick and easy way to visualize and analyze the robotic work cell before investing money into implementing it in the real world.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"24 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":"127014852","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}
A. Abubakar, K. Al-Athel, S. S. Akhtar, Abdulazeez Abubakar
Powder-based additive manufacturing (AM) technologies are commonly used to fabricate intricate-shape three-dimensional (3D) composite parts. The present study provides further insights into powder melt pool behavior and microstructure evolution during additive manufacturing of Hastelloy(HX)/WC composite using sequentially coupled multi-scale models. At the macro-scale, the heat transfer model is used to predict the temperature distribution and melts pool geometry formed during laser heating of multi-material powder bed. At the mesoscale, the phase-field and heat transfer models are coupled to predict the evolution of grains during the solidification of the powder melt. The computational results are reasonably comparable to that of the experiments. It is found that an ellipsoidal melt pool shape is formed around the irradiated zone. The temperature, thermal gradient and cooling rate changes across the melt pool dimensions. Due to epitaxial growth, columnar (elongated) grains are developed near the solid-liquid interface. In contrast, equiaxed grains are formed near the top regions of the melt pool due to higher cooling rates. The elongated grains become split into equiaxed ones due to the presence of the WC particles. The presence of the larger WC particles enhances the cooling rate; thereby, resulted in grain refinement. Reducing the WC particle size still results in grain refinement due to the pinning effect on grain boundaries; however, the grain size becomes affected by the WC particle size. The inclusion of foreign particles could be used to inhibit anisotropic behavior in 3D printed parts.
{"title":"A Multi-Scale Model for Microstructure Evolution During a Multi-Material Additive Manufacturing Process","authors":"A. Abubakar, K. Al-Athel, S. S. Akhtar, Abdulazeez Abubakar","doi":"10.1115/imece2022-92563","DOIUrl":"https://doi.org/10.1115/imece2022-92563","url":null,"abstract":"\u0000 Powder-based additive manufacturing (AM) technologies are commonly used to fabricate intricate-shape three-dimensional (3D) composite parts. The present study provides further insights into powder melt pool behavior and microstructure evolution during additive manufacturing of Hastelloy(HX)/WC composite using sequentially coupled multi-scale models. At the macro-scale, the heat transfer model is used to predict the temperature distribution and melts pool geometry formed during laser heating of multi-material powder bed. At the mesoscale, the phase-field and heat transfer models are coupled to predict the evolution of grains during the solidification of the powder melt. The computational results are reasonably comparable to that of the experiments. It is found that an ellipsoidal melt pool shape is formed around the irradiated zone. The temperature, thermal gradient and cooling rate changes across the melt pool dimensions. Due to epitaxial growth, columnar (elongated) grains are developed near the solid-liquid interface. In contrast, equiaxed grains are formed near the top regions of the melt pool due to higher cooling rates. The elongated grains become split into equiaxed ones due to the presence of the WC particles. The presence of the larger WC particles enhances the cooling rate; thereby, resulted in grain refinement. Reducing the WC particle size still results in grain refinement due to the pinning effect on grain boundaries; however, the grain size becomes affected by the WC particle size. The inclusion of foreign particles could be used to inhibit anisotropic behavior in 3D printed parts.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"147 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":"116193434","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}
Labeled training data are challenging to obtain in a manufacturing environment during production due to the time and cost constraints of the labelling process. Of the labeled training data that is collected, failure data comprises a small proportion or is non-existent in production datasets for condition monitoring. The small proportion can be related to failures occuring uxpectedly and parts are replaced quickly, meaning the failure state is rare and makes up a small portion of the run life and number of samples collected. The lack of labeled data and failure data leads to challenges in creating effective predictive systems, such as Digital Twins, to accurately determine equipment health state and remaining useful life. This work investigates training predictive algorithms using an augmented failure data set derived from laboratory systems with knowledge of real-world failures. Data are collected under different failure progressions and operating conditions to create variability for the variety of different production applications to apply these data augmentation methodologies. These same data are transformed by adding the variability measured through purposefully damaging the mechanical system to create the degraded and failed state data. This variability is extracted using a spectral augmentation technique on the surrogate system’s failure data under an artificial fatigue case. The fatigue case is created by incrementally damaging the bearing raceway and measuring the damaged surface area with respect to the total bearing raceway. The measured difference between these pre- and post-lab damage states is used as the damage state data set transformation function. The augmented and “true” data are then compared using class probability analysis and diagnosing particular failure instances. For future research, relatability analysis will be investigated to see how the effects change between bearings of different sizes.
