The aim of this work is to simulate thermal deformation of tool system and investigate the influence of cutting parameters on it in single-point diamond turning(SPDT) of aluminum alloy. The experiments with various cu...The aim of this work is to simulate thermal deformation of tool system and investigate the influence of cutting parameters on it in single-point diamond turning(SPDT) of aluminum alloy. The experiments with various cutting parameters were conducted. Cutting temperature was measured by FLIR A315 infrared thermal imager. Tool wear was measured by scanning electron microscope(SEM). The numerical model of heat flux considering tool wear generated in cutting zone was established. Then two-step finite element method(FEM) simulations matching the experimental conditions were carried out to simulate the thermal deformation. In addition, the tests of deformation of tool system were performed to verify previous simulation results. And then the influence of cutting parameters on thermal deformation was investigated. The results show that the temperature and thermal deformation from simulations agree well with the results from experiments in the same conditions. The maximum thermal deformation of tool reaches to 7 μm. The average flank wear width and cutting speed are the dominant factors affecting thermal deformation, and the effective way to decrease the thermal deformation of tool is to control the tool wear and the cutting speed.展开更多
In conformity with the principle of Design for Manufacture,feature-based design strate- (?)es have been developed.As the“feature”is relevant to the“macro process plan”and“macro NC programs”,obviously,“feature”...In conformity with the principle of Design for Manufacture,feature-based design strate- (?)es have been developed.As the“feature”is relevant to the“macro process plan”and“macro NC programs”,obviously,“feature”is beyond the power of conventional solid modellers.Neverthe- less,substantial breakthrough has not been made in the solid modeling field,except“feature at- taching”or“feature recognizing”methods have been taken on.In this paper,the theory, concepts,system architecture,and algorithm principles of solid modeling tool system have been represented.The practice of Feature Solid Modeling Tool System (FSMTS) developed at Huazhong University has proved that the tool may be a new foundation of Feature-Based Design.展开更多
Dispatching optimally FMS tool system can utilize efficiently FMS automated tool provide system and raise flexibility of FMS. Some dispatch problems to be solved on FMS tool system are put forward. The models discusse...Dispatching optimally FMS tool system can utilize efficiently FMS automated tool provide system and raise flexibility of FMS. Some dispatch problems to be solved on FMS tool system are put forward. The models discussed of FMS tool system are given, and the mathematic describes are made on the models. The concept of operation tool change set is posed, and a optimal objective function is recommended. The algorithm of operation tool change set is studied and given.The developed successfully tool management system proves the algorithm is effective.展开更多
Objective:This study aimed to systematically evaluate the measurement characteristics and methodological quality of childbirth experience assessment tools,with a view to informing the selection of healthcare professio...Objective:This study aimed to systematically evaluate the measurement characteristics and methodological quality of childbirth experience assessment tools,with a view to informing the selection of healthcare professionals who can provide high-quality assessment tools.Method:A systematic search was performed on specific databases:PubMed,Web of Science,Embase,CINAHL,SinoMed,China National Knowledge Infrastructure(CNKI),and Wanfang,from inception to February 29,2024.The researchers retrieved studies on the measurement attributes of the childbirth experience assessment tool,and traced back the references of the included studies to supplement relevant literature.According to the inclusion and exclusion criteria,screening and data extraction were independently undertaken by two reviewers.Two researchers individually used the Consensus-based Standards for the Selection of Health Measurement Instruments(COSMIN)Risk of Bias Checklist to assess the methodological quality of the scale,applied the COSMIN criteria to evaluate the measurement properties of the scale,and used a modified Grading of Recommendations,Assessment,Development,and Evaluation(GRADE)system to assess the certainty of evidence.Result:A total of 15 studies were included to evaluate the psychometric properties of 11 childbirth experience assessment tools(including different language versions).Eight studies’methodological quality of content validity was doubtful,and the remaining studies did not report content validity.None of the tools reported measurement error,cross-cultural validity,or responsiveness.In light of the questionable or unreported content validity of the tools,the evidence quality was deemed moderate or below.Consequently,the 11 assessment tools were recommended as grade B.Conclusion:In contrast,the Questionnaire for Assessing the Childbirth Experience(QACE)is recommended for provisional use,given its relatively good methodological and measurement attributes and appropriate content for evaluation.However,further validation of other measurement properties is needed.展开更多
Objective expertise evaluation of individuals,as a prerequisite stage for team formation,has been a long-term desideratum in large software development companies.With the rapid advancements in machine learning methods...Objective expertise evaluation of individuals,as a prerequisite stage for team formation,has been a long-term desideratum in large software development companies.With the rapid advancements in machine learning methods,based on reliable existing data stored in project management tools’datasets,automating this evaluation process becomes a natural step forward.In this context,our approach focuses on quantifying software developer expertise by using metadata from the task-tracking systems.For this,we mathematically formalize two categories of expertise:technology-specific expertise,which denotes the skills required for a particular technology,and general expertise,which encapsulates overall knowledge in the software industry.Afterward,we automatically classify the zones of expertise associated with each task a developer has worked on using Bidirectional Encoder Representations from Transformers(BERT)-like transformers to handle the unique characteristics of project tool datasets effectively.Finally,our method evaluates the proficiency of each software specialist across already completed projects from both technology-specific and general perspectives.The method was experimentally validated,yielding promising results.展开更多
