Int. J. Autom. Technol.最新文献_第3页

Multi-Scale Batch-Learning Growing Neural Gas Efficiently for Dynamic Data Distributions 动态数据分布的多尺度批量学习神经气体生长

Int. J. Autom. Technol. Pub Date : 2023-05-05 DOI: 10.20965/ijat.2023.p0206

Fernando Ardilla, Azhar Aulia Saputra, N. Kubota

{"title":"Multi-Scale Batch-Learning Growing Neural Gas Efficiently for Dynamic Data Distributions","authors":"Fernando Ardilla, Azhar Aulia Saputra, N. Kubota","doi":"10.20965/ijat.2023.p0206","DOIUrl":"https://doi.org/10.20965/ijat.2023.p0206","url":null,"abstract":"Growing neural gas (GNG) has many applications, including topology preservation, feature extraction, dynamic adaptation, clustering, and dimensionality reduction. These methods have broad applicability in extracting the topological structure of 3D point clouds, enabling unsupervised motion estimation, and depicting objects within a scene. Furthermore, multi-scale batch-learning GNG (MS-BL-GNG) has improved learning convergence. However, it is only implemented on static or stationary datasets, and adapting to dynamic data remains difficult. Similarly, the learning rate cannot be increased if new nodes are added to the existing network after accumulating errors in the sampling data. Next, we propose a new growth approach that, when applied to MS-BL-GNG, significantly increases the learning speed and adaptability of dynamic data distribution input patterns. This method immediately adds data samples as new nodes to existing networks. The probability of adding a new node is determined by the distance between the first, second, and third closest nodes. We applied our method for monitoring a moving object at its pace to demonstrate the usefulness of the proposed model. In addition, optimization methods are used such that processing can be performed in real-time.","PeriodicalId":13583,"journal":{"name":"Int. J. Autom. Technol.","volume":"61 1","pages":"206-216"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90728113","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}

引用次数: 0

Diagnosis Method of Lubrication Failure by Coolant Immersion for a CNC Lathe Spindle 数控车床主轴浸液润滑故障诊断方法

Int. J. Autom. Technol. Pub Date : 2023-03-05 DOI: 10.20965/ijat.2023.p0103

Keigo Takasugi, Naohiko Suzuki, Y. Kaneko, N. Asakawa

引用次数: 0

Utilization Method and Effect Evaluation of Systems Thinking in Future Design: Comparative Analysis of Policy-Making Workshops in Local Governments 系统思维在未来设计中的运用方法与效果评价:地方政府决策研讨会的比较分析

Int. J. Autom. Technol. Pub Date : 2023-03-05 DOI: 10.20965/ijat.2023.p0183

Yutaka Nomaguchi, Ryotaro Senoo, Shinya Fukutomi, K. Hara, K. Fujita

{"title":"Utilization Method and Effect Evaluation of Systems Thinking in Future Design: Comparative Analysis of Policy-Making Workshops in Local Governments","authors":"Yutaka Nomaguchi, Ryotaro Senoo, Shinya Fukutomi, K. Hara, K. Fujita","doi":"10.20965/ijat.2023.p0183","DOIUrl":"https://doi.org/10.20965/ijat.2023.p0183","url":null,"abstract":"The Future Design (FD) workshop (FDWS) is a discussion framework based on FD. The aim of FD is to activate a human trait called futurability, considering the preferences of future generations. Previous FD practices with the theme of policy-making in local governments have demonstrated this possibility. However, creating concrete proposals might depend on workshop participants’ abilities and emotions to perceive future society. By comparing two case studies, this study examines the effects of a method for utilizing a causal loop diagram (CLD), a tool for systems thinking, in FDWS to systematically draw the future society and activate discussions among the participants. CLD is a qualitative system model that helps identify the factors that lead to systemic problems and analyze the guidelines for solving them. Its effects on the performance of the FDWS discussion activity are evaluated. They are quantified by text mining analysis using participants’ remark records. Two case studies conducted at policy-making workshops in the local governments of Japan are examined. One is the FDWS in Kyoto City which adopted the proposed CLD utilization method, and the other is the FDWS in Suita City without CLD. The comparative analysis demonstrates that the proposed method makes the discussion livelier, less divergent, and more developed in the FDWS.","PeriodicalId":13583,"journal":{"name":"Int. J. Autom. Technol.","volume":"2 1","pages":"183-193"},"PeriodicalIF":0.0,"publicationDate":"2023-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80363280","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}

引用次数: 0

Augmented Reality-Based System for Skill Transfer of Workpiece Fixturing in Turning Operations 基于增强现实的车削加工中工件夹具技能传递系统

