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International Journal of Mechatronics and Manufacturing Systems最新文献

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Thermo-fluid dynamics modelling of conformal cooling channels produced with material jetting technology 用材料喷射技术制造的共形冷却通道的热流体动力学建模
International Journal of Mechatronics and Manufacturing Systems Pub Date : 2023-01-01 DOI: 10.1504/ijmms.2023.133399
E.B. Arrivabeni, M.C. Barbato, L. Giorleo
{"title":"Thermo-fluid dynamics modelling of conformal cooling channels produced with material jetting technology","authors":"E.B. Arrivabeni, M.C. Barbato, L. Giorleo","doi":"10.1504/ijmms.2023.133399","DOIUrl":"https://doi.org/10.1504/ijmms.2023.133399","url":null,"abstract":"Material Jetting is an additive manufacturing technology that uses photopolymerisation reaction to produce parts with high accuracy and low roughness. Moreover, because the support material is easily removed by thermal treatment, it results as an additive process able to guarantee very high level of shape complexity. Nowadays, thanks to new commercial polymers able to withstand higher temperatures, this technology starts to find applications in the production of insert mould for injection moulding process. The authors present a study about the thermo-fluid dynamics behaviour of samples of inserts mould having conformal cooling channels. The mould heat transfer performances were tested via experimental and numerical techniques. Results suggest that for the prediction of the transient thermal behaviour of these new polymers, it is quite important the accurate evaluation of material thermal properties. For the design based on numerical approaches, challenges could arise from the wide range of variations found on thermal properties.","PeriodicalId":39429,"journal":{"name":"International Journal of Mechatronics and Manufacturing Systems","volume":"270 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135495529","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
A review on in-situ process sensing and monitoring systems for fusion-based additive manufacturing 基于融合的增材制造原位过程传感与监控系统研究进展
International Journal of Mechatronics and Manufacturing Systems Pub Date : 2023-01-01 DOI: 10.1504/ijmms.2023.133390
Tuğrul Özel
{"title":"A review on in-situ process sensing and monitoring systems for fusion-based additive manufacturing","authors":"Tuğrul Özel","doi":"10.1504/ijmms.2023.133390","DOIUrl":"https://doi.org/10.1504/ijmms.2023.133390","url":null,"abstract":"In additive manufacturing (AM), parts suffer from quality variations, defects, intricate surface topography, and anisotropy in properties that are known to be influenced by factors including process parameters, layerwise processing, and powder melting and fusion. Their influence on process signatures also makes AM processes not fully manageable creating unacceptable levels of inconsistency. To detect the fusion quality with a purpose of quality predictions, in-situ process sensing and monitoring with sensors is often utilised with the goal that AM process can be controlled for consistency in quality. This paper provides a review of the literature on in-situ process sensing and monitoring methods and discusses research challenges and future directions for further efforts. Currently, sensory data is used for data analysis and making mostly off-line quality quantifications and predictions. The future goal is to develop intelligent AM systems that use in-situ process data for making automated intervention and quality control decisions.","PeriodicalId":39429,"journal":{"name":"International Journal of Mechatronics and Manufacturing Systems","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135495536","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
A Review from Physics Based Models to Artificial Intelligence Aided Models in Fatigue Prediction for Industry Applications 从基于物理的模型到人工智能辅助模型在工业疲劳预测中的应用综述
International Journal of Mechatronics and Manufacturing Systems Pub Date : 2023-01-01 DOI: 10.1504/ijmms.2023.10058393
E. Bahceci, Mete Bakir, Muge Gurgen, H. O. Unver
{"title":"A Review from Physics Based Models to Artificial Intelligence Aided Models in Fatigue Prediction for Industry Applications","authors":"E. Bahceci, Mete Bakir, Muge Gurgen, H. O. Unver","doi":"10.1504/ijmms.2023.10058393","DOIUrl":"https://doi.org/10.1504/ijmms.2023.10058393","url":null,"abstract":"","PeriodicalId":39429,"journal":{"name":"International Journal of Mechatronics and Manufacturing Systems","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66753959","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
Molten pool temperature monitoring in laser metal deposition: comparison between single wavelength and ratio pyrometry techniques 激光金属沉积熔池温度监测:单波长和比热法技术的比较
International Journal of Mechatronics and Manufacturing Systems Pub Date : 2023-01-01 DOI: 10.1504/ijmms.2023.132027
Simone Maffia, V. Furlan, B. Previtali
{"title":"Molten pool temperature monitoring in laser metal deposition: comparison between single wavelength and ratio pyrometry techniques","authors":"Simone Maffia, V. Furlan, B. Previtali","doi":"10.1504/ijmms.2023.132027","DOIUrl":"https://doi.org/10.1504/ijmms.2023.132027","url":null,"abstract":"","PeriodicalId":39429,"journal":{"name":"International Journal of Mechatronics and Manufacturing Systems","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66753986","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: 1
On predicting machined part accuracy from CNC machine errors using artificial neural networks 利用人工神经网络从数控机床误差预测加工零件精度
