Pub Date : 2017-09-01DOI: 10.1109/ETFA.2017.8247771
J. Miranda, J. Cabral, Suprateek Banerjee, Daniel Grossmann, C. F. Pedersen, S. Wagner
This study presents an assessment of the OPC Unified Architecture as an integration framework for heterogeneous healthcare systems enabling compliance with the Industry 4.0 paradigm. The contributions of this work are: 1) a conceptual architecture with heterogeneous networks for enabling Internet of Things healthcare applications, 2) OPC UA data models based on the HL7 Reference Information Model for information exchange and storage, and 3) an analysis of how OPC UA can enable the healthcare sector to be part of the Industry 4.0.
{"title":"Analysis of OPC unified architecture for healthcare applications","authors":"J. Miranda, J. Cabral, Suprateek Banerjee, Daniel Grossmann, C. F. Pedersen, S. Wagner","doi":"10.1109/ETFA.2017.8247771","DOIUrl":"https://doi.org/10.1109/ETFA.2017.8247771","url":null,"abstract":"This study presents an assessment of the OPC Unified Architecture as an integration framework for heterogeneous healthcare systems enabling compliance with the Industry 4.0 paradigm. The contributions of this work are: 1) a conceptual architecture with heterogeneous networks for enabling Internet of Things healthcare applications, 2) OPC UA data models based on the HL7 Reference Information Model for information exchange and storage, and 3) an analysis of how OPC UA can enable the healthcare sector to be part of the Industry 4.0.","PeriodicalId":6522,"journal":{"name":"2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)","volume":"111 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73632822","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 : 2017-09-01DOI: 10.1109/ETFA.2017.8247660
C. Nguyen, Xin Li, R. D. Blanton, Xiang Li
Virtual metrology is an important tool for industrial automation. To accurately build regression models for virtual metrology, we consider semi-supervised learning where labeled data are expensive to collect, but unlabeled data are abundant. In such a scenario, due to the scarcity of labeled data, traditional single-view learning methods face the risk of overfitting. To address the overfitting issue, we develop a Partial Co-training framework, which is an extension of the original co-training approach by means of an undirected probabilistic graphical model. Unlike other co-training techniques, this model creates a partial view by shrinking the original feature space, and makes use of this partial-view to provide guidance information for improving the complete-view model. Our approach is validated with data from two manufacturing applications. The results indicate that a consistent and robust estimation is achievable with very limited labeled data.
{"title":"Partial co-training for virtual metrology","authors":"C. Nguyen, Xin Li, R. D. Blanton, Xiang Li","doi":"10.1109/ETFA.2017.8247660","DOIUrl":"https://doi.org/10.1109/ETFA.2017.8247660","url":null,"abstract":"Virtual metrology is an important tool for industrial automation. To accurately build regression models for virtual metrology, we consider semi-supervised learning where labeled data are expensive to collect, but unlabeled data are abundant. In such a scenario, due to the scarcity of labeled data, traditional single-view learning methods face the risk of overfitting. To address the overfitting issue, we develop a Partial Co-training framework, which is an extension of the original co-training approach by means of an undirected probabilistic graphical model. Unlike other co-training techniques, this model creates a partial view by shrinking the original feature space, and makes use of this partial-view to provide guidance information for improving the complete-view model. Our approach is validated with data from two manufacturing applications. The results indicate that a consistent and robust estimation is achievable with very limited labeled data.","PeriodicalId":6522,"journal":{"name":"2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)","volume":"25 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74027859","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 : 2017-09-01DOI: 10.1109/ETFA.2017.8247767
Williams-Paul Nwadiugwu, Joong-Hyuk Cha, Dong-Seong Kim
In this paper, an enhanced SDP-Dynamic bloom filters for a DDS node discovery scheme in real-time distributed systems is proposed. Since the previous works of the DDS focuses more on the usage of a Simple Discovery Protocol (SDP) for endpoint to endpoint information communication of industrialscale networks, attempts have now been made to enhance this approach into the Simple Discovery Protocol Dynamic Bloom Filters (SDP-Dynamic Bloom) focusing more on scalability in the amount of sent and stored message packets in the industrial network system. Simulation result show that the proposed scheme viciously reduces the overall computing and processing time of both stable and unstable industrial network environment which arises during the restructuring process of the existing SDP bloom filters approach.
