Despite the transformative capability of laser powder bed fusion (LPBF) additive manufacturing to create components with intricate geometry, the large-scale adoption remains a barrier owing to the process complexity and significant build quality concerns. In-process melt pool imaging offers an unparalleled capability to tackle the problems by evaluating the impact of prominent process parameters (e.g., laser power, laser velocity, and hatch spacing) on build quality. However, the current investigations overlook the effect of other influential factors such as scan strategies. Because of the multitude and high-dimensionality in melt pool images, the extraction of manual features to characterize and intertwine diverse scan strategies (e.g., orthogonal serpentine, pre-scanned boarder, and clockwise spiral) is cumbersome or inefficient. While end-to-end deep neural networks realize automated feature extraction from melt pool images, they are limited in providing meaningful signatures for the characterization of various scan strategies. This paper presents a systematic image-guided analysis based on variational autoencoder (VAE) that enables the semantic representation of image data on low-dimensional latent space to characterize similarities between scan strategies. Further, hyperdimensional computing as a cognitive solution is integrated to differentiate various scan strategies according to latent features. Experimental results on the real-world case study based on 30,000 in-situ melt pool images show that VAE is significantly effective in interpretable characterization associated with 12 different scan strategies. In addition, the cognitive model differentiates scan strategies using the latent representation with an accuracy of 81.20 ± 0.8%.
{"title":"Latent Representation and Characterization of Scanning Strategy on Laser Powder Bed Fusion Additive Manufacturing","authors":"Farhad Imani, Ruimin Chen","doi":"10.1115/imece2022-96019","DOIUrl":"https://doi.org/10.1115/imece2022-96019","url":null,"abstract":"\u0000 Despite the transformative capability of laser powder bed fusion (LPBF) additive manufacturing to create components with intricate geometry, the large-scale adoption remains a barrier owing to the process complexity and significant build quality concerns. In-process melt pool imaging offers an unparalleled capability to tackle the problems by evaluating the impact of prominent process parameters (e.g., laser power, laser velocity, and hatch spacing) on build quality. However, the current investigations overlook the effect of other influential factors such as scan strategies. Because of the multitude and high-dimensionality in melt pool images, the extraction of manual features to characterize and intertwine diverse scan strategies (e.g., orthogonal serpentine, pre-scanned boarder, and clockwise spiral) is cumbersome or inefficient. While end-to-end deep neural networks realize automated feature extraction from melt pool images, they are limited in providing meaningful signatures for the characterization of various scan strategies. This paper presents a systematic image-guided analysis based on variational autoencoder (VAE) that enables the semantic representation of image data on low-dimensional latent space to characterize similarities between scan strategies. Further, hyperdimensional computing as a cognitive solution is integrated to differentiate various scan strategies according to latent features. Experimental results on the real-world case study based on 30,000 in-situ melt pool images show that VAE is significantly effective in interpretable characterization associated with 12 different scan strategies. In addition, the cognitive model differentiates scan strategies using the latent representation with an accuracy of 81.20 ± 0.8%.","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":"133453056","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}
Established tolerance analysis methods are capable of predicting the effects of geometrical part variations on the quality of products and hence virtually assuring their functionality. However, assumptions and simplifications are often made, which can lead to decisive uncertainties. To omit a significant effect of these uncertainties on the overall model and on the obtained results, both a virtual assessment of the model as well as an experimental validation are necessary. The current state of the art still lacks suitable methods and metrics to reliably evaluate the results of tolerance analyses. In addition, an approach is needed to investigate and evaluate the effects of uncertainties within the analysis model on the overall model. The aim of this contribution is therefore to derive statements about the suitability and significance of methods and metrics of verification and validation for evaluating simulation models and their feasibility in the context of tolerance analysis. First, general methods and metrics for the evaluation of simulation results are presented. Subsequently, the most promising ones are customized in an unifying approach. The statistical tolerance analysis of a 3-D-printed non-assembly mechanism in motion serves as an explanatory example for highlighting the procedure and the current challenges and constraints. Finally, the findings are critically discussed and as a result, statements about the further need for action are presented.