Off-axis aspherical mirrors are widely used in optical systems and precision measuring instruments,whereas off-axis aspherical mirrors with large sizes and off-axis are used in large optical systems such as astronomic...Off-axis aspherical mirrors are widely used in optical systems and precision measuring instruments,whereas off-axis aspherical mirrors with large sizes and off-axis are used in large optical systems such as astronomical telescopes and radio telescopes.However,if the off-axis amount of an off-axis aspherical mirror exceeds the capability of the machine tool,traditional rotary-turning machining methods are not applicable,and advanced computerized numerical control(CNC)machining methods,such as the slow-tool-servo method,must be im-plemented.This article proposes a non-conventional offset(NCO)fabrication method based on slow-tool-servo single-point diamond turning for machining off-axis aspherical surfaces with large off-axis amounts.This method is theoretically applicable to the machining of off-axis aspherical surfaces with any off-axis amount.NCO fab-rication is a simpler and more efficient path-planning solution for machining individual off-axis parabolic sur-faces.In addition,corresponding solutions for other types of aspherical surfaces are proposed using the NCO method.The turning depths of workpieces with different off-axis amounts at the same machining position are analyzed and compared.A specific measurement scheme for the NCO method is presented,and the experimental results indicate that the PV and RMS form errors are 0.658μm and 60 nm,respectively.This work demonstrates that the NCO method can effectively deal with the machining challenges of off-axis aspherical structures with large off-axis amounts.展开更多
The surfaces of brittle materials are susceptible to defects such as scratches,cracks,and chipping during con-ventional grinding processes,which significantly compromise surface quality and service performance.A flexi...The surfaces of brittle materials are susceptible to defects such as scratches,cracks,and chipping during con-ventional grinding processes,which significantly compromise surface quality and service performance.A flexible ball-end body-armor-like abrasive tool(BAAT)can effectively remove micro-convex peaks from the surfaces of brittle materials by employing a high tangential grinding force and a low normal grinding force,thereby achieving nano-level surface roughness and ultra-smooth mirror finishes.However,the surface contact me-chanism,pressure distribution pattern,and grinding force behavior between BAAT and workpiece remain in-adequately understood.This study examines the mechanism of liquid film formation and the distribution pattern of elastohydrodynamic pressure in high-shear and low-pressure grinding areas,drawing on the theories of elastohydrodynamic lubrication,non-Newtonian fluid dynamics,and material mechanics.A high-shear low-pressure grinding force model,which incorporates elastohydrodynamic liquid film thickness and abrasive grain size,was developed.The effects of the main grinding parameters(normal load,spindle rotational speed,and abrasive grain size)on the tangential grinding force were investigated through the processing of lithium niobate crystals using an intelligent precision-grinding system.The experimental results indicated that the relative error between the predicted and experimental values was 10.74%,thereby confirming the accuracy of the grinding force model.This study advances the understanding of elastohydrodynamic lubrication mechanisms in abrasive machining and provides a crucial theoretical foundation for the application of flexible ball-end BAAT.展开更多
The composite material layering process has attracted considerable attention due to its production advantages,including high scalability and compatibility with a wide range of raw materials.However,changes in process ...The composite material layering process has attracted considerable attention due to its production advantages,including high scalability and compatibility with a wide range of raw materials.However,changes in process conditions can lead to degradation in layer quality and non-uniformity,highlighting the need for real-time monitoring to improve overall quality and efficiency.In this study,an AI-based monitoring system was developed to evaluate layer width and assess quality in real time.Three deep learning models Faster Region-based Convolutional Neural Network(R-CNN),You Only Look Once version 8(YOLOv8),and Single Shot MultiBox Detector(SSD)were compared,and YOLOv8 was ultimately selected for its superior speed,flexibility,and scalability.The selected model was integrated into a user-friendly interface.To verify the reliability of the system,bead width control experiments were conducted,which identified feed speed and extrusion speed as the key process parameters.Accordingly,a Central Composite Design(CCD)experimental plan with 13 conditions was applied to evaluate layer width and validate the system’s reliability.Finally,the proposed system was applied to the additive manufacturing of an aerospace component,where it successfully detected bead width deviations during printing and enabled stable fabrication with a maximum geometric deviation of approximately 6 mm.These findings demonstrate the critical role of real-time monitoring of layer width and quality in improving process stability and final product quality in composite material additive manufacturing.展开更多
Modern manufacturing processes have become more reliant on automation because of the accelerated transition from Industry 3.0 to Industry 4.0.Manual inspection of products on assembly lines remains inefficient,prone t...Modern manufacturing processes have become more reliant on automation because of the accelerated transition from Industry 3.0 to Industry 4.0.Manual inspection of products on assembly lines remains inefficient,prone to errors and lacks consistency,emphasizing the need for a reliable and automated inspection system.Leveraging both object detection and image segmentation approaches,this research proposes a vision-based solution for the detection of various kinds of tools in the toolkit using deep learning(DL)models.Two Intel RealSense D455f depth cameras were arranged in a top down configuration to capture both RGB and depth images of the toolkits.After applying multiple constraints and enhancing them through preprocessing and augmentation,a dataset consisting of 3300 annotated RGB-D photos was generated.Several DL models were selected through a comprehensive assessment of mean Average Precision(mAP),precision-recall equilibrium,inference latency(target≥30 FPS),and computational burden,resulting in a preference for YOLO and Region-based Convolutional Neural Networks(R-CNN)variants over ViT-based