Int. J. Autom. Technol. Pub Date : 2023-03-05 DOI: 10.20965/ijat.2023.p0136

K. Nishida, Masatoshi Itoh, K. Nakamoto

{"title":"Augmented Reality-Based System for Skill Transfer of Workpiece Fixturing in Turning Operations","authors":"K. Nishida, Masatoshi Itoh, K. Nakamoto","doi":"10.20965/ijat.2023.p0136","DOIUrl":"https://doi.org/10.20965/ijat.2023.p0136","url":null,"abstract":"For machining operations, preparation work called a “setting operation” is always required in advance. The setting operation, which affects the lead time and machining accuracy, strongly depends on the skill level of the operator. Therefore, to improve the quality of machining operations, skill transfer is necessary by extracting and generalizing the skills related to the setting operation. In addition, a variety of accidents often occur during the setting operation. This can lead to machine tool failure or a serious incident involving the operator. Thus, skill transfer to an unskilled operator is also important for work safety. On the other hand, augmented reality (AR) is a promising human-computer interaction technology to support skill transfer at the manufacturing site. An AR technology generally overlays virtual images on the real-world environment. In this study, an AR-based system is developed to demonstrate a recommended workpiece fixturing method in turning operations for assisting unskilled operators as the first step of skill transfer. In turning operations, two types of fixturing are usually assumed: outer diameter clamping and inner diameter clamping. The dimensions of the targeted product shape are detected, and the workpiece shape is obtained. The removal volume to be machined is calculated as the difference between the targeted product shape and workpiece shape. The fixturing method is determined to avoid contact between the removal volume and the assumed jaw. The results of a case study show that the developed AR-based system is effective for skill transfer of workpiece fixturing by demonstrating the recommended fixturing method using skills acquired from operators.","PeriodicalId":13583,"journal":{"name":"Int. J. Autom. Technol.","volume":"73 1","pages":"136-143"},"PeriodicalIF":0.0,"publicationDate":"2023-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85703430","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}

引用次数: 0

Feasibility Study of Laser-Assisted Incremental Forming for Carbon Fiber Reinforced Thermo Plastic Based on 3D-CAD Data 基于3D-CAD数据的碳纤维增强热塑性塑料激光辅助增量成形可行性研究

Int. J. Autom. Technol. Pub Date : 2023-03-05 DOI: 10.20965/ijat.2023.p0144

Hidetake Tanaka, K. Yamada, Tatsuki Ikari

引用次数: 0

Machine Learning-Based Shape Error Estimation Using the Servomotor Current Generated During Micro-Milling of a Micro-Lens Mold 基于机器学习的微透镜模具微铣削伺服电机电流形状误差估计

Int. J. Autom. Technol. Pub Date : 2023-03-05 DOI: 10.20965/ijat.2023.p0092

Kenta Mizuhara, Daisuke Nakamichi, Wataru Yanagihara, Y. Kakinuma

{"title":"Machine Learning-Based Shape Error Estimation Using the Servomotor Current Generated During Micro-Milling of a Micro-Lens Mold","authors":"Kenta Mizuhara, Daisuke Nakamichi, Wataru Yanagihara, Y. Kakinuma","doi":"10.20965/ijat.2023.p0092","DOIUrl":"https://doi.org/10.20965/ijat.2023.p0092","url":null,"abstract":"The demand for the mass production of micro-lens arrays (MLAs) is increasing. An MLA is fabricated through an injection molding process, and its mold is manufactured by a five-axis high-precision machine tool using a small diameter endmill. A visual examination is not available to judge the quality of the mold while machining. Therefore, an effective process monitoring technology must be developed. A promising approach is to apply a servomotor current to in-process monitoring because as long as the servomotor works well, no external sensors, capital investment, or maintenance processes are required. From this perspective, a machine learning-based shape error estimation method using only the servomotor current is proposed. To explore the relationship between the motor current generated during micro-milling and the shape error of the mold, the servomotor current in X-, Y-, and Z-axes was recorded, and the corresponding shape error of the MLA mold was measured after machining. Input data were prepared by converting time-domain servomotor current data to frequency-domain data using short-time Fourier transform and reducing the dimensions of the data via principal component analysis. In terms of a meaningful label for the output data, the average shape error in the machined area corresponding to each window was provided. The input/output relationships were used to train five different machine learning models, and the accuracy of shape error estimation using each model was evaluated. In addition, the estimation accuracies using the X-, Y-, and Z-axes were compared to find the axis that senses the shape error with the highest accuracy. The results show that the non-linear method using the X-axis servomotor current information closest to the machining point achieved the highest shape error estimation accuracy.","PeriodicalId":13583,"journal":{"name":"Int. J. Autom. Technol.","volume":"30 1","pages":"92-102"},"PeriodicalIF":0.0,"publicationDate":"2023-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82666333","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}

