Pub Date : 2023-07-18DOI: 10.31803/tg-20220920172008
M. Katinić, Josip Kolar, P. Konjatić, M. Bošnjaković
In this paper, the dynamic behavior of a rotor kit with two identical disks located between the plain bearings was analyzed. Modal and harmonic analysis of this rotor kit configuration were performed in the Ansys software package. To calibrate the bearing parameters (stiffness and damping) in the numerical model, experimental measurements of the rotor kit with a disc mounted at the midspan of the shaft were performed. As a result of modal analysis, natural frequencies and models were obtained. Using the Campbell’s diagram, the critical speeds and the influence of the gyroscopic effects on the natural frequencies were determined. The responses of the rotor kit to different unbalance distributions were considered by harmonic analysis.
{"title":"Unbalance Response Analysis of a Rotor Kit with Two Identical Discs Located Between Bearings","authors":"M. Katinić, Josip Kolar, P. Konjatić, M. Bošnjaković","doi":"10.31803/tg-20220920172008","DOIUrl":"https://doi.org/10.31803/tg-20220920172008","url":null,"abstract":"In this paper, the dynamic behavior of a rotor kit with two identical disks located between the plain bearings was analyzed. Modal and harmonic analysis of this rotor kit configuration were performed in the Ansys software package. To calibrate the bearing parameters (stiffness and damping) in the numerical model, experimental measurements of the rotor kit with a disc mounted at the midspan of the shaft were performed. As a result of modal analysis, natural frequencies and models were obtained. Using the Campbell’s diagram, the critical speeds and the influence of the gyroscopic effects on the natural frequencies were determined. The responses of the rotor kit to different unbalance distributions were considered by harmonic analysis.","PeriodicalId":43419,"journal":{"name":"TEHNICKI GLASNIK-TECHNICAL JOURNAL","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69414877","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}
Pub Date : 2023-05-14DOI: 10.31803/tg-20221206210933
Safiye Ipek Ayvaz, Emre Özer
In this study, AISI 1040 and AISI 4140 steels were boriding using Ekabor-II commercial boriding powder with powder-pack boriding method using microwave and conventional heating methods. The samples were borided at 950 °C for 2 and 6 hours in an Ar atmosphere in a microwave oven of Enerzi-Mh2912-V8. Biphasic structure (FeB/Fe2B) was formed in all borided AISI 4140 samples and AISI 1040 samples borided for 6 hours. A single-phase structure was observed in AISI 1040 steel borided for 2 hours. Compared to the conventional method, a 1.5-1.6 times thicker boride layer was obtained in AISI 4140 and AISI 1040 steels with microwave-assisted powder-pack boriding. The highest hardness was measured as 1561.8 HV0.05 for boriding AISI 4140 steel and 1499.7 HV0.05 for boriding AISI 1040 steel. The Vickers indentation fracture toughness of borided steels with microwave energy varied between 2.31 and 3.46 MPa·m1/2. It was determined that in all samples borided by the microwave-assisted and conventional powder-pack boriding method, the adhesion strength between the boride layers and the substrate obtained was sufficient.