models due to the latter’s increased latency and resource requirements.YOLOV5,YOLOV8,YOLOV11,Faster R-CNN,and Mask R-CNN were trained on the annotated dataset and evaluated using key performance metrics(Recall,Accuracy,F1-score,and Precision).YOLOV11 demonstrated balanced excellence with 93.0%precision,89.9%recall,and a 90.6%F1-score in object detection,as well as 96.9%precision,95.3%recall,and a 96.5%F1-score in instance segmentation with an average inference time of 25 ms per frame(≈40 FPS),demonstrating real-time performance.Leveraging these results,a YOLOV11-based windows application was successfully deployed in a real-time assembly line environment,where it accurately processed live video streams to detect and segment tools within toolkits,demonstrating its practical effectiveness in industrial automation.The application is capable of precisely measuring socket dimensions by utilising edge detection techniques on YOLOv11 segmentation masks,in addition to detection and segmentation.This makes it possible to do specification-level quality control right on the assembly line,which improves the ability to examine things in real time.The implementation is a big step forward for intelligent manufacturing in the Industry 4.0 paradigm.It provides a scalable,efficient,and accurate way to do automated inspection and dimensional verification activities.展开更多
In the context of large language model(LLM)reshaping software engineering education,this paper presents OSSerCopilot,a LLM-based tutoring system designed to address the critical challenge faced by newcomers(especially...In the context of large language model(LLM)reshaping software engineering education,this paper presents OSSerCopilot,a LLM-based tutoring system designed to address the critical challenge faced by newcomers(especially student contributors)in open source software(OSS)communities.Leveraging natural language processing,code semantic understanding,and learner profiling,the system functions as an intelligent tutor to scaffold three core competency domains:contribution guideline interpretation,project architecture comprehension,and personalized task matching.By transforming traditional onboarding barriers-such as complex contribution documentation and opaque project structures-into interactive learning journeys,OSSerCopilot enables newcomers to complete their first OSS contribution more easily and confidently.This paper highlights how LLM technologies can redefine software engineering education by bridging the gap between theoretical knowledge and practical OSS participation,offering implications for curriculum design,competency assessment,and sustainable OSS ecosystem cultivation.A demonstration video of the system is available at https://figshare.com/articles/media/OSSerCopilot_Introduction_mp4/29510276.展开更多
Based on the theory of elastic mechanics and material mechanics, the orientation precision of the hohl schaft kegel（HSK） tooling system in static and dynamic states is theoretically and experimentally studied. The r...Based on the theory of elastic mechanics and material mechanics, the orientation precision of the hohl schaft kegel（HSK） tooling system in static and dynamic states is theoretically and experimentally studied. The relation between the clamping force and the shank taper is obtained. And a proper clamping force is found to be essential to assure the axial and radial orientation precisions of the HSK tooling system in high speed machining （HSM）. Analytical results show that the reason why the HSK tooling system can keep high precision at the high rotational speed is that the actual axial clamping force keeps the two surfaces of the shank and the spindle in contact all the time.展开更多
The principle and the constitution of an intelligent system for on-line and real-time montitoring tool cutting state were discussed and a synthetic sensors schedule combined a new type fluid acoustic emission sens...The principle and the constitution of an intelligent system for on-line and real-time montitoring tool cutting state were discussed and a synthetic sensors schedule combined a new type fluid acoustic emission sensor (AE) with motor current sensor was presented. The parallel communication between control system of machine tools, the monitoring intelligent system,and several decision-making systems for identifying tool cutting state was established It can auto - matically select the sensor way ,monitoring mode and identifying method in machining process- ing so as to build a successful and effective intelligent system for on -line and real-time moni- toring cutting tool states in FMS.展开更多
The necessity and feasibility of an expert system for carbide-tool utilization are analyzed and a practical system named CUES(carbide-tool utilization expert system ) is developed and realized. The system concept, mod...The necessity and feasibility of an expert system for carbide-tool utilization are analyzed and a practical system named CUES(carbide-tool utilization expert system ) is developed and realized. The system concept, module structure, data management, inference strategy and the interface design of the system are discussed in.detail. The system would be useful not only for the preparation of tool bank of FMS or CIMS, but the for the proper application of cemented carbide tools in conventional machining Processes.展开更多
Reliable on line cutting tool conditioning monitoring is an essential feature of automatic machine tool and flexible manufacturing system (FMS) and computer integrated manufacturing system (CIMS). Recently artificia...Reliable on line cutting tool conditioning monitoring is an essential feature of automatic machine tool and flexible manufacturing system (FMS) and computer integrated manufacturing system (CIMS). Recently artificial neural networks (ANNs) are used for this purpose in conjunction with suitable sensory systems. The present work in Norwegian University of Science and Technology (NTNU) uses back propagation neural networks (BP) and fuzzy neural networks (FNN) to process the cutting tool state data measured with force and acoustic emission (AE) sensors, and implements a valuable on line tool condition monitoring system using the ANNs. Different ANN structures are designed and investigated to estimate the tool wear state based on the fusion of acoustic emission and force signals. Finally, four case studies are introduced for the sensing and ANN processing of the tool wear states and the failures of the tool with practical experiment examples. The results indicate that a tool wear identification system can be achieved using the sensors integration with ANNs, and that ANNs provide a very effective method of implementing sensor integration for on line monitoring of tool wear states and abnormalities.展开更多