{"title":"A Hierarchical Approach for the Verification and Validation of Tolerance Analysis Models","authors":"Paul Schaechtl, B. Schleich, S. Wartzack","doi":"10.1115/imece2022-91890","DOIUrl":"https://doi.org/10.1115/imece2022-91890","url":null,"abstract":"\u0000 Established tolerance analysis methods are capable of predicting the effects of geometrical part variations on the quality of products and hence virtually assuring their functionality. However, assumptions and simplifications are often made, which can lead to decisive uncertainties. To omit a significant effect of these uncertainties on the overall model and on the obtained results, both a virtual assessment of the model as well as an experimental validation are necessary. The current state of the art still lacks suitable methods and metrics to reliably evaluate the results of tolerance analyses. In addition, an approach is needed to investigate and evaluate the effects of uncertainties within the analysis model on the overall model. The aim of this contribution is therefore to derive statements about the suitability and significance of methods and metrics of verification and validation for evaluating simulation models and their feasibility in the context of tolerance analysis. First, general methods and metrics for the evaluation of simulation results are presented. Subsequently, the most promising ones are customized in an unifying approach. The statistical tolerance analysis of a 3-D-printed non-assembly mechanism in motion serves as an explanatory example for highlighting the procedure and the current challenges and constraints. Finally, the findings are critically discussed and as a result, statements about the further need for action are presented.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"7 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":"131853129","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}
S. Pizzagalli, Yevhen Bondarenko, B. Baykara, A. Niidas, V. Kuts, Margus Kerm, T. Otto
Timber industry is one of the most relevant economic sectors in Estonia. Automatization of forestry management and harvesting processes optimization are realities also in this specific domain. As much as in other industrial fields adopting the Industry 4.0 paradigm and core technologies, forestry management, log harvesting and the wood processing industry make use of state-of-the-art sensors, Digital Twins and advanced interfaces for the operators. The latter include Extended Reality solutions and remote-control making use of immersive head mounted displays (HMD). This works presents an innovative system for hydraulic forestry crane teleoperation making use of HMD and wide-angle camera stream. The system hardware is installed locally while the software, integrated in Unity, supports the operator in using the crane’s native joysticks and controller for the log loading operations. Additional virtual user interface and controls are included in the immersive view and accessible through the same controls and joysticks.
{"title":"Forestry Crane Immersive User Interface for Control and Teleoperation","authors":"S. Pizzagalli, Yevhen Bondarenko, B. Baykara, A. Niidas, V. Kuts, Margus Kerm, T. Otto","doi":"10.1115/imece2022-94975","DOIUrl":"https://doi.org/10.1115/imece2022-94975","url":null,"abstract":"\u0000 Timber industry is one of the most relevant economic sectors in Estonia. Automatization of forestry management and harvesting processes optimization are realities also in this specific domain. As much as in other industrial fields adopting the Industry 4.0 paradigm and core technologies, forestry management, log harvesting and the wood processing industry make use of state-of-the-art sensors, Digital Twins and advanced interfaces for the operators. The latter include Extended Reality solutions and remote-control making use of immersive head mounted displays (HMD). This works presents an innovative system for hydraulic forestry crane teleoperation making use of HMD and wide-angle camera stream. The system hardware is installed locally while the software, integrated in Unity, supports the operator in using the crane’s native joysticks and controller for the log loading operations. Additional virtual user interface and controls are included in the immersive view and accessible through the same controls and joysticks.","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":"134351988","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}
S. Jegorov, A. Rassõlkin, V. Rjabtšikov, M. Ibrahim, V. Kuts
This paper introduces a novel concept of interconnecting components of Digital Twins using ROS2 and micro-ROS frameworks. Authors of the research argue that middleware implementation plays the most important role in the performance of Digital Twins and its robustness must be ensured for reliable real-time operation between components of Digital Twins. Propulsion Drive System Digital Twin is presented where a permanent magnet synchronous motor testbench is interconnected with a virtual counterpart based on the motor’s analytical model for calculation of the motor’s angular velocity and torque. The interface between the motor of the Propulsion Drive System and its virtual counterpart is implemented on a basis of a microcontroller running micro-ROS, with ROS2 acting as a fundamental middleware. The suggested method of connecting components of Digital Twins is tested through a round-trip time latency test. Results of the latency test indicate that the proposed concept is suitable for Digital Twin technologies in industrial applications. At the end of the paper, the authors discuss possible future developments and use cases of the suggested concept.