{"title":"Comparative Study of Conventional and Microwave-Assisted Boriding of AISI 1040 and AISI 4140 Steels","authors":"Safiye Ipek Ayvaz, Emre Özer","doi":"10.31803/tg-20221206210933","DOIUrl":"https://doi.org/10.31803/tg-20221206210933","url":null,"abstract":"In this study, AISI 1040 and AISI 4140 steels were boriding using Ekabor-II commercial boriding powder with powder-pack boriding method using microwave and conventional heating methods. The samples were borided at 950 °C for 2 and 6 hours in an Ar atmosphere in a microwave oven of Enerzi-Mh2912-V8. Biphasic structure (FeB/Fe2B) was formed in all borided AISI 4140 samples and AISI 1040 samples borided for 6 hours. A single-phase structure was observed in AISI 1040 steel borided for 2 hours. Compared to the conventional method, a 1.5-1.6 times thicker boride layer was obtained in AISI 4140 and AISI 1040 steels with microwave-assisted powder-pack boriding. The highest hardness was measured as 1561.8 HV0.05 for boriding AISI 4140 steel and 1499.7 HV0.05 for boriding AISI 1040 steel. The Vickers indentation fracture toughness of borided steels with microwave energy varied between 2.31 and 3.46 MPa·m1/2. It was determined that in all samples borided by the microwave-assisted and conventional powder-pack boriding method, the adhesion strength between the boride layers and the substrate obtained was sufficient.","PeriodicalId":43419,"journal":{"name":"TEHNICKI GLASNIK-TECHNICAL JOURNAL","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69414935","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}
Pub Date : 2023-05-14DOI: 10.31803/tg-20230429094940
Ivana Cukor, Miro Hegedic
This article aims to enhance existing understanding of incorporating sustainability aspects during the product development and seeks to fill the gaps regarding the relationship between LPD and sustainability aspects. An up-to-date literature review was performed. More specifically, the expansion of current knowledge covers finding instances in earlier studies that explain the meaning of a sustainability aspect, such as environmental, social and economic aspect. Also, this article focuses on exploring various sustainability aspects using lean product development (LPD) tools and practices. LPD tools and practices that would enable the achievement of sustainability objectives are presented. The findings suggest that the chance for the integration of sustainability in product development comes when integrating sustainability aspects in LPD methods and tools that are used in companies daily. An analysis of the impact of every single LPD tools on individual aspects of sustainability is lacking. The paper concludes with recommendations for future research.
{"title":"Lean Product Development Tools for Promotion of Sustainability Integration in Product Development","authors":"Ivana Cukor, Miro Hegedic","doi":"10.31803/tg-20230429094940","DOIUrl":"https://doi.org/10.31803/tg-20230429094940","url":null,"abstract":"This article aims to enhance existing understanding of incorporating sustainability aspects during the product development and seeks to fill the gaps regarding the relationship between LPD and sustainability aspects. An up-to-date literature review was performed. More specifically, the expansion of current knowledge covers finding instances in earlier studies that explain the meaning of a sustainability aspect, such as environmental, social and economic aspect. Also, this article focuses on exploring various sustainability aspects using lean product development (LPD) tools and practices. LPD tools and practices that would enable the achievement of sustainability objectives are presented. The findings suggest that the chance for the integration of sustainability in product development comes when integrating sustainability aspects in LPD methods and tools that are used in companies daily. An analysis of the impact of every single LPD tools on individual aspects of sustainability is lacking. The paper concludes with recommendations for future research.","PeriodicalId":43419,"journal":{"name":"TEHNICKI GLASNIK-TECHNICAL JOURNAL","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47110355","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}
Pub Date : 2023-05-14DOI: 10.31803/tg-20230109111604
J. Kim
The study concerns the transverse deformation behavior of a penetrator surrounded by sabot in a deformed gun barrel. In the gun barrel, transverse deformation occurs in the penetrator due to problems such as deflection by gravity, or geometric tolerance caused by the manufacturing process. This deformation causes structural instability problems and affects out-of-gun barrel movement. In addition, the deformation and structural safety of the penetrator is affected by the sabot supporting the penetrator. The finite element method was used to evaluate the effect of the sabot. Deformation and stress analysis were performed for the penetrator moving in the gun barrel, and the effect of the elastic modulus of the sabot on the deformation of the penetrator was studied.