According to the structure of the hohl schaft kegel（HSK） tooling system and its working principle, a mechanical model of the HSK tooling system is established. Major factors influencing the stiffness of the system a...According to the structure of the hohl schaft kegel（HSK） tooling system and its working principle, a mechanical model of the HSK tooling system is established. Major factors influencing the stiffness of the system are analyzed and the relationship between the load and the manufacturing quality is obtained. The basic rule of the stiffness variation is presented and the theoretical analysis is in a good agreement with experimental results. The dynamic stiffness must also be considered to evaluate the performance of the tooling system besides the staticstiffness. Finally, the selecting principles of the HSK types are proposed and their optimum operating conditions are established.展开更多
This paper describes a technology of dynamic display moving image by computer monitor,which is initially used in the design of tool detection system. The paper presents the hardware and software principie and edge det...This paper describes a technology of dynamic display moving image by computer monitor,which is initially used in the design of tool detection system. The paper presents the hardware and software principie and edge detection process. The way of marking edge point coordinates and stability of moving image also is analyzed. The method reforms the conventional design of the 2-D vision detection system. Moreover,it facilitates the design of the systematic mechanical construction,is convenient to compile instrument systemsoftware,and realizes to detect and track display image simultaneously. By the work,the tool detection system is improved to practical application.展开更多
In this paper, eddy current sensors and thermocouple sensors were employed to measure the thermal field and thermal deformation of a spindle of a telescopic CNC boring-milling machine tool, respectively. A linear regr...In this paper, eddy current sensors and thermocouple sensors were employed to measure the thermal field and thermal deformation of a spindle of a telescopic CNC boring-milling machine tool, respectively. A linear regression method was proposed to establish the thermal error model. Furthermore, two compensation methods were implemented based on the SIEMENS 840D system by using the feed shaft of z direction and telescopic spindle respectively. Experimental results showed that the thermal error could be reduced by 73.79% when using the second compensation method, and the thermal error could be eliminated by using the two compensation methods effectively.展开更多
Remote monitoring of tools for prediction of tool wear in cutting processes was considered, and a method of implementation of a remote-monitoring system previously developed was proposed. Sensor signals were received ...Remote monitoring of tools for prediction of tool wear in cutting processes was considered, and a method of implementation of a remote-monitoring system previously developed was proposed. Sensor signals were received and tool wear was predicted in the local system using an ART2 algorithm, while the monitoring result was transferred to the remote system via intemet. The monitoring system was installed at an on-site machine tool for monitoring three kinds of tools cutting titanium alloys, and the tool wear was evaluated on the basis of vigilances, similarities between vibration signals received and the normal patterns previously trained. A number of experiments were carried out to evaluate the performance of the proposed system, and the results show that the wears of finishing-cut tools are successfully detected when the moving average vigilance becomes lower than the critical vigilance, thus the appropriate tool replacement time is notified before the breakage.展开更多
AIM:To develop a tool to more explicitly assess and document the quality of systematic reviews.METHODS:We developed the Documentation and Appraisal Review Tool(DART)using epidemiologic principles of study design and t...AIM:To develop a tool to more explicitly assess and document the quality of systematic reviews.METHODS:We developed the Documentation and Appraisal Review Tool(DART)using epidemiologic principles of study design and the following resources:the modified Overview Quality Assessment Questionnaire(modified OQAQ),Assessment of Multiple Systematic Reviews(AMSTAR),the Cochrane Handbook,and the standards promoted by the Agency for Healthcare Research and Quality,and the Institutes of Medicine(IOM).We designed the DART tool to include the following:more detail to provide guidance and improve standardization of use,an approach to assess quality of systematic reviews addressing a variety of research designs,and additional space for recording notes to facilitate recall.DART underwent multiple rounds of testing with methodologists of varying levels of training and experience.Based on the results of six phases of pilot testing,we revised DART to improve performance,clarity and consistency.Pilot testing also included comparisons between DART,and the two most commonly used tools to evaluate the quality of systematic reviews,the modified OQAQ and AMSTAR.RESULTS:Compared to AMSTAR and modified OQAQ,DART includes two unique questions and several questions covered by modified OQAQ or AMSTAR but not both.Modified OQAQ and DART had the highest reporting consistency.Four AMSTAR questions were unclear and elicited inconsistent responses.Identifying reviewer rationale was most difficult using the modified OQAQ tool,and easiest using DART.DART allowsfor documentation of reviewer rationale,facilitating reconciliation between reviewers and documentation for future updates.DART also provides a comprehensive,systematic approach for reviewers with limited experience with systematic review methodology,to critically analyze systematic reviews.In addition,DART is the only one of the three tools to explicitly include quality review for biases specific to observational studies.This is now more widely recognized as important for assessing risk in order to generate recommendations that balance benefit to harm.The tool also includes the assessment of standards recommended by the March 2011 IOM Standards for Systematic Review.CONCLUSION:This comprehensive tool improves upon existing tools for assessing the quality of systematic reviews and guides reviewers through critically analyzing a systematic review.展开更多