{"title":"Enhanced SDP-dynamic bloom filters for a DDS node discovery in real-time distributed systems","authors":"Williams-Paul Nwadiugwu, Joong-Hyuk Cha, Dong-Seong Kim","doi":"10.1109/ETFA.2017.8247767","DOIUrl":"https://doi.org/10.1109/ETFA.2017.8247767","url":null,"abstract":"In this paper, an enhanced SDP-Dynamic bloom filters for a DDS node discovery scheme in real-time distributed systems is proposed. Since the previous works of the DDS focuses more on the usage of a Simple Discovery Protocol (SDP) for endpoint to endpoint information communication of industrialscale networks, attempts have now been made to enhance this approach into the Simple Discovery Protocol Dynamic Bloom Filters (SDP-Dynamic Bloom) focusing more on scalability in the amount of sent and stored message packets in the industrial network system. Simulation result show that the proposed scheme viciously reduces the overall computing and processing time of both stable and unstable industrial network environment which arises during the restructuring process of the existing SDP bloom filters approach.","PeriodicalId":6522,"journal":{"name":"2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)","volume":"35 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75798933","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 : 2017-09-01DOI: 10.1109/ETFA.2017.8247705
M. Steinegger, Martin Melik-Merkumians, Johannes Zajc, G. Schitter
In this paper, a framework for automatic generation of a flexible and modular system for fault detection and diagnosis (FDD) is proposed. The method is based on an ontology-based integration framework, which gathers the information from various engineering artifacts. Based on the ontologies, FDD functions are generated based on structural and procedural generation rules. The rules are encoded as SPARQL queries which automatically build logical segments of the entire manufacturing system in the ontology, assign sub-processes to these segments, and finally generate the appropriate FDD system for the sub-process. These generated modular FDD functions are additionally combined in a modular way to enable the fault detection and diagnosis of the entire system. The effectiveness of the approach is demonstrated by a first application to a conveyor system.
{"title":"A framework for automatic knowledge-based fault detection in industrial conveyor systems","authors":"M. Steinegger, Martin Melik-Merkumians, Johannes Zajc, G. Schitter","doi":"10.1109/ETFA.2017.8247705","DOIUrl":"https://doi.org/10.1109/ETFA.2017.8247705","url":null,"abstract":"In this paper, a framework for automatic generation of a flexible and modular system for fault detection and diagnosis (FDD) is proposed. The method is based on an ontology-based integration framework, which gathers the information from various engineering artifacts. Based on the ontologies, FDD functions are generated based on structural and procedural generation rules. The rules are encoded as SPARQL queries which automatically build logical segments of the entire manufacturing system in the ontology, assign sub-processes to these segments, and finally generate the appropriate FDD system for the sub-process. These generated modular FDD functions are additionally combined in a modular way to enable the fault detection and diagnosis of the entire system. The effectiveness of the approach is demonstrated by a first application to a conveyor system.","PeriodicalId":6522,"journal":{"name":"2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)","volume":"135 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75035541","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 : 2017-09-01DOI: 10.1109/ETFA.2017.8247694
F. Denaro, L. Consolini, Davide Buratti
In industrial weight-filling machines, containers are filled with the liquid stored in a tank by an electronically controlled valve. The weight is sensed through a load cell. We develop a learning algorithm that predicts the right closure time as a function of liquid pressure and temperature. The algorithm solves a non-convex robust regression problem and is based on a branch and bound approach in regressors space.
{"title":"Robust regression for adaptive control of industrial weight fillers","authors":"F. Denaro, L. Consolini, Davide Buratti","doi":"10.1109/ETFA.2017.8247694","DOIUrl":"https://doi.org/10.1109/ETFA.2017.8247694","url":null,"abstract":"In industrial weight-filling machines, containers are filled with the liquid stored in a tank by an electronically controlled valve. The weight is sensed through a load cell. We develop a learning algorithm that predicts the right closure time as a function of liquid pressure and temperature. The algorithm solves a non-convex robust regression problem and is based on a branch and bound approach in regressors space.","PeriodicalId":6522,"journal":{"name":"2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)","volume":"27 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78122867","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 : 2017-09-01DOI: 10.1109/ETFA.2017.8247614
Fabian Mauroner, M. Baunach
Real-time multi-tasking systems may require an individual stack for each task to fulfill all hard real-time requirements. However, these stacks may consume a huge memory space, even if not all stacks are simultaneously fully utilized. Thus, sharing currently unused stack space may improve memory utilization as possible with Memory Management Units (MMUs). However, an MMU introduces temporal jitter to memory accesses, influencing the real-time behavior. In this work, we propose a new concept to share dynamically the complete available stack space across tasks. Thereby, every stack operation executes in a deterministic time, by giving the Microcontroller Unit (MCU) Operating System (OS)-awareness.