{"title":"Analysis of the Behavior of a Penetrator Advancing Through a Guide Surface","authors":"J. Kim","doi":"10.31803/tg-20230109111604","DOIUrl":"https://doi.org/10.31803/tg-20230109111604","url":null,"abstract":"The study concerns the transverse deformation behavior of a penetrator surrounded by sabot in a deformed gun barrel. In the gun barrel, transverse deformation occurs in the penetrator due to problems such as deflection by gravity, or geometric tolerance caused by the manufacturing process. This deformation causes structural instability problems and affects out-of-gun barrel movement. In addition, the deformation and structural safety of the penetrator is affected by the sabot supporting the penetrator. The finite element method was used to evaluate the effect of the sabot. Deformation and stress analysis were performed for the penetrator moving in the gun barrel, and the effect of the elastic modulus of the sabot on the deformation of the penetrator was studied.","PeriodicalId":43419,"journal":{"name":"TEHNICKI GLASNIK-TECHNICAL JOURNAL","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47162571","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}
Pub Date : 2023-05-13DOI: 10.31803/tg-20230224142711
Chil-Yuob Choo
This paper analyzes the effect of the characteristics of 5G services on users' continuous intention to use, focusing on the technology acceptance model. With the start of the fourth industrial revolution in the 21st century, 5G is the best technology used in the Internet of Things, high-speed information and communication, artificial intelligence, big data, autonomous vehicles, virtual reality, augmented reality, robots, nanotechnology, and blockchain. The technical characteristics of 5G ultra-high-speed information communication are represented by ultra-high speed, ultra-high capacity, ultra-low delay, and ultra-high connectivity. 5G mobile communication technology is essential, and after the technology provided by 5G services is commercialized, it can play all its roles as a practical core new growth engine. 5G mobile communication (hereinafter referred to as 5G) is far superior to LTE, which is a 4G mobile communication, in terms of transmission speed, waiting time, and terminal capacity. 5G service is not just an axis of the process of developing mobile communication technology, but also the creation of innovative corporate value of technology. This is because higher network quality and innovation with 5G service technology will improve perceived usability, perceived ease of use, and perceived entertainment, which will ultimately have a positive impact on users' intention to use 5G services. Therefore, due to the lack of investment in information and communication bases, platforms, and applications, this paper can be used as the basis for establishing government policies.
{"title":"A Study on the Effect of Quality Factors of Smartphone 5G Technology on the Reliability of Information and Communication Policy","authors":"Chil-Yuob Choo","doi":"10.31803/tg-20230224142711","DOIUrl":"https://doi.org/10.31803/tg-20230224142711","url":null,"abstract":"This paper analyzes the effect of the characteristics of 5G services on users' continuous intention to use, focusing on the technology acceptance model. With the start of the fourth industrial revolution in the 21st century, 5G is the best technology used in the Internet of Things, high-speed information and communication, artificial intelligence, big data, autonomous vehicles, virtual reality, augmented reality, robots, nanotechnology, and blockchain. The technical characteristics of 5G ultra-high-speed information communication are represented by ultra-high speed, ultra-high capacity, ultra-low delay, and ultra-high connectivity. 5G mobile communication technology is essential, and after the technology provided by 5G services is commercialized, it can play all its roles as a practical core new growth engine. 5G mobile communication (hereinafter referred to as 5G) is far superior to LTE, which is a 4G mobile communication, in terms of transmission speed, waiting time, and terminal capacity. 5G service is not just an axis of the process of developing mobile communication technology, but also the creation of innovative corporate value of technology. This is because higher network quality and innovation with 5G service technology will improve perceived usability, perceived ease of use, and perceived entertainment, which will ultimately have a positive impact on users' intention to use 5G services. Therefore, due to the lack of investment in information and communication bases, platforms, and applications, this paper can be used as the basis for establishing government policies.","PeriodicalId":43419,"journal":{"name":"TEHNICKI GLASNIK-TECHNICAL JOURNAL","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69414705","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}
Pub Date : 2023-05-13DOI: 10.31803/tg-20230502171228
Davor Kolar, D. Lisjak, Martin Curman, Juraj Benić
Rotating parts can be found in almost all operational equipment in the industry and are of great importance for proper operation. However, reliability theory explains that every industrial system can change its state when failure happens. Predictive maintenance as one of the latest maintenance strategy emerged from the Maintenance 4.0 concept. Nowadays, this concept can include Industrial Internet of Things (IIoT) devices to connect industrial assets thus enable data collection and analysis that can help make better decisions about maintenance activity. Robust data acquisition system is a prerequisite for any modern predictive maintenance task as it provides necessary data for further analysis and health assessment of the industry asset. Fault diagnosis is an important task in the maintenance of industrial rotating subsystems, considering that early state change diagnosis and fault identification can prevent system failure. Vibration analysis in theory and practice is considered a correct technique for early detection of state changes and failure diagnostics of rotating subsystems. The identified technical state should be considered in a context of the ability and different inability states. Therefore, early different inability states identification is the next step in the rotary machinery diagnostics procedure. Most of the existing techniques for fault diagnosis of rotating subsystems that use vibrations involve the step of extracting features from the raw signal. Considering that the features that describe the behavior of the rotary subsystem can differ significantly depending on the type of equipment, such an approach usually requires an expert in the field of signal processing and rotary subsystems who can define the necessary features. Recently, the emergence of machine deep learning and its application in maintenance promises to provide highly efficient fault diagnostics while simultaneously reducing the need for expert knowledge and human labour. This paper presents authors aim to use self-developed IIoT system built as an IIoT accelerometer as the edge device, web API and database with convolutional neural network as deep learning-based data-driven fault diagnosis to detect and identify different inability states of rotating subsystems. Large dataset for two different rotational speed is collected using IIOT system and multiple convolutional neural network models are trained and tested to examine possibility of using IIOT for inability state prediction.
