Pub Date : 2022-10-01DOI: 10.3850/978-981-11-2724-3_0688-cd
M. Leva, Lorenzo Comberti, M. Demichela, A. Caimo
{"title":"Human Performance in Manufacturing Tasks: Optimization and Assessment of required Workload and Capabilities","authors":"M. Leva, Lorenzo Comberti, M. Demichela, A. Caimo","doi":"10.3850/978-981-11-2724-3_0688-cd","DOIUrl":"https://doi.org/10.3850/978-981-11-2724-3_0688-cd","url":null,"abstract":"","PeriodicalId":342000,"journal":{"name":"Proceedings of the 29th European Safety and Reliability Conference (ESREL)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117338380","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 : 2020-03-09DOI: 10.3850/978-981-11-2724-3_0219-cd
Dejan Škanata
{"title":"Worst Case Risk","authors":"Dejan Škanata","doi":"10.3850/978-981-11-2724-3_0219-cd","DOIUrl":"https://doi.org/10.3850/978-981-11-2724-3_0219-cd","url":null,"abstract":"","PeriodicalId":342000,"journal":{"name":"Proceedings of the 29th European Safety and Reliability Conference (ESREL)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121559347","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 : 2019-09-26DOI: 10.3850/978-981-11-2724-3_0047-CD
M. Newall, C. Gulijk
{"title":"Real-Time Queries on Large Volumes of Safety Text","authors":"M. Newall, C. Gulijk","doi":"10.3850/978-981-11-2724-3_0047-CD","DOIUrl":"https://doi.org/10.3850/978-981-11-2724-3_0047-CD","url":null,"abstract":"","PeriodicalId":342000,"journal":{"name":"Proceedings of the 29th European Safety and Reliability Conference (ESREL)","volume":"208 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131656641","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 : 2019-09-26DOI: 10.3850/978-981-11-2724-3_0827-cd
Meng-Yun Zhao, Wang-Ji Chiachío, Yan Wei-Xin, W. Ren, M. Beer
The distributions of ratios of random variables arise in many applied problems such as in structural dynamics working with frequency response functions (FRFs) and transmissibility functions (TFs). When analysing the distribution properties of ratio random variables through the definition of probability density functions (PDF), the problem is usually accompanied by multiple integrals. In this study, a unified solution is presented to efficiently calculate the PDF of a ratio random variable with its denominator and numerator specified by arbitrary distributions. With the use of probability density transformation principle, a unified expression can be derived for the ratio random variable by reducing the concerned problem into two-dimensional integrals. As a result, the PDFs of the ratio random variable can be efficiently computed by using effective numerical integration techniques. Finally, based on the vibration tests performed on the Alamosa Canyon Bridge, the proposed method is applied to the data to quantify the uncertainty of FRFs and TFs.
{"title":"Probabilistic Modelling for Frequency Response Functions and Transmissibility Functions with Complex Ratio Statistics","authors":"Meng-Yun Zhao, Wang-Ji Chiachío, Yan Wei-Xin, W. Ren, M. Beer","doi":"10.3850/978-981-11-2724-3_0827-cd","DOIUrl":"https://doi.org/10.3850/978-981-11-2724-3_0827-cd","url":null,"abstract":"The distributions of ratios of random variables arise in many applied problems such as in structural dynamics working with frequency response functions (FRFs) and transmissibility functions (TFs). When analysing the distribution properties of ratio random variables through the definition of probability density functions (PDF), the problem is usually accompanied by multiple integrals. In this study, a unified solution is presented to efficiently calculate the PDF of a ratio random variable with its denominator and numerator specified by arbitrary distributions. With the use of probability density transformation principle, a unified expression can be derived for the ratio random variable by reducing the concerned problem into two-dimensional integrals. As a result, the PDFs of the ratio random variable can be efficiently computed by using effective numerical integration techniques. Finally, based on the vibration tests performed on the Alamosa Canyon Bridge, the proposed method is applied to the data to quantify the uncertainty of FRFs and TFs.","PeriodicalId":342000,"journal":{"name":"Proceedings of the 29th European Safety and Reliability Conference (ESREL)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117297467","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 : 2019-09-26DOI: 10.3850/978-981-11-2724-3_0914-cd
H. Zerrouki, Hector Diego Estrada-Lugo, H. Smadi, E. Patelli