引用次数: 0

Automatic Parts Correspondence Determination for Transforming Assemblies via Local and Global Geometry Processing 局部和全局几何处理变换装配件的零件对应关系自动确定

Int. J. Autom. Technol. Pub Date : 2023-03-05 DOI: 10.20965/ijat.2023.p0176

Hayata Shibuya, Y. Nagai

{"title":"Automatic Parts Correspondence Determination for Transforming Assemblies via Local and Global Geometry Processing","authors":"Hayata Shibuya, Y. Nagai","doi":"10.20965/ijat.2023.p0176","DOIUrl":"https://doi.org/10.20965/ijat.2023.p0176","url":null,"abstract":"Transforming assemblies are products that alter their shapes by re-assembling their parts. This idea is applied to a wide range of objects from folding gadgets as outdoor gear aimed at saving space, to robotic characters fighting in Hollywood films which drastically change their appearance. While the former type falls into a folding or packing problems, the latter requires a different viewpoint to be solved since the destination shape is not necessarily aiming at minimizing the occupation space. As a possible solution, this kind of deformation can be decomposed into segmentation of the shape to parts and parts matching. Segmentation is a general problem in shape modeling and numerous algorithms have been proposed for this. On the other hand, matching simultaneously multiple parts (many-to-many matching) has hardly been explored. This study develops a many-to-many matching algorithm for surface meshes of parts from two distinct destination shapes of a single transforming assembly. The proposed algorithm consists of a local geometry analysis and a global optimization of parts combination based on such analysis. For the local geometry analysis, the surface geometric feature is described by a local shape descriptor. Some vertices are detected as feature points by intrinsic shape signature (ISS) and the geometry at the feature points is expressed by the signature of histogram of orientation (SHOT). For all the combination of pairs from each destination shape, the number of feature points with similar descriptor values is counted. In the global optimization, the final matching is determined by the maximum weight matching on a complete bipartite graph whose nodes are the parts, and edges are weighted by the number of the feature points with similar descriptors. We present successful results for several examples to empirically show the effectiveness of the proposed algorithm.","PeriodicalId":13583,"journal":{"name":"Int. J. Autom. Technol.","volume":"10 1","pages":"176-182"},"PeriodicalIF":0.0,"publicationDate":"2023-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74300038","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}

引用次数: 0

Acquisition of Skills for Process Planning Through Eye Tracking When Understanding Mechanical Drawings 在理解机械图纸时通过眼动追踪获得工艺规划技能

Int. J. Autom. Technol. Pub Date : 2023-03-05 DOI: 10.20965/ijat.2023.p0128

Takumu Yoshikawa, Fumihiro Nakamura, E. Sogabe, K. Nakamoto

{"title":"Acquisition of Skills for Process Planning Through Eye Tracking When Understanding Mechanical Drawings","authors":"Takumu Yoshikawa, Fumihiro Nakamura, E. Sogabe, K. Nakamoto","doi":"10.20965/ijat.2023.p0128","DOIUrl":"https://doi.org/10.20965/ijat.2023.p0128","url":null,"abstract":"In parts machining, process planning is typically conducted by skillful operators. The quality of machining is highly dependent on process planning, which determines the operation parameters, such as the operation sequence and cutting tool. To achieve high-quality machining without depending on the skill level of the operators, standardization of process planning is desired. Therefore, it is necessary to extract and generalize skills related to process planning. Furthermore, eye tracking technology is expected to visualize unconscious human behavior. In this study, eye tracking technology is adopted to detect the movement of the operator’s eyes and gather gaze data when understanding mechanical drawings. Gaze data are analyzed using a heat map and bubble chart to identify differences in eye movement according to skill level. The analyzed heat maps indicate that the gazes of the skillful operator are gathered because the operator focuses on the area that is strongly related to the quality of machining. The analyzed bubble charts also indicate that the skillful operator considers the machining process by checking annotations, then understands the shape, and finally verifies the numerical values of the annotations. From the results of interviews performed based on the analysis, the individual skill could be effectively extracted in detail, particularly the skill regarding the operation sequence. Furthermore, the acquired skills are incorporated into a computer-aided process planning system developed in a previous study. The operation sequence is modified to reflect the acquired skills. Machining experiments confirmed the effectiveness of adopting operators’ skills in process planning.","PeriodicalId":13583,"journal":{"name":"Int. J. Autom. Technol.","volume":"2012 1","pages":"128-135"},"PeriodicalIF":0.0,"publicationDate":"2023-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86420102","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}