{"title":"Identification of Inability States of Rotating Machinery Subsystems Using Industrial IoT and Convolutional Neural Network – Initial Research","authors":"Davor Kolar, D. Lisjak, Martin Curman, Juraj Benić","doi":"10.31803/tg-20230502171228","DOIUrl":"https://doi.org/10.31803/tg-20230502171228","url":null,"abstract":"Rotating parts can be found in almost all operational equipment in the industry and are of great importance for proper operation. However, reliability theory explains that every industrial system can change its state when failure happens. Predictive maintenance as one of the latest maintenance strategy emerged from the Maintenance 4.0 concept. Nowadays, this concept can include Industrial Internet of Things (IIoT) devices to connect industrial assets thus enable data collection and analysis that can help make better decisions about maintenance activity. Robust data acquisition system is a prerequisite for any modern predictive maintenance task as it provides necessary data for further analysis and health assessment of the industry asset. Fault diagnosis is an important task in the maintenance of industrial rotating subsystems, considering that early state change diagnosis and fault identification can prevent system failure. Vibration analysis in theory and practice is considered a correct technique for early detection of state changes and failure diagnostics of rotating subsystems. The identified technical state should be considered in a context of the ability and different inability states. Therefore, early different inability states identification is the next step in the rotary machinery diagnostics procedure. Most of the existing techniques for fault diagnosis of rotating subsystems that use vibrations involve the step of extracting features from the raw signal. Considering that the features that describe the behavior of the rotary subsystem can differ significantly depending on the type of equipment, such an approach usually requires an expert in the field of signal processing and rotary subsystems who can define the necessary features. Recently, the emergence of machine deep learning and its application in maintenance promises to provide highly efficient fault diagnostics while simultaneously reducing the need for expert knowledge and human labour. This paper presents authors aim to use self-developed IIoT system built as an IIoT accelerometer as the edge device, web API and database with convolutional neural network as deep learning-based data-driven fault diagnosis to detect and identify different inability states of rotating subsystems. Large dataset for two different rotational speed is collected using IIOT system and multiple convolutional neural network models are trained and tested to examine possibility of using IIOT for inability state prediction.","PeriodicalId":43419,"journal":{"name":"TEHNICKI GLASNIK-TECHNICAL JOURNAL","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47412816","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}
Pub Date : 2023-05-13DOI: 10.31803/tg-20230424191508
Z. Keran, Amalija Horvatić Novak, Andrej Razumić, B. Runje, P. Piljek
The presence of dislocations significantly modifies the mechanical properties of crystalline solids. Severe plastic deformation (SPD) and the most used SPD process – the Equal Channel Angular Pressing (ECAP), affect the multiplication and localized accumulation of dislocations. This research is related to the observation of dislocation pile-up and significant reduction of the crystalline grain size caused by severe deformations in the ECAP process of the widely used aluminium material (Al 99.5%). Because of its lightweight, the application of Al 99.5 % can pose a challenge for the aviation and space industry, especially since its mechanical properties limit its application. Improving these mechanical properties can extend its applicability in cases of demanding constructions as well as influence the final product cost. As a confirmation of SPD in-fluence on mechanical properties, material hardness has been examined and described. Dislocation monitoring is enabled using the light and electron microscopy and AFM (Atomic Force Microscope) device. A numerical simulation of the Equal Channel Angular Pressing process using the ABAQUS software package determined the representative area of the most severe deformation.