The core of computer numerical control(CNC) machine tool is the electrical system which controls and coordinates every part of CNC machine tool to complete processing tasks, so it is of great significance to strengthe...The core of computer numerical control(CNC) machine tool is the electrical system which controls and coordinates every part of CNC machine tool to complete processing tasks, so it is of great significance to strengthen the reliability of the electrical system. However, the electrical system is very complex due to many uncertain factors and dynamic stochastic characteristics when failure occurs. Therefore, the traditional fault tree analysis(FTA) method is not applicable. Bayesian network(BN) not only has a unique advantage to analyze nodes with multiply states in reliability analysis for complex systems, but also can solve the state explosion problem properly caused by Markov model when dealing with dynamic fault tree(DFT). In addition, the forward causal reasoning of BN can get the conditional probability distribution of the system under considering the uncertainty;the backward diagnosis reasoning of BN can recognize the weak links in system, so it is valuable for improving the system reliability.展开更多
基金Project(51175122)supported by the National Natural Science Foundation of China
文摘The aim of this work is to simulate thermal deformation of tool system and investigate the influence of cutting parameters on it in single-point diamond turning(SPDT) of aluminum alloy. The experiments with various cutting parameters were conducted. Cutting temperature was measured by FLIR A315 infrared thermal imager. Tool wear was measured by scanning electron microscope(SEM). The numerical model of heat flux considering tool wear generated in cutting zone was established. Then two-step finite element method(FEM) simulations matching the experimental conditions were carried out to simulate the thermal deformation. In addition, the tests of deformation of tool system were performed to verify previous simulation results. And then the influence of cutting parameters on thermal deformation was investigated. The results show that the temperature and thermal deformation from simulations agree well with the results from experiments in the same conditions. The maximum thermal deformation of tool reaches to 7 μm. The average flank wear width and cutting speed are the dominant factors affecting thermal deformation, and the effective way to decrease the thermal deformation of tool is to control the tool wear and the cutting speed.
文摘In conformity with the principle of Design for Manufacture,feature-based design strate- (?)es have been developed.As the“feature”is relevant to the“macro process plan”and“macro NC programs”,obviously,“feature”is beyond the power of conventional solid modellers.Neverthe- less,substantial breakthrough has not been made in the solid modeling field,except“feature at- taching”or“feature recognizing”methods have been taken on.In this paper,the theory, concepts,system architecture,and algorithm principles of solid modeling tool system have been represented.The practice of Feature Solid Modeling Tool System (FSMTS) developed at Huazhong University has proved that the tool may be a new foundation of Feature-Based Design.
文摘Dispatching optimally FMS tool system can utilize efficiently FMS automated tool provide system and raise flexibility of FMS. Some dispatch problems to be solved on FMS tool system are put forward. The models discussed of FMS tool system are given, and the mathematic describes are made on the models. The concept of operation tool change set is posed, and a optimal objective function is recommended. The algorithm of operation tool change set is studied and given.The developed successfully tool management system proves the algorithm is effective.
文摘Objective:This study aimed to systematically evaluate the measurement characteristics and methodological quality of childbirth experience assessment tools,with a view to informing the selection of healthcare professionals who can provide high-quality assessment tools.Method:A systematic search was performed on specific databases:PubMed,Web of Science,Embase,CINAHL,SinoMed,China National Knowledge Infrastructure(CNKI),and Wanfang,from inception to February 29,2024.The researchers retrieved studies on the measurement attributes of the childbirth experience assessment tool,and traced back the references of the included studies to supplement relevant literature.According to the inclusion and exclusion criteria,screening and data extraction were independently undertaken by two reviewers.Two researchers individually used the Consensus-based Standards for the Selection of Health Measurement Instruments(COSMIN)Risk of Bias Checklist to assess the methodological quality of the scale,applied the COSMIN criteria to evaluate the measurement properties of the scale,and used a modified Grading of Recommendations,Assessment,Development,and Evaluation(GRADE)system to assess the certainty of evidence.Result:A total of 15 studies were included to evaluate the psychometric properties of 11 childbirth experience assessment tools(including different language versions).Eight studies’methodological quality of content validity was doubtful,and the remaining studies did not report content validity.None of the tools reported measurement error,cross-cultural validity,or responsiveness.In light of the questionable or unreported content validity of the tools,the evidence quality was deemed moderate or below.Consequently,the 11 assessment tools were recommended as grade B.Conclusion:In contrast,the Questionnaire for Assessing the Childbirth Experience(QACE)is recommended for provisional use,given its relatively good methodological and measurement attributes and appropriate content for evaluation.However,further validation of other measurement properties is needed.
基金supported by the project“Romanian Hub for Artificial Intelligence-HRIA”,Smart Growth,Digitization and Financial Instruments Program,2021–2027,MySMIS No.334906.
文摘Objective expertise evaluation of individuals,as a prerequisite stage for team formation,has been a long-term desideratum in large software development companies.With the rapid advancements in machine learning methods,based on reliable existing data stored in project management tools’datasets,automating this evaluation process becomes a natural step forward.In this context,our approach focuses on quantifying software developer expertise by using metadata from the task-tracking systems.For this,we mathematically formalize two categories of expertise:technology-specific expertise,which denotes the skills required for a particular technology,and general expertise,which encapsulates overall knowledge in the software industry.Afterward,we automatically classify the zones of expertise associated with each task a developer has worked on using Bidirectional Encoder Representations from Transformers(BERT)-like transformers to handle the unique characteristics of project tool datasets effectively.Finally,our method evaluates the proficiency of each software specialist across already completed projects from both technology-specific and general perspectives.The method was experimentally validated,yielding promising results.