{"title":"Data Augmentation Using Spectral Failure Deltas to Diagnose Bearing Failure","authors":"Ethan Wescoat, Matthew Krugh, L. Mears","doi":"10.1115/imece2022-93869","DOIUrl":"https://doi.org/10.1115/imece2022-93869","url":null,"abstract":"\u0000 Labeled training data are challenging to obtain in a manufacturing environment during production due to the time and cost constraints of the labelling process. Of the labeled training data that is collected, failure data comprises a small proportion or is non-existent in production datasets for condition monitoring. The small proportion can be related to failures occuring uxpectedly and parts are replaced quickly, meaning the failure state is rare and makes up a small portion of the run life and number of samples collected. The lack of labeled data and failure data leads to challenges in creating effective predictive systems, such as Digital Twins, to accurately determine equipment health state and remaining useful life. This work investigates training predictive algorithms using an augmented failure data set derived from laboratory systems with knowledge of real-world failures. Data are collected under different failure progressions and operating conditions to create variability for the variety of different production applications to apply these data augmentation methodologies. These same data are transformed by adding the variability measured through purposefully damaging the mechanical system to create the degraded and failed state data. This variability is extracted using a spectral augmentation technique on the surrogate system’s failure data under an artificial fatigue case. The fatigue case is created by incrementally damaging the bearing raceway and measuring the damaged surface area with respect to the total bearing raceway. The measured difference between these pre- and post-lab damage states is used as the damage state data set transformation function. The augmented and “true” data are then compared using class probability analysis and diagnosing particular failure instances. For future research, relatability analysis will be investigated to see how the effects change between bearings of different sizes.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"2 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":"130823280","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 initiatives on carbon capture utilization, use of CO2 in the manufacture of foamed polymers is valuable. The low solubility and strong temperature/pressure correlation to utilization remains a limit. Here we explore two aspects of green manufacturing. Use of a biopolymer and CO2 to foam it. Microcellular foams were produced from amorphous polylactic acid (PLA) with 12% d-lactide content using the batch foaming method. The batch method produces foams that are affected by cell nucleation, growth and solidification. In the thermal soak method, CO2 was introduced into PLA above its Tg, depressurized resulting in solidification, followed by soaking in a hot water bath for trapped CO2 to be released. In a second method, CO2 injected above the Tg was held at a temperature above ambient to encourage cell growth followed by a quench. The results showed that foams made through the decompression technique at foaming temperature of 55 °C were rigid in nature and had a better mix of cellular architecture due to their well-defined bimodal cellular structure compared to the foams made at foaming temperature of 75° C. Excellent mechanical and good sound absorption properties were attributed to the bimodal distr. Thermal conductivity values of (0.031–0.063) W/mK obtained for the PLA foams made using the thermal soak and decompression techniques was equivalent to that of petroleum based extruded polystyrene (EPS) and expanded polystyrene (XPS) foams ∼ (0.03–0.06) W/mK valuable for building insulation.
{"title":"Compostable, Full Biobased Foams Using Environmentally Benign Manufacturing","authors":"K. Oluwabunmi, N. D'Souza, Weihuan Zhao","doi":"10.1115/imece2022-95956","DOIUrl":"https://doi.org/10.1115/imece2022-95956","url":null,"abstract":"\u0000 With initiatives on carbon capture utilization, use of CO2 in the manufacture of foamed polymers is valuable. The low solubility and strong temperature/pressure correlation to utilization remains a limit. Here we explore two aspects of green manufacturing. Use of a biopolymer and CO2 to foam it. Microcellular foams were produced from amorphous polylactic acid (PLA) with 12% d-lactide content using the batch foaming method. The batch method produces foams that are affected by cell nucleation, growth and solidification. In the thermal soak method, CO2 was introduced into PLA above its Tg, depressurized resulting in solidification, followed by soaking in a hot water bath for trapped CO2 to be released. In a second method, CO2 injected above the Tg was held at a temperature above ambient to encourage cell growth followed by a quench. The results showed that foams made through the decompression technique at foaming temperature of 55 °C were rigid in nature and had a better mix of cellular architecture due to their well-defined bimodal cellular structure compared to the foams made at foaming temperature of 75° C. Excellent mechanical and good sound absorption properties were attributed to the bimodal distr. Thermal conductivity values of (0.031–0.063) W/mK obtained for the PLA foams made using the thermal soak and decompression techniques was equivalent to that of petroleum based extruded polystyrene (EPS) and expanded polystyrene (XPS) foams ∼ (0.03–0.06) W/mK valuable for building insulation.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"10 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":"122134997","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}
Mobile robots are being widely used in smart manufacturing, and efficient task assignment and path planning for these robots is an area of high interest. In previous studies, task assignment and path planning are usually solved as separate problems, which can result in optimal solutions in their respective fields, but not necessarily optimal as an integrated problem. Meanwhile, precedence constraints exist between sequential processing operations and material delivery tasks in the manufacturing environment. Thus, those planning methods developed for warehousing and logistics may not simply apply to the environment of smart factories. In this paper, we propose an integrated task and path planning approach based on Looking-backward Search Strategy (LSS) and Regret-based Search Strategy (RSS). In the stage of task assignment, the real paths for mobile robots are identified based on the Cooperative A* (CA*) algorithm and the time and energy consumed by mobile robots and machining centers are calculated. Then a greedy strategy working with LSS or RSS is used to search reasonable task assignments in time-series, which can generate a joint optimal solution for both task assignment and path planning. We verify the validity of the proposed approach in a simulated smart factory and the results show that our approach can improve the operation efficiency of the smart factory and save the time and energy consumption effectively.