{"title":"In-Crystal Dislocation Behaviour and Hardness Changes in the Case of Severe Plastic Deformation of Aluminium Samples","authors":"Z. Keran, Amalija Horvatić Novak, Andrej Razumić, B. Runje, P. Piljek","doi":"10.31803/tg-20230424191508","DOIUrl":"https://doi.org/10.31803/tg-20230424191508","url":null,"abstract":"The presence of dislocations significantly modifies the mechanical properties of crystalline solids. Severe plastic deformation (SPD) and the most used SPD process – the Equal Channel Angular Pressing (ECAP), affect the multiplication and localized accumulation of dislocations. This research is related to the observation of dislocation pile-up and significant reduction of the crystalline grain size caused by severe deformations in the ECAP process of the widely used aluminium material (Al 99.5%). Because of its lightweight, the application of Al 99.5 % can pose a challenge for the aviation and space industry, especially since its mechanical properties limit its application. Improving these mechanical properties can extend its applicability in cases of demanding constructions as well as influence the final product cost. As a confirmation of SPD in-fluence on mechanical properties, material hardness has been examined and described. Dislocation monitoring is enabled using the light and electron microscopy and AFM (Atomic Force Microscope) device. A numerical simulation of the Equal Channel Angular Pressing process using the ABAQUS software package determined the representative area of the most severe deformation.","PeriodicalId":43419,"journal":{"name":"TEHNICKI GLASNIK-TECHNICAL JOURNAL","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69414757","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}
Pub Date : 2023-05-13DOI: 10.31803/tg-20221220200605
Tae-Yeong Jeong, Il-Kyu Ha
Smoking is an extremely important health problem in modern society. This study focuses on a method for preventing smoking in non-smoking areas, such as public places, as well as the development of an artificial neural network based smoking motion recognition system for more accurately recognizing smokers in such areas. In particular, we attempted to increase the rate of recognition of smoking behaviors using an OpenPose based algorithm and the accuracy of such recognition by additionally applying a hardware device for recognizing cigarette smoke. In addition, a preprocessing method for inputting a dataset into the proposed system is proposed. To improve the recognition performance, four types of dataset models were created, and the most suitable dataset model was selected experimentally. Based on this dataset model, test data were created and input into the proposed neural network based smoking behavior recognition system. In addition, the nearest neighbor interpolation method was selected experimentally as an image interpolation approach and applied to the image preprocessing. When applying experimental data based on learned data, the developed system showed a recognition rate of 70-75%, and the smoking recognition accuracy was increased through the addition of the hardware device.
{"title":"OpenPose based Smoking Gesture Recognition System using Artificial Neural Network","authors":"Tae-Yeong Jeong, Il-Kyu Ha","doi":"10.31803/tg-20221220200605","DOIUrl":"https://doi.org/10.31803/tg-20221220200605","url":null,"abstract":"Smoking is an extremely important health problem in modern society. This study focuses on a method for preventing smoking in non-smoking areas, such as public places, as well as the development of an artificial neural network based smoking motion recognition system for more accurately recognizing smokers in such areas. In particular, we attempted to increase the rate of recognition of smoking behaviors using an OpenPose based algorithm and the accuracy of such recognition by additionally applying a hardware device for recognizing cigarette smoke. In addition, a preprocessing method for inputting a dataset into the proposed system is proposed. To improve the recognition performance, four types of dataset models were created, and the most suitable dataset model was selected experimentally. Based on this dataset model, test data were created and input into the proposed neural network based smoking behavior recognition system. In addition, the nearest neighbor interpolation method was selected experimentally as an image interpolation approach and applied to the image preprocessing. When applying experimental data based on learned data, the developed system showed a recognition rate of 70-75%, and the smoking recognition accuracy was increased through the addition of the hardware device.","PeriodicalId":43419,"journal":{"name":"TEHNICKI GLASNIK-TECHNICAL JOURNAL","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47550152","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}
Pub Date : 2023-05-13DOI: 10.31803/tg-20230417145110
U. Župerl, M. Kovačič
When machining difficult-to-cut metal materials often used to make sheet metal forming tools, excessive cutting force jumps often break the cutting edge. Therefore, this research developed a system of three neural network models to accurately predict the maximal cutting forces on the cutting edge in helical end milling of layered metal material. The model considers the different machinability of individual layers of a multilayer metal material. Comparing the neural force system with a linear regression model and experimental data shows that the system accurately predicts the cutting force when milling layered metal materials for a combination of specific cutting parameters. The predicted values of the cutting forces agree well with the measured values. The maximum error of the predicted cutting forces is 5.85% for all performed comparative tests. The obtained model accuracy is 98.65%.