{"title":"Applications of Bayesian Networks in Chemical and Process Industries: A Review","authors":"H. Zerrouki, Hector Diego Estrada-Lugo, H. Smadi, E. Patelli","doi":"10.3850/978-981-11-2724-3_0914-cd","DOIUrl":"https://doi.org/10.3850/978-981-11-2724-3_0914-cd","url":null,"abstract":"","PeriodicalId":342000,"journal":{"name":"Proceedings of the 29th European Safety and Reliability Conference (ESREL)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133592002","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 : 2019-09-26DOI: 10.3850/978-981-11-2724-3_0503-cd
Rui Li, W. Verhagen, R. Curran
Remaining useful life (RUL) prediction is crucial for the implementation of Prognostics and Health Management (PHM) systems, enabling application of predictive maintenance strategies for critical systems (e.g. in aviation, power, railway). Existing literature addresses aspects of data-driven prognostic approaches, with a predominant focus on introducing and testing various novel prediction techniques which are purposed towards improving prediction accuracy performance. However, a relative lack of research can be identified when considering a comparative evaluation of competing for data-driven approaches. In particular, the contributing process elements and characteristics of data-driven prognostics methods are typically not compared in detail. To overcome these drawbacks, this paper aims to evaluate the underlying technical processes for statistical and artificial neural networks (ANN) methods for prognostics. A case study is conducted to implement both approaches on the PHM08 Challenge Data Set for comparison. This research comprehensively compares the statistical and ANN prognostic methods in a systematic manner, covering and comparing their respective technical processes, and evaluates the results with respect to prediction accuracy
{"title":"Comparison of Data-driven Prognostics Models: A Process Perspective","authors":"Rui Li, W. Verhagen, R. Curran","doi":"10.3850/978-981-11-2724-3_0503-cd","DOIUrl":"https://doi.org/10.3850/978-981-11-2724-3_0503-cd","url":null,"abstract":"Remaining useful life (RUL) prediction is crucial for the implementation of Prognostics and Health Management (PHM) systems, enabling application of predictive maintenance strategies for critical systems (e.g. in aviation, power, railway). Existing literature addresses aspects of data-driven prognostic approaches, with a predominant focus on introducing and testing various novel prediction techniques which are purposed towards improving prediction accuracy performance. However, a relative lack of research can be identified when considering a comparative evaluation of competing for data-driven approaches. In particular, the contributing process elements and characteristics of data-driven prognostics methods are typically not compared in detail. To overcome these drawbacks, this paper aims to evaluate the underlying technical processes for statistical and artificial neural networks (ANN) methods for prognostics. A case study is conducted to implement both approaches on the PHM08 Challenge Data Set for comparison. This research comprehensively compares the statistical and ANN prognostic methods in a systematic manner, covering and comparing their respective technical processes, and evaluates the results with respect to prediction accuracy","PeriodicalId":342000,"journal":{"name":"Proceedings of the 29th European Safety and Reliability Conference (ESREL)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127677269","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 : 2019-09-25DOI: 10.3850/978-981-11-2724-3_0137-CD
Jack Litherland, J. Andrews
Railway utilization is increasing. In 2017-18 there were over 1.7 billion passenger journeys made on the UK railway network, more than double the number made in 1995. Therefore getting maximum performance from the existing network by streamlining maintenance is vital. Previous research has tended to model maintenance interventions as uniform length and assume no spatial dependencies. However, in reality maintenance decisions are generally taken accounting for the condition of the whole of a route section thus prioritizing the utilization of the available resources. In this research, Petri nets will be used to explore a range of techniques for modelling maintenance on a 100 mile section of UK railway. Four methodologies will be implemented and compared. Initially the system will be modelled using a single small (220 yards) section and the values for the route section extrapolated from this. The second method will model the system as 849 individual small sections, with some interactions and dependencies considered between the track sections. The third methodology will consider that maintenance will affect a group of adjacent sections and maintenance will only be performed if all sections are degraded. The final methodology will schedule work using work banks to allow the number of sections maintained during an intervention to vary.