{"title":"Novel Digital Twin Concept for Industrial Application. Study Case: Propulsion Drive System","authors":"S. Jegorov, A. Rassõlkin, V. Rjabtšikov, M. Ibrahim, V. Kuts","doi":"10.1115/imece2022-97243","DOIUrl":"https://doi.org/10.1115/imece2022-97243","url":null,"abstract":"\u0000 This paper introduces a novel concept of interconnecting components of Digital Twins using ROS2 and micro-ROS frameworks. Authors of the research argue that middleware implementation plays the most important role in the performance of Digital Twins and its robustness must be ensured for reliable real-time operation between components of Digital Twins. Propulsion Drive System Digital Twin is presented where a permanent magnet synchronous motor testbench is interconnected with a virtual counterpart based on the motor’s analytical model for calculation of the motor’s angular velocity and torque. The interface between the motor of the Propulsion Drive System and its virtual counterpart is implemented on a basis of a microcontroller running micro-ROS, with ROS2 acting as a fundamental middleware. The suggested method of connecting components of Digital Twins is tested through a round-trip time latency test. Results of the latency test indicate that the proposed concept is suitable for Digital Twin technologies in industrial applications. At the end of the paper, the authors discuss possible future developments and use cases of the suggested concept.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"143 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":"128827287","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 practicable application of electron beam melted (EBM) titanium parts requires acceptable mechanical, fatigue, and tribological properties. The current literature is still lacking enough investigations on the tribological properties of EBM titanium. This paper presents the preliminary results and analysis of the dry sliding behavior of electron beam melted (EBM) Ti6Al4V in as-built and machined conditions. To understand the dry sliding behavior at different built orientations, rotary abrasion tests have been conducted on EBM Ti6Al4V specimens built at three built orientations, i.e., 3°, 45°, and 90°. EBM fabricated Ti6Al4V specimens were subjected to rotary abrasion against alumina particles up to 4000 cycles. The mass removal was recorded. The wear tracks generated on Ti6Al4V specimens were inspected through scanning electron microscopy, optical microscopy, and optical 3D profiler. The wear-induced microstructure and hardness variation have been investigated. Experimental results show that the dry sliding wear behavior of EBM Ti6Al4V is influenced by built orientation due to process-induced surface asperities and hardness. Machining significantly increases wear resistance depending on built orientation, and offsets wear anisotropy. The wear mechanism is discussed as well.
{"title":"Sliding Wear Behavior of Electron Beam Melted (EBM) Ti6Al4V","authors":"Mohammad Sayem Bin Abdullah, Ramulu Mamidala","doi":"10.1115/imece2022-94735","DOIUrl":"https://doi.org/10.1115/imece2022-94735","url":null,"abstract":"\u0000 The practicable application of electron beam melted (EBM) titanium parts requires acceptable mechanical, fatigue, and tribological properties. The current literature is still lacking enough investigations on the tribological properties of EBM titanium. This paper presents the preliminary results and analysis of the dry sliding behavior of electron beam melted (EBM) Ti6Al4V in as-built and machined conditions. To understand the dry sliding behavior at different built orientations, rotary abrasion tests have been conducted on EBM Ti6Al4V specimens built at three built orientations, i.e., 3°, 45°, and 90°. EBM fabricated Ti6Al4V specimens were subjected to rotary abrasion against alumina particles up to 4000 cycles. The mass removal was recorded. The wear tracks generated on Ti6Al4V specimens were inspected through scanning electron microscopy, optical microscopy, and optical 3D profiler. The wear-induced microstructure and hardness variation have been investigated. Experimental results show that the dry sliding wear behavior of EBM Ti6Al4V is influenced by built orientation due to process-induced surface asperities and hardness. Machining significantly increases wear resistance depending on built orientation, and offsets wear anisotropy. The wear mechanism is discussed as well.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"119 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":"133474352","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}
R. Shanmugam, Dhinakaran Veeman, Muthu Shanmugam Mannan, Gopika Kalaiselvan
In this work, alloy Ti-6Al-4V was fabricated using direct metal laser sintering (DMLS) approach and studied the effect of heat treatment (solution treatment 950 °C/2h-furnace cooling and aging 550 °C/6h-air cooling) on the oxidation and wear performance at elevated temperature. The microstructural investigation revealed that as-built alloy consists of a fine-grained martensitic needle shape structure with columnar grains. In the solution treatment aging (STA) treated alloy, the rod-shaped β with different lengths of a was observed. As-built and STA-treated alloy Ti-6Al-4V were subjected to a cyclic oxidation test at 650 °C for 50 h in air. The reaction products developed on the sample’s surface are evaluated by scanning electron microscope (SEM) and X-ray diffraction (XRD). A thick TiO2 layer was formed on the alloy surface, and some cracks were noticed due to thermal stress. The high-temperature wear test was carried out on the Ti-6Al-4V alloy at room temperature (30 °C), 200, and 400 °C using a reciprocating pin-on-disc tribometer in dry conditions. The abrasive wear mechanism was found at RT, whereas oxidation and the adhesive mechanism were noticed at 200 and 400 °C. Results exhibited that STA alloy had a higher wear resistance than that of as-built alloy.
