Pub Date : 1900-01-01DOI: 10.5220/0011526000003329
João Pereira, Mauro Queirós, Nuno M. C. da Costa, S. Marcelino, José Meireles, Jaime C. Fonseca, António Moreira, João Borges
{"title":"TMRobot Series Toolbox: Interfacing Collaborative Robots with MATLAB","authors":"João Pereira, Mauro Queirós, Nuno M. C. da Costa, S. Marcelino, José Meireles, Jaime C. Fonseca, António Moreira, João Borges","doi":"10.5220/0011526000003329","DOIUrl":"https://doi.org/10.5220/0011526000003329","url":null,"abstract":"","PeriodicalId":380008,"journal":{"name":"International Conference on Innovative Intelligent Industrial Production and Logistics","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133413971","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 : 1900-01-01DOI: 10.5220/0010657500003062
Dylan Molinié, K. Madani
: The new challenges Science is facing nowadays are legion; they mostly focus on high level technology, and more specifically Robotics , Internet of Things , Smart Automation (cities, houses, plants, buildings, etc.), and more recently Cyber-Physical Systems and Industry 4.0 . For a long time, cognitive systems have been seen as a mere dream only worth of Science Fiction. Even though there is much to be done, the researches and progress made in Artificial Intelligence have let cognition-based systems make a great leap forward, which is now an actual great area of interest for many scientists and industrialists. Nonetheless, there are two main obstacles to system’s smartness: computational limitations and the infinite number of states to define; Machine Learning-based algorithms are perfectly suitable to Cognition and Automation, for they allow an automatic – and accurate – identification of the systems, usable as knowledge for later regulation. In this paper, we discuss the benefits of Machine Learning, and we present some new avenues of reflection for automatic behavior correctness identification through space partitioning, and density conceptualization and computation.
{"title":"Characterizing N-Dimension Data Clusters: A Density-based Metric for Compactness and Homogeneity Evaluation","authors":"Dylan Molinié, K. Madani","doi":"10.5220/0010657500003062","DOIUrl":"https://doi.org/10.5220/0010657500003062","url":null,"abstract":": The new challenges Science is facing nowadays are legion; they mostly focus on high level technology, and more specifically Robotics , Internet of Things , Smart Automation (cities, houses, plants, buildings, etc.), and more recently Cyber-Physical Systems and Industry 4.0 . For a long time, cognitive systems have been seen as a mere dream only worth of Science Fiction. Even though there is much to be done, the researches and progress made in Artificial Intelligence have let cognition-based systems make a great leap forward, which is now an actual great area of interest for many scientists and industrialists. Nonetheless, there are two main obstacles to system’s smartness: computational limitations and the infinite number of states to define; Machine Learning-based algorithms are perfectly suitable to Cognition and Automation, for they allow an automatic – and accurate – identification of the systems, usable as knowledge for later regulation. In this paper, we discuss the benefits of Machine Learning, and we present some new avenues of reflection for automatic behavior correctness identification through space partitioning, and density conceptualization and computation.","PeriodicalId":380008,"journal":{"name":"International Conference on Innovative Intelligent Industrial Production and Logistics","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132958423","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 : 1900-01-01DOI: 10.5220/0011574500003329
Ander García, Xabier Oregui, Javier Franco, Unai Arrieta
{"title":"Edge Containerized Architecture for Manufacturing Process Time Series Data Monitoring and Visualization","authors":"Ander García, Xabier Oregui, Javier Franco, Unai Arrieta","doi":"10.5220/0011574500003329","DOIUrl":"https://doi.org/10.5220/0011574500003329","url":null,"abstract":"","PeriodicalId":380008,"journal":{"name":"International Conference on Innovative Intelligent Industrial Production and Logistics","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126040518","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 : 1900-01-01DOI: 10.5220/0011526200003329
Mauro Queirós, João Pereira, Nuno M. C. da Costa, S. Marcelino, José Meireles, Jaime C. Fonseca, António Moreira, João Borges
: Flexibility and speed in the development of new industrial machines are essential factors for the success of capital goods industries. When assembling a printed circuit board (PCB), since all the components are surface-mounted devices (SMD), the whole process is automatic. However, in many PCBs, it is necessary to place components that are not SMDs, called pin through-hole components (PTH), having to be inserted manually, which leads to delays in the production line. This work proposes and validates a prototype work cell based on a collaborative robot and vision systems whose objective is to insert these components in a completely autonomous or semi-autonomous way. Different tests were made to validate this work cell, showing the correct implementation and the possibility of replacing the human worker on this PCB assembly task.