基金Supported by National Key R&D Program of China(Grant No.2023YFE0203800)the National Natural Science Foundation of China(Grant No.52105482).
文摘Off-axis aspherical mirrors are widely used in optical systems and precision measuring instruments,whereas off-axis aspherical mirrors with large sizes and off-axis are used in large optical systems such as astronomical telescopes and radio telescopes.However,if the off-axis amount of an off-axis aspherical mirror exceeds the capability of the machine tool,traditional rotary-turning machining methods are not applicable,and advanced computerized numerical control(CNC)machining methods,such as the slow-tool-servo method,must be im-plemented.This article proposes a non-conventional offset(NCO)fabrication method based on slow-tool-servo single-point diamond turning for machining off-axis aspherical surfaces with large off-axis amounts.This method is theoretically applicable to the machining of off-axis aspherical surfaces with any off-axis amount.NCO fab-rication is a simpler and more efficient path-planning solution for machining individual off-axis parabolic sur-faces.In addition,corresponding solutions for other types of aspherical surfaces are proposed using the NCO method.The turning depths of workpieces with different off-axis amounts at the same machining position are analyzed and compared.A specific measurement scheme for the NCO method is presented,and the experimental results indicate that the PV and RMS form errors are 0.658μm and 60 nm,respectively.This work demonstrates that the NCO method can effectively deal with the machining challenges of off-axis aspherical structures with large off-axis amounts.
基金Supported by National Natural Science Foundation of China(Grant Nos.52575516,51875329)Taishan Scholar Special Foundation of Shandong Province(Grant Nos.tstp20240826,tsqn201812064)+2 种基金Shandong Provincial Natural Science Foundation(Grant No.ZR2023ME112)Key Research and Development Project of the Ningxia Hui Autonomous Region(Grant No.2024BEE02019)Innovation Capacity Improvement Programme for High-tech SMEs of Shandong Province(Grant Nos.2022TSGC1333,2022TSGC1261).
文摘The surfaces of brittle materials are susceptible to defects such as scratches,cracks,and chipping during con-ventional grinding processes,which significantly compromise surface quality and service performance.A flexible ball-end body-armor-like abrasive tool(BAAT)can effectively remove micro-convex peaks from the surfaces of brittle materials by employing a high tangential grinding force and a low normal grinding force,thereby achieving nano-level surface roughness and ultra-smooth mirror finishes.However,the surface contact me-chanism,pressure distribution pattern,and grinding force behavior between BAAT and workpiece remain in-adequately understood.This study examines the mechanism of liquid film formation and the distribution pattern of elastohydrodynamic pressure in high-shear and low-pressure grinding areas,drawing on the theories of elastohydrodynamic lubrication,non-Newtonian fluid dynamics,and material mechanics.A high-shear low-pressure grinding force model,which incorporates elastohydrodynamic liquid film thickness and abrasive grain size,was developed.The effects of the main grinding parameters(normal load,spindle rotational speed,and abrasive grain size)on the tangential grinding force were investigated through the processing of lithium niobate crystals using an intelligent precision-grinding system.The experimental results indicated that the relative error between the predicted and experimental values was 10.74%,thereby confirming the accuracy of the grinding force model.This study advances the understanding of elastohydrodynamic lubrication mechanisms in abrasive machining and provides a crucial theoretical foundation for the application of flexible ball-end BAAT.
基金support of the Korea Institute of Industrial Technol-ogy as“Development of a remote manufacturing system for high-risk,high-difficulty pipe production processes”(kitech EH-25-0004)supported by the Technology Innovation Program(or Industrial Strategic Technology Development Program)(RS-2023–00237714+2 种基金Development of Dynamic Metrology Tool for CMP Process StabilizationRS-2025–02634755Development of Real-Time Electrical Fire Prevention System Technology Reflecting the Characteristics of Traditional Markets)funded by the Ministry of Trade,Industry&Energy(MOTIE,Republic of Korea).
文摘The composite material layering process has attracted considerable attention due to its production advantages,including high scalability and compatibility with a wide range of raw materials.However,changes in process conditions can lead to degradation in layer quality and non-uniformity,highlighting the need for real-time monitoring to improve overall quality and efficiency.In this study,an AI-based monitoring system was developed to evaluate layer width and assess quality in real time.Three deep learning models Faster Region-based Convolutional Neural Network(R-CNN),You Only Look Once version 8(YOLOv8),and Single Shot MultiBox Detector(SSD)were compared,and YOLOv8 was ultimately selected for its superior speed,flexibility,and scalability.The selected model was integrated into a user-friendly interface.To verify the reliability of the system,bead width control experiments were conducted,which identified feed speed and extrusion speed as the key process parameters.Accordingly,a Central Composite Design(CCD)experimental plan with 13 conditions was applied to evaluate layer width and validate the system’s reliability.Finally,the proposed system was applied to the additive manufacturing of an aerospace component,where it successfully detected bead width deviations during printing and enabled stable fabrication with a maximum geometric deviation of approximately 6 mm.These findings demonstrate the critical role of real-time monitoring of layer width and quality in improving process stability and final product quality in composite material additive manufacturing.