{"title":"Effect of Heat Treatment on the Oxidation and High Temperature Wear Performance of Alloy Ti-6Al-4V Manufactured by Direct Metal Laser Sintering","authors":"R. Shanmugam, Dhinakaran Veeman, Muthu Shanmugam Mannan, Gopika Kalaiselvan","doi":"10.1115/imece2022-95392","DOIUrl":"https://doi.org/10.1115/imece2022-95392","url":null,"abstract":"\u0000 In this work, alloy Ti-6Al-4V was fabricated using direct metal laser sintering (DMLS) approach and studied the effect of heat treatment (solution treatment 950 °C/2h-furnace cooling and aging 550 °C/6h-air cooling) on the oxidation and wear performance at elevated temperature. The microstructural investigation revealed that as-built alloy consists of a fine-grained martensitic needle shape structure with columnar grains. In the solution treatment aging (STA) treated alloy, the rod-shaped β with different lengths of a was observed. As-built and STA-treated alloy Ti-6Al-4V were subjected to a cyclic oxidation test at 650 °C for 50 h in air. The reaction products developed on the sample’s surface are evaluated by scanning electron microscope (SEM) and X-ray diffraction (XRD). A thick TiO2 layer was formed on the alloy surface, and some cracks were noticed due to thermal stress. The high-temperature wear test was carried out on the Ti-6Al-4V alloy at room temperature (30 °C), 200, and 400 °C using a reciprocating pin-on-disc tribometer in dry conditions. The abrasive wear mechanism was found at RT, whereas oxidation and the adhesive mechanism were noticed at 200 and 400 °C. Results exhibited that STA alloy had a higher wear resistance than that of as-built alloy.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"4 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":"130993376","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, Michael Jones, Suyen Bueso Quan, Maria Gonzalez Bocanegra, Mohammad Taheri
Safety is the top priority for every transportation system. Although various aspects of transportation infrastructure’s safety have been studied, in-motion monitoring and detection of defect is still a big concern. Understanding the trend of anomalies, and how to monitor undesired conditions are of high interest in transportation. In this study, the technology of Distributed Acoustic Sensing (DAS) for in-motion rail condition monitoring is studied through experimental testing and simulation modeling. DAS uses fiber optic cables along the track to detect any anomaly indicator. DAS permit the measurement of a desired parameter as a function of length along the fiber. Despite any conventional Nondestructive Testing (NDT) technique where the coverage or scanning area of the sensors are very limited, DAS provides a full, fast and accurate coverage of all section under the test. The objective of this research is to provide an assessment of anomaly detection and monitoring techniques based on DAS for transportation investigation. It presents the experimental evaluations and numerical simulations on the current methodologies in DAS systems. DAS was used to evaluate the transportation traffic condition in a rural area by connecting an available underground dark fiber to the DAS interrogator and system as well as simulated traffic condition in smaller scale in a parking lot. COMSOL Multiphysics software was used to model the interaction of ambient vibration with the fiber optic. Results show that the condition of the transportation can be monitored and detected by DAS with an appropriate accuracy. DAS information can be used for traffic condition monitoring, object tracking and flaw detections in the transportation lines.