{"title":"Human-Robot Collaboration (HRC) with Vision Inspection for PCB Assembly","authors":"Mauro Queirós, João Pereira, Nuno M. C. da Costa, S. Marcelino, José Meireles, Jaime C. Fonseca, António Moreira, João Borges","doi":"10.5220/0011526200003329","DOIUrl":"https://doi.org/10.5220/0011526200003329","url":null,"abstract":": Flexibility and speed in the development of new industrial machines are essential factors for the success of capital goods industries. When assembling a printed circuit board (PCB), since all the components are surface-mounted devices (SMD), the whole process is automatic. However, in many PCBs, it is necessary to place components that are not SMDs, called pin through-hole components (PTH), having to be inserted manually, which leads to delays in the production line. This work proposes and validates a prototype work cell based on a collaborative robot and vision systems whose objective is to insert these components in a completely autonomous or semi-autonomous way. Different tests were made to validate this work cell, showing the correct implementation and the possibility of replacing the human worker on this PCB assembly task.","PeriodicalId":380008,"journal":{"name":"International Conference on Innovative Intelligent Industrial Production and Logistics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130992096","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 : 1900-01-01DOI: 10.5220/0011380300003329
S. Latham, C. Giannetti
{"title":"Root Cause Classification of Temperature-related Failure Modes in a Hot Strip Mill","authors":"S. Latham, C. Giannetti","doi":"10.5220/0011380300003329","DOIUrl":"https://doi.org/10.5220/0011380300003329","url":null,"abstract":"","PeriodicalId":380008,"journal":{"name":"International Conference on Innovative Intelligent Industrial Production and Logistics","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114725778","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 : 1900-01-01DOI: 10.5220/0010055400690075
R. Mühlbacher, Hans Göpfrich, A. Gàlffy
This paper proposes an infrastructure for the digitalisation and integration of tasks along the life cycle of a lotsize-1 product from specification to depollution. The proposal shows the integration of existing open source tools into a design and production infrastructure. Starting from the positioning of the approach within the RAMI 4.0 framework, additional abstraction layers are presented, which help to organize the life cycle process. Besides the layer conception a showcase implementation is presented, which provides a factory for the production of model airplanes. The prototype shows the life cycle of a product instance as it is specified down to the production and even further. The digital twin convoys the instance along its whole existence.
{"title":"Infrastructure for an Integrated Industry 4.0 Life Cycle Spanning Design and Production Platform","authors":"R. Mühlbacher, Hans Göpfrich, A. Gàlffy","doi":"10.5220/0010055400690075","DOIUrl":"https://doi.org/10.5220/0010055400690075","url":null,"abstract":"This paper proposes an infrastructure for the digitalisation and integration of tasks along the life cycle of a lotsize-1 product from specification to depollution. The proposal shows the integration of existing open source tools into a design and production infrastructure. Starting from the positioning of the approach within the RAMI 4.0 framework, additional abstraction layers are presented, which help to organize the life cycle process. Besides the layer conception a showcase implementation is presented, which provides a factory for the production of model airplanes. The prototype shows the life cycle of a product instance as it is specified down to the production and even further. The digital twin convoys the instance along its whole existence.","PeriodicalId":380008,"journal":{"name":"International Conference on Innovative Intelligent Industrial Production and Logistics","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116262819","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 : 1900-01-01DOI: 10.5220/0011548000003329
A. L. Alfeo, M. G. Cimino, G. Gagliardi
: Maintenance activities can be better planned by employing machine learning technologies to monitor an asset’s health conditions. However, the variety of observable measures (e.g. temperature, vibration) and behaviours characterizing the health degradation process results in time-consuming manual feature extraction to ensure accurate degradation stage recognitions. Indeed, approaches able to provide automatic feature extraction from multiple and heterogeneous sources are more and more required in the field of predictive maintenance. This is-sue can be addressed in a data-driven fashion by using feature learning technology, enabling the transformation of minimally processed time series into informative features. Given its capability of discovering meaningful patterns in data while enabling data fusion, many feature learning approaches are based on deep learning technology (e.g. autoencoders). In this work, an architecture based on autoencoders is used to automatically extract degradation-representative features from minimally preprocessed time series of vibration and temperature data. Different autoencoder architectures are implemented to compare different data fusion strategies. The proposed approach is tested considering both the recognition performances and the quality of the learned features with a publicly available real-world dataset about bearings’ progressive degradation. The proposed approach is also compared against manual feature extraction and the state-of-the-art technology in feature learning.