引用次数: 0

Study on Process Design Based on Language Analysis and Image Discrimination Using CNN Deep Learning 基于CNN深度学习的语言分析和图像识别流程设计研究

Int. J. Autom. Technol. Pub Date : 2023-03-05 DOI: 10.20965/ijat.2023.p0112

Akio Hayashi, Y. Morimoto

{"title":"Study on Process Design Based on Language Analysis and Image Discrimination Using CNN Deep Learning","authors":"Akio Hayashi, Y. Morimoto","doi":"10.20965/ijat.2023.p0112","DOIUrl":"https://doi.org/10.20965/ijat.2023.p0112","url":null,"abstract":"At present, machining with numerically controlled (NC) machine tools is mostly performed by NC programs generated by computer-aided design and computer-aided manufacturing (CAD/CAM) systems. However, even if the machining shape to be machined is the same, there are numerous machining processes involving a series of operations such as determining the machining area, machining order, and machining conditions. These are entrusted to the user, and automation is difficult. In addition, these tasks depend on the experience and know-how of skilled engineers, and it is very difficult to convert them into algorithms and reflect them in the creation of NC programs. Therefore, in this study, artificial intelligence (AI) was used for the process design of multi-tasking machine tools, with the goal of determining and automating the process design using shape examples. We propose a shape recognition method that includes image analysis by AI. This image analysis makes it possible to determine the characteristics of the machining shape, and the machining operator can easily judge the machining process based on the CAD model. Furthermore, because there are shapes that cannot be determined from image data alone, shape features are also extracted from the STEP file of the CAD model. A language analysis of the STEP file can find the characteristic components and their numerical information to determine the coordinates of the shape features. By combining image analysis and language analysis, the method can easily judge the process based on the information in the CAD model. Finally, using the generated learning model and analysis program, we conducted a test to determine whether a multitasking machine tool is necessary for machining.","PeriodicalId":13583,"journal":{"name":"Int. J. Autom. Technol.","volume":"14 1","pages":"112-119"},"PeriodicalIF":0.0,"publicationDate":"2023-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88586156","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}

引用次数: 0

Editorial: Application of Artificial Intelligence Techniques in Production Engineering 社论:人工智能技术在生产工程中的应用

Int. J. Autom. Technol. Pub Date : 2023-03-05 DOI: 10.20965/ijat.2023.p0091

K. Nakamoto, Keigo Takasugi

{"title":"Editorial: Application of Artificial Intelligence Techniques in Production Engineering","authors":"K. Nakamoto, Keigo Takasugi","doi":"10.20965/ijat.2023.p0091","DOIUrl":"https://doi.org/10.20965/ijat.2023.p0091","url":null,"abstract":"Artificial intelligence (AI) techniques have been behind disruptive innovations in every industry. Based on AI techniques, large amounts of data can be converted into actionable insights and predictions. Manufacturers have frequently faced different kinds of challenges, such as unexpected machinery failures or defective product deliveries. Still, the adoption of AI techniques is expected to improve operational efficiency, enable the launch of new products, customize product designs, and plan future financial actions. Recently, manufacturers have been using AI techniques to improve the quality of their products, achieve greater speed and visibility across supply chains, and optimize inventory management.\u0000 Given that the attention and interest in AI techniques has been growing rapidly, it is time that the current state of the art of their practical applications be presented. The main aim of this special issue is to bring together the latest AI research and practical case studies of AI techniques in production engineering.\u0000 This special issue features 10 papers related to not only operation automation but also sophisticated skill transfer in manufacturers. Their subjects cover various advancements, such as failure diagnosis, product estimation, process planning, operation planning, and workpiece fixturing in the area of machining. Moreover, the authors boldly strive to apply AI technologies even to complex systems in manufacturing fields such as laser-assisted incremental forming, injection molded direct joining, and parts assembling.\u0000 We thank the authors for their interesting papers submitted for this special issue, and we are sure that both general readers and specialists will find the information the authors provide both interesting and informative. Moreover, we deeply appreciate the reviewers for their incisive efforts. Without these contributions, this special issue would not have been possible. We truly hope that this special issue triggers further research on AI techniques in production engineering.","PeriodicalId":13583,"journal":{"name":"Int. J. Autom. Technol.","volume":"1 1","pages":"91"},"PeriodicalIF":0.0,"publicationDate":"2023-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83997994","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}

引用次数: 0