{"title":"An Integrated Task and Path Planning Approach for Mobile Robots in Smart Factory","authors":"Shuo Liu, Bohan Feng, Dan Yu, Youyi Bi","doi":"10.1115/imece2022-95364","DOIUrl":"https://doi.org/10.1115/imece2022-95364","url":null,"abstract":"\u0000 Mobile robots are being widely used in smart manufacturing, and efficient task assignment and path planning for these robots is an area of high interest. In previous studies, task assignment and path planning are usually solved as separate problems, which can result in optimal solutions in their respective fields, but not necessarily optimal as an integrated problem. Meanwhile, precedence constraints exist between sequential processing operations and material delivery tasks in the manufacturing environment. Thus, those planning methods developed for warehousing and logistics may not simply apply to the environment of smart factories. In this paper, we propose an integrated task and path planning approach based on Looking-backward Search Strategy (LSS) and Regret-based Search Strategy (RSS). In the stage of task assignment, the real paths for mobile robots are identified based on the Cooperative A* (CA*) algorithm and the time and energy consumed by mobile robots and machining centers are calculated. Then a greedy strategy working with LSS or RSS is used to search reasonable task assignments in time-series, which can generate a joint optimal solution for both task assignment and path planning. We verify the validity of the proposed approach in a simulated smart factory and the results show that our approach can improve the operation efficiency of the smart factory and save the time and energy consumption effectively.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"24 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":"124991012","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}
Composite coatings with tailored properties can be effectively deposited with the cold spray process via careful control of deposition parameters. To avoid repetitive experiments, numerical models are commonly used to optimize the cold spray deposition process parameters. The present study proposes using a physics-based hybrid computational approach to model the cold spray deposition of Ni-Ti/Al2O3 composite coating used for wear applications. The method involves using point cloud (for the impacting particles) and finite elements (for the deformed splats structures and substrate) to simulate dissimilar particles impact and interactions, plastic deformation, and temperature rise. The approach is computationally efficient and adequately captures the thermo-mechanical deformation resulting from the interactions among dissimilar particles. The simulations are carried out for various combinations of material types, particles sizes and shapes, and impacting velocities. The results from the simulations are analyzed and validated by comparing them with that of previous works. The plastic deformation and temperature rise within the mating bodies increase with increasing particles’ kinetic energies. The Ni-Ti-Al2O3 powder particles lead to higher plastic deformation, temperature rise, and inter-particle bonding due to the presence of the hard Al2O3 particles. The temperature does not rise above melting; however, recrystallization of coating microstructure becomes possible even at a low deposition rate.