{"title":"Automatic Feature Extraction for Bearings' Degradation Assessment using Minimally Pre-processed Time series and Multi-modal Feature Learning","authors":"A. L. Alfeo, M. G. Cimino, G. Gagliardi","doi":"10.5220/0011548000003329","DOIUrl":"https://doi.org/10.5220/0011548000003329","url":null,"abstract":": Maintenance activities can be better planned by employing machine learning technologies to monitor an asset’s health conditions. However, the variety of observable measures (e.g. temperature, vibration) and behaviours characterizing the health degradation process results in time-consuming manual feature extraction to ensure accurate degradation stage recognitions. Indeed, approaches able to provide automatic feature extraction from multiple and heterogeneous sources are more and more required in the field of predictive maintenance. This is-sue can be addressed in a data-driven fashion by using feature learning technology, enabling the transformation of minimally processed time series into informative features. Given its capability of discovering meaningful patterns in data while enabling data fusion, many feature learning approaches are based on deep learning technology (e.g. autoencoders). In this work, an architecture based on autoencoders is used to automatically extract degradation-representative features from minimally preprocessed time series of vibration and temperature data. Different autoencoder architectures are implemented to compare different data fusion strategies. The proposed approach is tested considering both the recognition performances and the quality of the learned features with a publicly available real-world dataset about bearings’ progressive degradation. The proposed approach is also compared against manual feature extraction and the state-of-the-art technology in feature learning.","PeriodicalId":380008,"journal":{"name":"International Conference on Innovative Intelligent Industrial Production and Logistics","volume":"201 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122568156","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 : 1900-01-01DOI: 10.5220/0011378400003329
Johan Oxenstierna, J. Malec, Volker Krüger
{"title":"New Benchmarks and Optimization Model for the Storage Location Assignment Problem","authors":"Johan Oxenstierna, J. Malec, Volker Krüger","doi":"10.5220/0011378400003329","DOIUrl":"https://doi.org/10.5220/0011378400003329","url":null,"abstract":"","PeriodicalId":380008,"journal":{"name":"International Conference on Innovative Intelligent Industrial Production and Logistics","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123560190","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 : 1900-01-01DOI: 10.1007/978-3-031-37228-5_6
Randy Paredis, Cláudio Gomes, H. Vangheluwe
{"title":"A Family of Digital T Workflows and Architectures: Exploring Two Cases","authors":"Randy Paredis, Cláudio Gomes, H. Vangheluwe","doi":"10.1007/978-3-031-37228-5_6","DOIUrl":"https://doi.org/10.1007/978-3-031-37228-5_6","url":null,"abstract":"","PeriodicalId":380008,"journal":{"name":"International Conference on Innovative Intelligent Industrial Production and Logistics","volume":"4651 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132566758","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 : 1900-01-01DOI: 10.1007/978-3-031-37228-5_8
Christine Markarian
{"title":"An Online Variant of Set Cover Inspired by Happy Clients","authors":"Christine Markarian","doi":"10.1007/978-3-031-37228-5_8","DOIUrl":"https://doi.org/10.1007/978-3-031-37228-5_8","url":null,"abstract":"","PeriodicalId":380008,"journal":{"name":"International Conference on Innovative Intelligent Industrial Production and Logistics","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129424101","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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