{"title":"StackMMU: Dynamic stack sharing for embedded systems","authors":"Fabian Mauroner, M. Baunach","doi":"10.1109/ETFA.2017.8247614","DOIUrl":"https://doi.org/10.1109/ETFA.2017.8247614","url":null,"abstract":"Real-time multi-tasking systems may require an individual stack for each task to fulfill all hard real-time requirements. However, these stacks may consume a huge memory space, even if not all stacks are simultaneously fully utilized. Thus, sharing currently unused stack space may improve memory utilization as possible with Memory Management Units (MMUs). However, an MMU introduces temporal jitter to memory accesses, influencing the real-time behavior. In this work, we propose a new concept to share dynamically the complete available stack space across tasks. Thereby, every stack operation executes in a deterministic time, by giving the Microcontroller Unit (MCU) Operating System (OS)-awareness.","PeriodicalId":6522,"journal":{"name":"2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)","volume":"24 1","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81434845","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 : 2017-09-01DOI: 10.1109/ETFA.2017.8247756
Alberto Isasi-Andrieu, Estíbaliz Garrote-Contreras, P. Iriondo, David Aldama-Gant, A. Galdran
A recurrent problem in the industrial sector is the quality control and surface inspection of reflecting pieces with non-planar surfaces. This is an extended and non-solved problem because it is related not only to the material itself but also to the coating. This problem appears in a wide spectrum of industrial sectors such as automation, aeronautics or orthopaedics. In recent years, a new imaging technology called deflectometry has been introduced in the field of surface inspection for industrial applications. This technology features a high resolution camera and a dedicated illumination system-based on displaying fringe patterns in a monitor-allowing the detection of irregularities in surfaces. However, the introduction of this technology into automated quality control systems remains a challenging task, due to the wide range of defects and shapes that can appear. It becomes thus necessary to characterize different types of errors and their associated detection setups. In this paper we propose a novel methodology to define and analyse the best setup for each pattern. We also explore an efficient technique to maximize the number of different pieces inspected without modifying the setup of the acquisition system. Experimental results show that the presented methodology defines an inspection method that can be installed in an automatic quality control device for non-planar surfaces analysis of manufactured products.
{"title":"Deflectometry setup definition for automatic chrome surface inspection","authors":"Alberto Isasi-Andrieu, Estíbaliz Garrote-Contreras, P. Iriondo, David Aldama-Gant, A. Galdran","doi":"10.1109/ETFA.2017.8247756","DOIUrl":"https://doi.org/10.1109/ETFA.2017.8247756","url":null,"abstract":"A recurrent problem in the industrial sector is the quality control and surface inspection of reflecting pieces with non-planar surfaces. This is an extended and non-solved problem because it is related not only to the material itself but also to the coating. This problem appears in a wide spectrum of industrial sectors such as automation, aeronautics or orthopaedics. In recent years, a new imaging technology called deflectometry has been introduced in the field of surface inspection for industrial applications. This technology features a high resolution camera and a dedicated illumination system-based on displaying fringe patterns in a monitor-allowing the detection of irregularities in surfaces. However, the introduction of this technology into automated quality control systems remains a challenging task, due to the wide range of defects and shapes that can appear. It becomes thus necessary to characterize different types of errors and their associated detection setups. In this paper we propose a novel methodology to define and analyse the best setup for each pattern. We also explore an efficient technique to maximize the number of different pieces inspected without modifying the setup of the acquisition system. Experimental results show that the presented methodology defines an inspection method that can be installed in an automatic quality control device for non-planar surfaces analysis of manufactured products.","PeriodicalId":6522,"journal":{"name":"2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)","volume":"397 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85022090","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 : 2017-09-01DOI: 10.1109/ETFA.2017.8247711
M. Wimmer, Petr Novák, R. Šindelář, L. Berardinelli, Tanja Mayerhofer, Alexandra Mazak
Variability modeling is an emerging topic in the general field of systems engineering and, with current trends such as Industrie 4.0, it gains more and more interest in the domain of production systems. Therefore, it is not sufficient to describe systems in several specific cases, but instead families of systems have to be used. In this paper we introduce a role class library for AutomationML to explicitly represent variability. This allows to exchange not only system descriptions but also system family descriptions. We argue for a light-weight extension of AutomationML. The variability-based modeling approach is based on cardinalities, which is a well-known concept from conceptual modeling and feature modeling. Furthermore, we also show how instantiations of variability models can be validated by our EMF-based AutomationML workbench.