{"title":"Distributed Acoustic Sensing (DAS) for Intelligent In-Motion Transportation Condition Monitoring","authors":"H. Taheri, Michael Jones, Suyen Bueso Quan, Maria Gonzalez Bocanegra, Mohammad Taheri","doi":"10.1115/imece2022-95366","DOIUrl":"https://doi.org/10.1115/imece2022-95366","url":null,"abstract":"\u0000 Safety is the top priority for every transportation system. Although various aspects of transportation infrastructure’s safety have been studied, in-motion monitoring and detection of defect is still a big concern. Understanding the trend of anomalies, and how to monitor undesired conditions are of high interest in transportation. In this study, the technology of Distributed Acoustic Sensing (DAS) for in-motion rail condition monitoring is studied through experimental testing and simulation modeling. DAS uses fiber optic cables along the track to detect any anomaly indicator. DAS permit the measurement of a desired parameter as a function of length along the fiber. Despite any conventional Nondestructive Testing (NDT) technique where the coverage or scanning area of the sensors are very limited, DAS provides a full, fast and accurate coverage of all section under the test. The objective of this research is to provide an assessment of anomaly detection and monitoring techniques based on DAS for transportation investigation. It presents the experimental evaluations and numerical simulations on the current methodologies in DAS systems. DAS was used to evaluate the transportation traffic condition in a rural area by connecting an available underground dark fiber to the DAS interrogator and system as well as simulated traffic condition in smaller scale in a parking lot. COMSOL Multiphysics software was used to model the interaction of ambient vibration with the fiber optic. Results show that the condition of the transportation can be monitored and detected by DAS with an appropriate accuracy. DAS information can be used for traffic condition monitoring, object tracking and flaw detections in the transportation lines.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"2009 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":"131241078","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}
Job Lazarus Okello, A. F. El-Bab, M. Yoshino, H. El-Hofy, M. Hassan
High surface roughness hinders the flow of fluids in microchannels leading to low accuracy and poor-quality products. In this work, the adaptive neuro-fuzzy inference system (ANFIS) was used to examine surface roughness in CO2 laser fabrication of microchannels on polymethyl methacrylate (PMMA). The PMMA substrates were coated with a 500 nm layer of 99.95% pure aluminium. The inputs were speed (10, 15, and 20 mm/s), power (1.5, 3.0, and 4.5 W), and pulse rate (800, 900, and 1000 pules per inch) while the output was surface roughness. A 3-level full factorial design of experiments was used, and 27 experiments were conducted. Using the gaussian membership function (gaussmf), the ANFIS model was developed using the ANFIS toolbox in MATLAB R2022a. Analysis of variance was performed to examine the significance of the inputs. Power is the most significant followed by speed and pulse rate. The mean relative error (MRE), mean absolute error (MAE), and the correlation coefficient (R) were used to examine the accuracy and viability of the model. MRE, MAE, and R were found to be 0.257, 0.899, and 0.9957 (R2 = 0.9914) respectively. The root mean square error (RMSE) was 0.0022 and 3.6099 for the training data and checking data respectively. Hence, the developed model can predict the values of the average surface roughness with high accuracy.
{"title":"Modelling of Surface Roughness in CO2 Laser Ablation of Aluminium-Coated Polymethyl Methacrylate (PMMA) Using Adaptive Neuro-Fuzzy Inference System (ANFIS)","authors":"Job Lazarus Okello, A. F. El-Bab, M. Yoshino, H. El-Hofy, M. Hassan","doi":"10.1115/imece2022-92024","DOIUrl":"https://doi.org/10.1115/imece2022-92024","url":null,"abstract":"\u0000 High surface roughness hinders the flow of fluids in microchannels leading to low accuracy and poor-quality products. In this work, the adaptive neuro-fuzzy inference system (ANFIS) was used to examine surface roughness in CO2 laser fabrication of microchannels on polymethyl methacrylate (PMMA). The PMMA substrates were coated with a 500 nm layer of 99.95% pure aluminium. The inputs were speed (10, 15, and 20 mm/s), power (1.5, 3.0, and 4.5 W), and pulse rate (800, 900, and 1000 pules per inch) while the output was surface roughness. A 3-level full factorial design of experiments was used, and 27 experiments were conducted. Using the gaussian membership function (gaussmf), the ANFIS model was developed using the ANFIS toolbox in MATLAB R2022a. Analysis of variance was performed to examine the significance of the inputs. Power is the most significant followed by speed and pulse rate. The mean relative error (MRE), mean absolute error (MAE), and the correlation coefficient (R) were used to examine the accuracy and viability of the model. MRE, MAE, and R were found to be 0.257, 0.899, and 0.9957 (R2 = 0.9914) respectively. The root mean square error (RMSE) was 0.0022 and 3.6099 for the training data and checking data respectively. Hence, the developed model can predict the values of the average surface roughness with high accuracy.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"18 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":"115395901","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 threats of cyber-attacks against Cyber-manufacturing systems (CMS) pose production manager with a unique challenge. The timing, target, severity of their occurrence is all uncertain and yet decisions need to be made in real time to ensure the achievement of production goals under their advent. This paper proposes a systemic approach to estimate threat severity in three different dimensions, (i) disruption potential, (ii) total economic impact, and (iii) non-tangible losses. A model resilient testbed CMS is presented, which is a system with prevention, detection, redundancy, and recovery mechanisms implemented against cyber-attacks. We evaluate the potential threat by analyzing the state of production factors and the characteristics of the potential responses that the system has set in place. The severity of the attack cannot be defined in advance given that the level of disruption that can create is not an absolute value but rather dependent on the state of the system at it time of its occurrence. To address this uncertainty, we utilize an expected value equation in which we take the worst-case scenario and take actions to ensure the system remains resilient. Decisions are taken to minimize cost while ensuring the fulfillment of the production goals.