International Journal of Mechatronics and Manufacturing Systems Pub Date : 2023-01-01 DOI: 10.1504/ijmms.2023.133394
Marios Christos Koutsogiannis, George Christopher Vosniakos
{"title":"On predicting machined part accuracy from CNC machine errors using artificial neural networks","authors":"Marios Christos Koutsogiannis, George Christopher Vosniakos","doi":"10.1504/ijmms.2023.133394","DOIUrl":"https://doi.org/10.1504/ijmms.2023.133394","url":null,"abstract":"","PeriodicalId":39429,"journal":{"name":"International Journal of Mechatronics and Manufacturing Systems","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135495722","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
Improving geometric accuracy in incremental sheet metal forming using convolutional neural networks 利用卷积神经网络提高增量钣金成形的几何精度
International Journal of Mechatronics and Manufacturing Systems Pub Date : 2023-01-01 DOI: 10.1504/ijmms.2023.133393
Darren Wei Wen Low, Chaudhari Akshay, Suwat Jirathearanat, A. Senthil Kumar
{"title":"Improving geometric accuracy in incremental sheet metal forming using convolutional neural networks","authors":"Darren Wei Wen Low, Chaudhari Akshay, Suwat Jirathearanat, A. Senthil Kumar","doi":"10.1504/ijmms.2023.133393","DOIUrl":"https://doi.org/10.1504/ijmms.2023.133393","url":null,"abstract":"Single point incremental forming (SPIF) is a flexible sheet metal forming process. Unlike sheet metal stamping, SPIF does away with costly forming dies but instead uses a tool to incrementally form the sheet into the desired geometry. However, a key weakness of SPIF is its poor geometric accuracy, which is largely caused by material spring-back throughout the forming process. This paper presents a framework which minimises SPIF geometric error through optimisation of the forming toolpath. The approach utilises a trained convolutional neural network (CNN) to model the forming process, which provides greater flexibility and compatibility with a wide range of geometry. A geometric compensation algorithm was developed to compensate for the predicted spring-back. Experimental validation of the proposed framework demonstrated consistent accuracy improvements in both trained and untrained geometry. This paper highlights the viability of using CNNs in improving SPIF accuracy.","PeriodicalId":39429,"journal":{"name":"International Journal of Mechatronics and Manufacturing Systems","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135495317","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
On predicting machined part accuracy from CNC machine errors using Artificial Neural Networks 利用人工神经网络从数控机床误差预测加工零件精度
International Journal of Mechatronics and Manufacturing Systems Pub Date : 2023-01-01 DOI: 10.1504/ijmms.2023.10057692
G. Vosniakos, Marios Christos Koutsogiannis
{"title":"On predicting machined part accuracy from CNC machine errors using Artificial Neural Networks","authors":"G. Vosniakos, Marios Christos Koutsogiannis","doi":"10.1504/ijmms.2023.10057692","DOIUrl":"https://doi.org/10.1504/ijmms.2023.10057692","url":null,"abstract":"","PeriodicalId":39429,"journal":{"name":"International Journal of Mechatronics and Manufacturing Systems","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66753786","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
Deep learning for defect identification in 3-D printing with fused filament fabrication 基于深度学习的熔丝3d打印缺陷识别
International Journal of Mechatronics and Manufacturing Systems Pub Date : 2023-01-01 DOI: 10.1504/ijmms.2023.10057693
Shreyas Aniyambeth, Deepak Malekar, T. Ozel
{"title":"Deep learning for defect identification in 3-D printing with fused filament fabrication","authors":"Shreyas Aniyambeth, Deepak Malekar, T. Ozel","doi":"10.1504/ijmms.2023.10057693","DOIUrl":"https://doi.org/10.1504/ijmms.2023.10057693","url":null,"abstract":"","PeriodicalId":39429,"journal":{"name":"International Journal of Mechatronics and Manufacturing Systems","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66753845","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
Neural network as approach for detection of non-compliant semi-finished Additive Manufactured parts 基于神经网络的增材制造半成品不合规检测方法
International Journal of Mechatronics and Manufacturing Systems Pub Date : 2023-01-01 DOI: 10.1504/ijmms.2023.10057694
M. Quarto, G. D’Urso
{"title":"Neural network as approach for detection of non-compliant semi-finished Additive Manufactured parts","authors":"M. Quarto, G. D’Urso","doi":"10.1504/ijmms.2023.10057694","DOIUrl":"https://doi.org/10.1504/ijmms.2023.10057694","url":null,"abstract":"","PeriodicalId":39429,"journal":{"name":"International Journal of Mechatronics and Manufacturing Systems","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66753902","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
Improving geometric accuracy in incremental sheet metal forming using convolutional neural networks 利用卷积神经网络提高增量钣金成形的几何精度
International Journal of Mechatronics and Manufacturing Systems Pub Date : 2023-01-01 DOI: 10.1504/ijmms.2023.10057691
S. Jirathearanat, A. Chaudhari, Darren Wei Wen Low, S. A
{"title":"Improving geometric accuracy in incremental sheet metal forming using convolutional neural networks","authors":"S. Jirathearanat, A. Chaudhari, Darren Wei Wen Low, S. A","doi":"10.1504/ijmms.2023.10057691","DOIUrl":"https://doi.org/10.1504/ijmms.2023.10057691","url":null,"abstract":"","PeriodicalId":39429,"journal":{"name":"International Journal of Mechatronics and Manufacturing Systems","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66754007","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
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