Pub Date : 2023-05-04DOI: 10.48550/arXiv.2305.03063
D. Onchis, Gilbert-Rainer Gillich, Eduard Hogea, Cristian Tufisi
In the last decade, damage detection approaches swiftly changed from advanced signal processing methods to machine learning and especially deep learning models, to accurately and non-intrusively estimate the state of the beam structures. But as the deep learning models reached their peak performances, also their limitations in applicability and vulnerabilities were observed. One of the most important reason for the lack of trustworthiness in operational conditions is the absence of intrinsic explainability of the deep learning system, due to the encoding of the knowledge in tensor values and without the inclusion of logical constraints. In this paper, we propose a neuro-symbolic model for the detection of damages in cantilever beams based on a novel cognitive architecture in which we join the processing power of convolutional networks with the interactive control offered by queries realized through the inclusion of real logic directly into the model. The hybrid discriminative model is introduced under the name Logic Convolutional Neural Regressor and it is tested on a dataset of values of the relative natural frequency shifts of cantilever beams derived from an original mathematical relation. While the obtained results preserve all the predictive capabilities of deep learning models, the usage of three distances as predicates for satisfiability, makes the system more trustworthy and scalable for practical applications. Extensive numerical and laboratory experiments were performed, and they all demonstrated the superiority of the hybrid approach, which can open a new path for solving the damage detection problem.
{"title":"Neuro-symbolic model for cantilever beams damage detection","authors":"D. Onchis, Gilbert-Rainer Gillich, Eduard Hogea, Cristian Tufisi","doi":"10.48550/arXiv.2305.03063","DOIUrl":"https://doi.org/10.48550/arXiv.2305.03063","url":null,"abstract":"In the last decade, damage detection approaches swiftly changed from advanced signal processing methods to machine learning and especially deep learning models, to accurately and non-intrusively estimate the state of the beam structures. But as the deep learning models reached their peak performances, also their limitations in applicability and vulnerabilities were observed. One of the most important reason for the lack of trustworthiness in operational conditions is the absence of intrinsic explainability of the deep learning system, due to the encoding of the knowledge in tensor values and without the inclusion of logical constraints. In this paper, we propose a neuro-symbolic model for the detection of damages in cantilever beams based on a novel cognitive architecture in which we join the processing power of convolutional networks with the interactive control offered by queries realized through the inclusion of real logic directly into the model. The hybrid discriminative model is introduced under the name Logic Convolutional Neural Regressor and it is tested on a dataset of values of the relative natural frequency shifts of cantilever beams derived from an original mathematical relation. While the obtained results preserve all the predictive capabilities of deep learning models, the usage of three distances as predicates for satisfiability, makes the system more trustworthy and scalable for practical applications. Extensive numerical and laboratory experiments were performed, and they all demonstrated the superiority of the hybrid approach, which can open a new path for solving the damage detection problem.","PeriodicalId":10628,"journal":{"name":"Comput. Ind.","volume":"10 1","pages":"103991"},"PeriodicalIF":0.0,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74124304","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}
Dong‐Joon Lim, Sangjin Kim, U. Hwang, Sang-Ho Jeong, Dongwook Kim, Yeolib Kim
{"title":"Development of a virtual metrology system for smart manufacturing: A case study of spandex fiber production","authors":"Dong‐Joon Lim, Sangjin Kim, U. Hwang, Sang-Ho Jeong, Dongwook Kim, Yeolib Kim","doi":"10.2139/ssrn.4124529","DOIUrl":"https://doi.org/10.2139/ssrn.4124529","url":null,"abstract":"","PeriodicalId":10628,"journal":{"name":"Comput. Ind.","volume":"24 1","pages":"103825"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77487373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-01DOI: 10.1016/j.compind.2022.103659