文摘Modern manufacturing processes have become more reliant on automation because of the accelerated transition from Industry 3.0 to Industry 4.0.Manual inspection of products on assembly lines remains inefficient,prone to errors and lacks consistency,emphasizing the need for a reliable and automated inspection system.Leveraging both object detection and image segmentation approaches,this research proposes a vision-based solution for the detection of various kinds of tools in the toolkit using deep learning(DL)models.Two Intel RealSense D455f depth cameras were arranged in a top down configuration to capture both RGB and depth images of the toolkits.After applying multiple constraints and enhancing them through preprocessing and augmentation,a dataset consisting of 3300 annotated RGB-D photos was generated.Several DL models were selected through a comprehensive assessment of mean Average Precision(mAP),precision-recall equilibrium,inference latency(target≥30 FPS),and computational burden,resulting in a preference for YOLO and Region-based Convolutional Neural Networks(R-CNN)variants over ViT-based models due to the latter’s increased latency and resource requirements.YOLOV5,YOLOV8,YOLOV11,Faster R-CNN,and Mask R-CNN were trained on the annotated dataset and evaluated using key performance metrics(Recall,Accuracy,F1-score,and Precision).YOLOV11 demonstrated balanced excellence with 93.0%precision,89.9%recall,and a 90.6%F1-score in object detection,as well as 96.9%precision,95.3%recall,and a 96.5%F1-score in instance segmentation with an average inference time of 25 ms per frame(≈40 FPS),demonstrating real-time performance.Leveraging these results,a YOLOV11-based windows application was successfully deployed in a real-time assembly line environment,where it accurately processed live video streams to detect and segment tools within toolkits,demonstrating its practical effectiveness in industrial automation.The application is capable of precisely measuring socket dimensions by utilising edge detection techniques on YOLOv11 segmentation masks,in addition to detection and segmentation.This makes it possible to do specification-level quality control right on the assembly line,which improves the ability to examine things in real time.The implementation is a big step forward for intelligent manufacturing in the Industry 4.0 paradigm.It provides a scalable,efficient,and accurate way to do automated inspection and dimensional verification activities.
基金supported by the National Natural Science Foundation of China (62202022, 92582204, and 62572030)the Fundamental Research Funds for the Central Universitiesthe exploratory elective projects of the State Key Laboratory of Complex and Critical Software Environments
文摘In the context of large language model(LLM)reshaping software engineering education,this paper presents OSSerCopilot,a LLM-based tutoring system designed to address the critical challenge faced by newcomers(especially student contributors)in open source software(OSS)communities.Leveraging natural language processing,code semantic understanding,and learner profiling,the system functions as an intelligent tutor to scaffold three core competency domains:contribution guideline interpretation,project architecture comprehension,and personalized task matching.By transforming traditional onboarding barriers-such as complex contribution documentation and opaque project structures-into interactive learning journeys,OSSerCopilot enables newcomers to complete their first OSS contribution more easily and confidently.This paper highlights how LLM technologies can redefine software engineering education by bridging the gap between theoretical knowledge and practical OSS participation,offering implications for curriculum design,competency assessment,and sustainable OSS ecosystem cultivation.A demonstration video of the system is available at https://figshare.com/articles/media/OSSerCopilot_Introduction_mp4/29510276.
文摘Based on the theory of elastic mechanics and material mechanics, the orientation precision of the hohl schaft kegel（HSK） tooling system in static and dynamic states is theoretically and experimentally studied. The relation between the clamping force and the shank taper is obtained. And a proper clamping force is found to be essential to assure the axial and radial orientation precisions of the HSK tooling system in high speed machining （HSM）. Analytical results show that the reason why the HSK tooling system can keep high precision at the high rotational speed is that the actual axial clamping force keeps the two surfaces of the shank and the spindle in contact all the time.
文摘The principle and the constitution of an intelligent system for on-line and real-time montitoring tool cutting state were discussed and a synthetic sensors schedule combined a new type fluid acoustic emission sensor (AE) with motor current sensor was presented. The parallel communication between control system of machine tools, the monitoring intelligent system,and several decision-making systems for identifying tool cutting state was established It can auto - matically select the sensor way ,monitoring mode and identifying method in machining process- ing so as to build a successful and effective intelligent system for on -line and real-time moni- toring cutting tool states in FMS.
文摘The necessity and feasibility of an expert system for carbide-tool utilization are analyzed and a practical system named CUES(carbide-tool utilization expert system ) is developed and realized. The system concept, module structure, data management, inference strategy and the interface design of the system are discussed in.detail. The system would be useful not only for the preparation of tool bank of FMS or CIMS, but the for the proper application of cemented carbide tools in conventional machining Processes.
文摘Reliable on line cutting tool conditioning monitoring is an essential feature of automatic machine tool and flexible manufacturing system (FMS) and computer integrated manufacturing system (CIMS). Recently artificial neural networks (ANNs) are used for this purpose in conjunction with suitable sensory systems. The present work in Norwegian University of Science and Technology (NTNU) uses back propagation neural networks (BP) and fuzzy neural networks (FNN) to process the cutting tool state data measured with force and acoustic emission (AE) sensors, and implements a valuable on line tool condition monitoring system using the ANNs. Different ANN structures are designed and investigated to estimate the tool wear state based on the fusion of acoustic emission and force signals. Finally, four case studies are introduced for the sensing and ANN processing of the tool wear states and the failures of the tool with practical experiment examples. The results indicate that a tool wear identification system can be achieved using the sensors integration with ANNs, and that ANNs provide a very effective method of implementing sensor integration for on line monitoring of tool wear states and abnormalities.