{"title":"A Physics-Based Computational Model for the Cold Spray Deposition of Composite Coatings","authors":"A. Abubakar, A. Arif, S. S. Akhtar, K. Al-Athel","doi":"10.1115/imece2022-92144","DOIUrl":"https://doi.org/10.1115/imece2022-92144","url":null,"abstract":"\u0000 Composite coatings with tailored properties can be effectively deposited with the cold spray process via careful control of deposition parameters. To avoid repetitive experiments, numerical models are commonly used to optimize the cold spray deposition process parameters. The present study proposes using a physics-based hybrid computational approach to model the cold spray deposition of Ni-Ti/Al2O3 composite coating used for wear applications. The method involves using point cloud (for the impacting particles) and finite elements (for the deformed splats structures and substrate) to simulate dissimilar particles impact and interactions, plastic deformation, and temperature rise. The approach is computationally efficient and adequately captures the thermo-mechanical deformation resulting from the interactions among dissimilar particles. The simulations are carried out for various combinations of material types, particles sizes and shapes, and impacting velocities. The results from the simulations are analyzed and validated by comparing them with that of previous works. The plastic deformation and temperature rise within the mating bodies increase with increasing particles’ kinetic energies. The Ni-Ti-Al2O3 powder particles lead to higher plastic deformation, temperature rise, and inter-particle bonding due to the presence of the hard Al2O3 particles. The temperature does not rise above melting; however, recrystallization of coating microstructure becomes possible even at a low deposition rate.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"20 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":"121895263","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}
Alok Yadav, A. Sachdeva, Rajeev Agrawal, R. K. Garg
Manufacturing industries across the globe are now adopting additive manufacturing (AM) practices over the traditional manufacturing process due to less waste generation and other economic and emissions benefits. Additive manufacturing can also be considered a key enabling technology for the high technology plan. However, the practices related to additive manufacturing in developing and developed economies are limited due to knowledge and technological advancements. Environmental impact assessment is an emerging research area highlighted in the last few years. At this point, research and industry attention is focused on determining where AM can replace or create new manufacturing systems. This study compares the environmental impact assessment of traditional and additive manufacturing processes by considering a case of pattern making. This paper also investigates how additive manufacturing technologies contribute to creating a sustainable environment in the manufacturing industry. A real-time case study is performed in SMEs of India, showing that additive manufacturing processes help lower the environmental impacts. The present study also highlighted the opportunities for additive manufacturing in sustainability. The gate-to-gate analysis is performed, and impact assessment is done by GABI software version 9 on Windows 10 operating system. In this report, a case study has been done to compare the traditional IC and AM processes using Aluminum alloy (Al-Si-Cu) in terms of environmental Sustainability. Results show that 28.77% reduction in GWP, 74.04% reduction in emission to Air, 36.30% reduction in AP and 45.62% reduction in HTP by using AM process. Overall, AM process is an environmentally sustainable process. This study would help researchers and the manufacturing industry determine the emissions associated with pattern making using the conventional IC process under Indian climatic conditions. It assists manufacturing industries in choosing the best available IC alternative regarding reduced environmental emissions.
{"title":"Environmental Sustainability of Additive Manufacturing: A Case Study of Indian Manufacturing Industry","authors":"Alok Yadav, A. Sachdeva, Rajeev Agrawal, R. K. Garg","doi":"10.1115/imece2022-95349","DOIUrl":"https://doi.org/10.1115/imece2022-95349","url":null,"abstract":"\u0000 Manufacturing industries across the globe are now adopting additive manufacturing (AM) practices over the traditional manufacturing process due to less waste generation and other economic and emissions benefits. Additive manufacturing can also be considered a key enabling technology for the high technology plan. However, the practices related to additive manufacturing in developing and developed economies are limited due to knowledge and technological advancements. Environmental impact assessment is an emerging research area highlighted in the last few years. At this point, research and industry attention is focused on determining where AM can replace or create new manufacturing systems. This study compares the environmental impact assessment of traditional and additive manufacturing processes by considering a case of pattern making. This paper also investigates how additive manufacturing technologies contribute to creating a sustainable environment in the manufacturing industry. A real-time case study is performed in SMEs of India, showing that additive manufacturing processes help lower the environmental impacts.\u0000 The present study also highlighted the opportunities for additive manufacturing in sustainability. The gate-to-gate analysis is performed, and impact assessment is done by GABI software version 9 on Windows 10 operating system. In this report, a case study has been done to compare the traditional IC and AM processes using Aluminum alloy (Al-Si-Cu) in terms of environmental Sustainability. Results show that 28.77% reduction in GWP, 74.04% reduction in emission to Air, 36.30% reduction in AP and 45.62% reduction in HTP by using AM process. Overall, AM process is an environmentally sustainable process. This study would help researchers and the manufacturing industry determine the emissions associated with pattern making using the conventional IC process under Indian climatic conditions. It assists manufacturing industries in choosing the best available IC alternative regarding reduced environmental emissions.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"16 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":"125083824","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}
The monitoring and diagnosis of dimensional deviation is an important means for the continuous improvement of assembly capacity in manufacturing systems. As optical scanning measurements become more common, statistical models based on 3D point cloud data have gained widespread attention. This paper introduces a general tensor regression method that builds a linear regression model between input and output. First, voxel technology is used to transform the 3D point cloud with deviation information into tensor form. Secondly, a Tensor-on-Scalar regression model is established for quality monitoring, and a Tensor-on-Tensor regression model is established for fault diagnosis. Then, tensor decomposition is used to reduce the number of parameters to be estimated in the regression model. Finally, the learning of parameter values is achieved by combining alternating least squares and gradient descent or coordinate descent. A case study of the door inner panel assembly process evaluates the predictive performance of a tensor regression model. The results show that the proposed method outperforms most existing methods in terms of prediction accuracy. Hence, the tensor regression model can achieve high-performance quality monitoring and fault diagnosis.