Jianpeng Cao, David F. Bucher, D. Hall, Mike Eggers
{"title":"A graph-based approach for module library development in industrialized construction","authors":"Jianpeng Cao, David F. Bucher, D. Hall, Mike Eggers","doi":"10.1016/j.compind.2022.103659","DOIUrl":"https://doi.org/10.1016/j.compind.2022.103659","url":null,"abstract":"","PeriodicalId":10628,"journal":{"name":"Comput. Ind.","volume":"1 1","pages":"103659"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73108757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-01DOI: 10.1016/j.compind.2022.103665
Jinwon Lee, Changmo Yeo, Hyotae Kim, D. Mun
{"title":"Deep learning-based digitalization of a part catalog book to generate part specification by a neutral reference data dictionary","authors":"Jinwon Lee, Changmo Yeo, Hyotae Kim, D. Mun","doi":"10.1016/j.compind.2022.103665","DOIUrl":"https://doi.org/10.1016/j.compind.2022.103665","url":null,"abstract":"","PeriodicalId":10628,"journal":{"name":"Comput. Ind.","volume":"37 1","pages":"103665"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82540068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-01DOI: 10.1016/j.compind.2022.103644
M. Abdel-Baset, Victor Chang, Abduallah Gamal
{"title":"Retraction Notice to: \"Evaluation of the green supply chain management practices: A novel neutrosophic approach\" [Computers in Industry. Vol. 108 C (2019) pp 210-220]","authors":"M. Abdel-Baset, Victor Chang, Abduallah Gamal","doi":"10.1016/j.compind.2022.103644","DOIUrl":"https://doi.org/10.1016/j.compind.2022.103644","url":null,"abstract":"","PeriodicalId":10628,"journal":{"name":"Comput. Ind.","volume":"1 1","pages":"103644"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89963620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-01DOI: 10.1016/j.compind.2022.103664
Dayi Zhang, William Jackson, G. Dobie, G. West, C. Macleod
{"title":"Structure-from-motion based image unwrapping and stitching for small bore pipe inspections","authors":"Dayi Zhang, William Jackson, G. Dobie, G. West, C. Macleod","doi":"10.1016/j.compind.2022.103664","DOIUrl":"https://doi.org/10.1016/j.compind.2022.103664","url":null,"abstract":"","PeriodicalId":10628,"journal":{"name":"Comput. Ind.","volume":"277 1","pages":"103664"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72873039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-01DOI: 10.1016/j.compind.2022.103641
M. Abdel-Baset, Victor Chang, Abduallah Gamal, F. Smarandache
{"title":"Retraction Notice to An integrated neutrosophic ANP and VIKOR method for achieving sustainable supplier selection: A case study in importing field [Comput. Ind., vol. 106C (2019) pp. 94-110]","authors":"M. Abdel-Baset, Victor Chang, Abduallah Gamal, F. Smarandache","doi":"10.1016/j.compind.2022.103641","DOIUrl":"https://doi.org/10.1016/j.compind.2022.103641","url":null,"abstract":"","PeriodicalId":10628,"journal":{"name":"Comput. Ind.","volume":"71 1 1","pages":"103641"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77454061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-01DOI: 10.1016/j.compind.2021.103592
E. Kulcsár, I. Gyurika, Tamás Csiszér
{"title":"Network-based - Quality Function Deployment (NB-QFD): The combination of traditional QFD with network science approach and techniques","authors":"E. Kulcsár, I. Gyurika, Tamás Csiszér","doi":"10.1016/j.compind.2021.103592","DOIUrl":"https://doi.org/10.1016/j.compind.2021.103592","url":null,"abstract":"","PeriodicalId":10628,"journal":{"name":"Comput. Ind.","volume":"10 1","pages":"103592"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88570839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-01DOI: 10.1016/j.compind.2021.103594
Yishuo Jiang, Ming Li, Daqiang Guo, Wei Wu, R. Zhong, G. Huang
{"title":"Digital twin-enabled smart modular integrated construction system for on-site assembly","authors":"Yishuo Jiang, Ming Li, Daqiang Guo, Wei Wu, R. Zhong, G. Huang","doi":"10.1016/j.compind.2021.103594","DOIUrl":"https://doi.org/10.1016/j.compind.2021.103594","url":null,"abstract":"","PeriodicalId":10628,"journal":{"name":"Comput. Ind.","volume":"145 1","pages":"103594"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83079011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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