{"title":"Artificial Neural Network System for Predicting Cutting Forces in Helical-End Milling of Laser-Deposited Metal Materials","authors":"U. Župerl, M. Kovačič","doi":"10.31803/tg-20230417145110","DOIUrl":"https://doi.org/10.31803/tg-20230417145110","url":null,"abstract":"When machining difficult-to-cut metal materials often used to make sheet metal forming tools, excessive cutting force jumps often break the cutting edge. Therefore, this research developed a system of three neural network models to accurately predict the maximal cutting forces on the cutting edge in helical end milling of layered metal material. The model considers the different machinability of individual layers of a multilayer metal material. Comparing the neural force system with a linear regression model and experimental data shows that the system accurately predicts the cutting force when milling layered metal materials for a combination of specific cutting parameters. The predicted values of the cutting forces agree well with the measured values. The maximum error of the predicted cutting forces is 5.85% for all performed comparative tests. The obtained model accuracy is 98.65%.","PeriodicalId":43419,"journal":{"name":"TEHNICKI GLASNIK-TECHNICAL JOURNAL","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69414752","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}
This study proposes a method for maintaining parallelism of the optical cavity of a laser interferometer using machine learning. The Fabry-Perot interferometer is utilized as an experimental optical structure in this research due to its advantage of having a brief optical structure. The supervised machine learning method is used to train algorithms to accurately classify and predict the tilt angle of the plane mirror using labeled interference images. Based on the predicted results, stepper motors are fixed on a plane mirror that can automatically adjust the pitch and yaw angles. According to the experimental results, the average correction error and standard deviation in 17-grid classification experiment are 32.38 and 11.21 arcseconds, respectively. In 25-grid classification experiment, the average correction error and standard deviation are 19.44 and 7.86 arcseconds, respectively. The results show that this parallelism maintenance technology has essential for the semiconductor industry and precision positioning technology.
{"title":"Leveling Maintenance Mechanism by Using the Fabry-Perot Interferometer with Machine\u0000Learning Technology","authors":"Syuan-Cheng Chang, Chung-Ping Chang, Yung-Cheng Wang, Chi-Chieh Chu","doi":"10.31803/tg-20230425154156","DOIUrl":"https://doi.org/10.31803/tg-20230425154156","url":null,"abstract":"This study proposes a method for maintaining parallelism of the optical cavity of a laser interferometer using machine learning. The Fabry-Perot interferometer is utilized as an experimental optical structure in this research due to its advantage of having a brief optical structure. The supervised machine learning method is used to train algorithms to accurately classify and predict the tilt angle of the plane mirror using labeled interference images. Based on the predicted results, stepper motors are fixed on a plane mirror that can automatically adjust the pitch and yaw angles. According to the experimental results, the average correction error and standard deviation in 17-grid classification experiment are 32.38 and 11.21 arcseconds, respectively. In 25-grid classification experiment, the average correction error and standard deviation are 19.44 and 7.86 arcseconds, respectively. The results show that this parallelism maintenance technology has essential for the semiconductor industry and precision positioning technology.","PeriodicalId":43419,"journal":{"name":"TEHNICKI GLASNIK-TECHNICAL JOURNAL","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69414793","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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