文摘According to the structure of the hohl schaft kegel（HSK） tooling system and its working principle, a mechanical model of the HSK tooling system is established. Major factors influencing the stiffness of the system are analyzed and the relationship between the load and the manufacturing quality is obtained. The basic rule of the stiffness variation is presented and the theoretical analysis is in a good agreement with experimental results. The dynamic stiffness must also be considered to evaluate the performance of the tooling system besides the staticstiffness. Finally, the selecting principles of the HSK types are proposed and their optimum operating conditions are established.
文摘This paper describes a technology of dynamic display moving image by computer monitor,which is initially used in the design of tool detection system. The paper presents the hardware and software principie and edge detection process. The way of marking edge point coordinates and stability of moving image also is analyzed. The method reforms the conventional design of the 2-D vision detection system. Moreover,it facilitates the design of the systematic mechanical construction,is convenient to compile instrument systemsoftware,and realizes to detect and track display image simultaneously. By the work,the tool detection system is improved to practical application.
文摘In this paper, eddy current sensors and thermocouple sensors were employed to measure the thermal field and thermal deformation of a spindle of a telescopic CNC boring-milling machine tool, respectively. A linear regression method was proposed to establish the thermal error model. Furthermore, two compensation methods were implemented based on the SIEMENS 840D system by using the feed shaft of z direction and telescopic spindle respectively. Experimental results showed that the thermal error could be reduced by 73.79% when using the second compensation method, and the thermal error could be eliminated by using the two compensation methods effectively.
基金supported by Changwon National University in 2009-2010
文摘Remote monitoring of tools for prediction of tool wear in cutting processes was considered, and a method of implementation of a remote-monitoring system previously developed was proposed. Sensor signals were received and tool wear was predicted in the local system using an ART2 algorithm, while the monitoring result was transferred to the remote system via intemet. The monitoring system was installed at an on-site machine tool for monitoring three kinds of tools cutting titanium alloys, and the tool wear was evaluated on the basis of vigilances, similarities between vibration signals received and the normal patterns previously trained. A number of experiments were carried out to evaluate the performance of the proposed system, and the results show that the wears of finishing-cut tools are successfully detected when the moving average vigilance becomes lower than the critical vigilance, thus the appropriate tool replacement time is notified before the breakage.
文摘AIM:To develop a tool to more explicitly assess and document the quality of systematic reviews.METHODS:We developed the Documentation and Appraisal Review Tool(DART)using epidemiologic principles of study design and the following resources:the modified Overview Quality Assessment Questionnaire(modified OQAQ),Assessment of Multiple Systematic Reviews(AMSTAR),the Cochrane Handbook,and the standards promoted by the Agency for Healthcare Research and Quality,and the Institutes of Medicine(IOM).We designed the DART tool to include the following:more detail to provide guidance and improve standardization of use,an approach to assess quality of systematic reviews addressing a variety of research designs,and additional space for recording notes to facilitate recall.DART underwent multiple rounds of testing with methodologists of varying levels of training and experience.Based on the results of six phases of pilot testing,we revised DART to improve performance,clarity and consistency.Pilot testing also included comparisons between DART,and the two most commonly used tools to evaluate the quality of systematic reviews,the modified OQAQ and AMSTAR.RESULTS:Compared to AMSTAR and modified OQAQ,DART includes two unique questions and several questions covered by modified OQAQ or AMSTAR but not both.Modified OQAQ and DART had the highest reporting consistency.Four AMSTAR questions were unclear and elicited inconsistent responses.Identifying reviewer rationale was most difficult using the modified OQAQ tool,and easiest using DART.DART allowsfor documentation of reviewer rationale,facilitating reconciliation between reviewers and documentation for future updates.DART also provides a comprehensive,systematic approach for reviewers with limited experience with systematic review methodology,to critically analyze systematic reviews.In addition,DART is the only one of the three tools to explicitly include quality review for biases specific to observational studies.This is now more widely recognized as important for assessing risk in order to generate recommendations that balance benefit to harm.The tool also includes the assessment of standards recommended by the March 2011 IOM Standards for Systematic Review.CONCLUSION:This comprehensive tool improves upon existing tools for assessing the quality of systematic reviews and guides reviewers through critically analyzing a systematic review.
基金the National Science and Technology Major Project of China(No.2014ZX04014-011)
文摘The core of computer numerical control(CNC) machine tool is the electrical system which controls and coordinates every part of CNC machine tool to complete processing tasks, so it is of great significance to strengthen the reliability of the electrical system. However, the electrical system is very complex due to many uncertain factors and dynamic stochastic characteristics when failure occurs. Therefore, the traditional fault tree analysis(FTA) method is not applicable. Bayesian network(BN) not only has a unique advantage to analyze nodes with multiply states in reliability analysis for complex systems, but also can solve the state explosion problem properly caused by Markov model when dealing with dynamic fault tree(DFT). In addition, the forward causal reasoning of BN can get the conditional probability distribution of the system under considering the uncertainty;the backward diagnosis reasoning of BN can recognize the weak links in system, so it is valuable for improving the system reliability.