{"title":"Monitoring and Diagnosis of Dimensional Deviation in Assembly Process Using Tensor Regression","authors":"Rui Sun, Sun Jin, Yinhua Liu","doi":"10.1115/imece2022-95014","DOIUrl":"https://doi.org/10.1115/imece2022-95014","url":null,"abstract":"The monitoring and diagnosis of dimensional deviation is an important means for the continuous improvement of assembly capacity in manufacturing systems. As optical scanning measurements become more common, statistical models based on 3D point cloud data have gained widespread attention. This paper introduces a general tensor regression method that builds a linear regression model between input and output. First, voxel technology is used to transform the 3D point cloud with deviation information into tensor form. Secondly, a Tensor-on-Scalar regression model is established for quality monitoring, and a Tensor-on-Tensor regression model is established for fault diagnosis. Then, tensor decomposition is used to reduce the number of parameters to be estimated in the regression model. Finally, the learning of parameter values is achieved by combining alternating least squares and gradient descent or coordinate descent. A case study of the door inner panel assembly process evaluates the predictive performance of a tensor regression model. The results show that the proposed method outperforms most existing methods in terms of prediction accuracy. Hence, the tensor regression model can achieve high-performance quality monitoring and fault diagnosis.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"9 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":"115416580","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}
Min-Soo Kim, Seog-Chan Oh, Eun Hyo Chang, James W. Wells, J. Arinez, Y. Jang
The increasing demand for electric vehicles and the emergence of autonomous transport technologies within production like autonomous mobile robot or self-driving rolling chassis have raised the possibility of developing conveyor-less matrix assembly system. The conveyor-less matrix assembly system is characterized by high adaptability to demand changes with low-cost investments and asynchronous operations allowing high routing and process flexibilities where the sequence of assembly operations is only limited by the product-specific precedence orders. With high flexibility potentials, however, the system needs to face high complexity issues in modeling and control. The high complexity may reduce the system performance and thus, the performance evaluation is a key component in modeling and control of conveyor-less matrix systems. To study the evaluation methods for the conveyor-less matrix assembly, this paper introduces two models, a mixed-integer linear programming model as exact method and a simulation model as heuristic method, and then illustrates how two models are different but can work collaboratively in a hypothetical example drawn from automotive assembly trim area. Finally, this paper intends to provide insights on the business value calculation of conveyor-less matrix assembly system, for practitioners who are interested in building conveyor-less matrix assembly system in the future.
{"title":"Performance Evaluation of Conveyor-Less Matrix Assembly System Using Simulation and Mathematical Models","authors":"Min-Soo Kim, Seog-Chan Oh, Eun Hyo Chang, James W. Wells, J. Arinez, Y. Jang","doi":"10.1115/imece2022-94996","DOIUrl":"https://doi.org/10.1115/imece2022-94996","url":null,"abstract":"\u0000 The increasing demand for electric vehicles and the emergence of autonomous transport technologies within production like autonomous mobile robot or self-driving rolling chassis have raised the possibility of developing conveyor-less matrix assembly system. The conveyor-less matrix assembly system is characterized by high adaptability to demand changes with low-cost investments and asynchronous operations allowing high routing and process flexibilities where the sequence of assembly operations is only limited by the product-specific precedence orders. With high flexibility potentials, however, the system needs to face high complexity issues in modeling and control. The high complexity may reduce the system performance and thus, the performance evaluation is a key component in modeling and control of conveyor-less matrix systems. To study the evaluation methods for the conveyor-less matrix assembly, this paper introduces two models, a mixed-integer linear programming model as exact method and a simulation model as heuristic method, and then illustrates how two models are different but can work collaboratively in a hypothetical example drawn from automotive assembly trim area. Finally, this paper intends to provide insights on the business value calculation of conveyor-less matrix assembly system, for practitioners who are interested in building conveyor-less matrix assembly system in the future.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"132 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":"128524836","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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