{"title":"A Petri Net Methodology for Modelling the Maintenance of Railway Route Sections","authors":"Jack Litherland, J. Andrews","doi":"10.3850/978-981-11-2724-3_0137-CD","DOIUrl":"https://doi.org/10.3850/978-981-11-2724-3_0137-CD","url":null,"abstract":"Railway utilization is increasing. In 2017-18 there were over 1.7 billion passenger journeys made on the UK railway network, more than double the number made in 1995. Therefore getting maximum performance from the existing network by streamlining maintenance is vital. Previous research has tended to model maintenance interventions as uniform length and assume no spatial dependencies. However, in reality maintenance decisions are generally taken accounting for the condition of the whole of a route section thus prioritizing the utilization of the available resources. In this research, Petri nets will be used to explore a range of techniques for modelling maintenance on a 100 mile section of UK railway. Four methodologies will be implemented and compared. Initially the system will be modelled using a single small (220 yards) section and the values for the route section extrapolated from this. The second method will model the system as 849 individual small sections, with some interactions and dependencies considered between the track sections. The third methodology will consider that maintenance will affect a group of adjacent sections and maintenance will only be performed if all sections are degraded. The final methodology will schedule work using work banks to allow the number of sections maintained during an intervention to vary.","PeriodicalId":342000,"journal":{"name":"Proceedings of the 29th European Safety and Reliability Conference (ESREL)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130755764","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 : 2019-09-23DOI: 10.3850/978-981-11-2724-3_0302-cd
D. Verstraete, E. Droguett, M. Modarres
Multi-sensor systems are proliferating the asset management industry and by proxy, the structural health management community. Asset managers are beginning to require a prognostics and health management system to predict and assess maintenance decisions. These systems handle big machinery data and multi-sensor fusion and integrate remaining useful life prognostic capabilities. We introduce a deep adversarial learning approach to damage prognostics. A non-Markovian variational inference-based model incorporating an adversarial training algorithm framework was developed. The proposed framework was applied to a public multi-sensor data set of turbofan engines to demonstrate its ability to predict remaining useful life. We find that using the deep adversarial based approach results in higher performing remaining useful life predictions.
{"title":"A Deep Adversarial Approach based on Multisensor Fusion for Remaining Useful Lifeprognostics","authors":"D. Verstraete, E. Droguett, M. Modarres","doi":"10.3850/978-981-11-2724-3_0302-cd","DOIUrl":"https://doi.org/10.3850/978-981-11-2724-3_0302-cd","url":null,"abstract":"Multi-sensor systems are proliferating the asset management industry and by proxy, the structural health management community. Asset managers are beginning to require a prognostics and health management system to predict and assess maintenance decisions. These systems handle big machinery data and multi-sensor fusion and integrate remaining useful life prognostic capabilities. We introduce a deep adversarial learning approach to damage prognostics. A non-Markovian variational inference-based model incorporating an adversarial training algorithm framework was developed. The proposed framework was applied to a public multi-sensor data set of turbofan engines to demonstrate its ability to predict remaining useful life. We find that using the deep adversarial based approach results in higher performing remaining useful life predictions.","PeriodicalId":342000,"journal":{"name":"Proceedings of the 29th European Safety and Reliability Conference (ESREL)","volume":"224 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130738573","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 : 2019-09-22DOI: 10.3850/978-981-11-2724-3_0348-cd
El Kahi Elio, D. Olivier, K. Michel, Mehdizadeh Rasool, Conin Marianne, Rahme Pierre
{"title":"Influence of Spatial Variability of Soil Properties on Structures Response","authors":"El Kahi Elio, D. Olivier, K. Michel, Mehdizadeh Rasool, Conin Marianne, Rahme Pierre","doi":"10.3850/978-981-11-2724-3_0348-cd","DOIUrl":"https://doi.org/10.3850/978-981-11-2724-3_0348-cd","url":null,"abstract":"","PeriodicalId":342000,"journal":{"name":"Proceedings of the 29th European Safety and Reliability Conference (ESREL)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130856048","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 : 2019-09-22DOI: 10.3850/978-981-11-2724-3_0349-cd
E. Kahi, R. Mehdizadeh, K. Michel, D. Olivier, P. Rahme
{"title":"Sensitivity Analysis in the Transmission of Ground Movements to Structures considering the Variability of Soil-Structure Interaction Parameters","authors":"E. Kahi, R. Mehdizadeh, K. Michel, D. Olivier, P. Rahme","doi":"10.3850/978-981-11-2724-3_0349-cd","DOIUrl":"https://doi.org/10.3850/978-981-11-2724-3_0349-cd","url":null,"abstract":"","PeriodicalId":342000,"journal":{"name":"Proceedings of the 29th European Safety and Reliability Conference (ESREL)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132427892","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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