{"title":"Assessing Severity of Cyber-Attack Threats Against Cyber-Manufacturing Systems","authors":"Carlos Espinoza-Zelaya, Y. Moon","doi":"10.1115/imece2022-94493","DOIUrl":"https://doi.org/10.1115/imece2022-94493","url":null,"abstract":"\u0000 The threats of cyber-attacks against Cyber-manufacturing systems (CMS) pose production manager with a unique challenge. The timing, target, severity of their occurrence is all uncertain and yet decisions need to be made in real time to ensure the achievement of production goals under their advent. This paper proposes a systemic approach to estimate threat severity in three different dimensions, (i) disruption potential, (ii) total economic impact, and (iii) non-tangible losses.\u0000 A model resilient testbed CMS is presented, which is a system with prevention, detection, redundancy, and recovery mechanisms implemented against cyber-attacks. We evaluate the potential threat by analyzing the state of production factors and the characteristics of the potential responses that the system has set in place. The severity of the attack cannot be defined in advance given that the level of disruption that can create is not an absolute value but rather dependent on the state of the system at it time of its occurrence. To address this uncertainty, we utilize an expected value equation in which we take the worst-case scenario and take actions to ensure the system remains resilient. Decisions are taken to minimize cost while ensuring the fulfillment of the production goals.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"158 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":"124496611","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}
Matheus Cardoso, Rodrigo Lozan, G. Barbosa, David A. Guerra-Zubiaga, S. Shiki
Faced with the advances in automation related to the digital transformation of the industry, new products are developed, and the fabrication processes are becoming smarter day by day. However, modern manufacturing systems look for electricity savings, especially in machining operations. In this sense, power consumption has a big deal for industry costs, and it needs to be monitored to provide a more competitive business. So, to minimize this problem, digital manufacturing based on simulation tools has been used to find economic ways to optimize the manufacturing processes, providing a reduction of recurring costs. Thus, this research proposes the use of Tecnomatix Siemens PS (Process Simulate) software for process simulation of 2024 aluminum drilling to explore the analysis of energy consumption (EC) in a machining operation using a robot. Also, this proposal looks for a digital twin conception, comprising its variables and features to make possible a case study assisted by the Design of Experiments (DOE) method.
{"title":"Energy Consumption Evaluation on Robotic Drilling Process Using Digital Twin Technology","authors":"Matheus Cardoso, Rodrigo Lozan, G. Barbosa, David A. Guerra-Zubiaga, S. Shiki","doi":"10.1115/imece2022-95205","DOIUrl":"https://doi.org/10.1115/imece2022-95205","url":null,"abstract":"\u0000 Faced with the advances in automation related to the digital transformation of the industry, new products are developed, and the fabrication processes are becoming smarter day by day. However, modern manufacturing systems look for electricity savings, especially in machining operations. In this sense, power consumption has a big deal for industry costs, and it needs to be monitored to provide a more competitive business. So, to minimize this problem, digital manufacturing based on simulation tools has been used to find economic ways to optimize the manufacturing processes, providing a reduction of recurring costs. Thus, this research proposes the use of Tecnomatix Siemens PS (Process Simulate) software for process simulation of 2024 aluminum drilling to explore the analysis of energy consumption (EC) in a machining operation using a robot. Also, this proposal looks for a digital twin conception, comprising its variables and features to make possible a case study assisted by the Design of Experiments (DOE) method.","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":"123209113","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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