{"title":"Cardinality-based variability modeling with AutomationML","authors":"M. Wimmer, Petr Novák, R. Šindelář, L. Berardinelli, Tanja Mayerhofer, Alexandra Mazak","doi":"10.1109/ETFA.2017.8247711","DOIUrl":"https://doi.org/10.1109/ETFA.2017.8247711","url":null,"abstract":"Variability modeling is an emerging topic in the general field of systems engineering and, with current trends such as Industrie 4.0, it gains more and more interest in the domain of production systems. Therefore, it is not sufficient to describe systems in several specific cases, but instead families of systems have to be used. In this paper we introduce a role class library for AutomationML to explicitly represent variability. This allows to exchange not only system descriptions but also system family descriptions. We argue for a light-weight extension of AutomationML. The variability-based modeling approach is based on cardinalities, which is a well-known concept from conceptual modeling and feature modeling. Furthermore, we also show how instantiations of variability models can be validated by our EMF-based AutomationML workbench.","PeriodicalId":6522,"journal":{"name":"2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)","volume":"33 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85234432","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 : 2017-09-01DOI: 10.1109/ETFA.2017.8247624
M. Vlk, R. Barták, Z. Hanzálek
Real-life scheduling has to face many difficulties such as dynamics of manufacturing environments with unforeseen events occurring during the execution of a schedule. Namely, in the case of a resource failure, it may be necessary to process a lot of work again, or a feasible schedule recovery may not exist at all. Moreover, the time window within which the ongoing schedule must be updated may be very short, and too timeconsuming computation of the schedule may lead to a failure of the scheduling mechanism and setback in production. Our approach in the area of predictive-reactive scheduling is to allow for substitution of tasks, which cannot be executed, with a set of alternative tasks. This paper makes use of the model of the hierarchical workflows and gives an SMT and a CSP models to recover an ongoing schedule from a resource failure with the objective to minimize the work processed in vain. The experimental analysis identified parameters for which the SMT model clearly outperforms the CSP model and vice versa.
{"title":"Minimization of useless work in resource failure recovery of workflow schedules","authors":"M. Vlk, R. Barták, Z. Hanzálek","doi":"10.1109/ETFA.2017.8247624","DOIUrl":"https://doi.org/10.1109/ETFA.2017.8247624","url":null,"abstract":"Real-life scheduling has to face many difficulties such as dynamics of manufacturing environments with unforeseen events occurring during the execution of a schedule. Namely, in the case of a resource failure, it may be necessary to process a lot of work again, or a feasible schedule recovery may not exist at all. Moreover, the time window within which the ongoing schedule must be updated may be very short, and too timeconsuming computation of the schedule may lead to a failure of the scheduling mechanism and setback in production. Our approach in the area of predictive-reactive scheduling is to allow for substitution of tasks, which cannot be executed, with a set of alternative tasks. This paper makes use of the model of the hierarchical workflows and gives an SMT and a CSP models to recover an ongoing schedule from a resource failure with the objective to minimize the work processed in vain. The experimental analysis identified parameters for which the SMT model clearly outperforms the CSP model and vice versa.","PeriodicalId":6522,"journal":{"name":"2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)","volume":"46 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85242874","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 : 2017-09-01DOI: 10.1109/ETFA.2017.8247683
Antje Rogalla, O. Niggemann
New products or product varieties require adapted processes and new production configurations of Cyber-Physical Production Systems. In this paper the focus is on production planning. The planning task is placed into the existing theory of automated planning. The system should automatically generate new production processes and react to new situations in dynamic environments. A new concept of planning and a new algorithm are presented, so that automated planning methods are applicable in real industrial environments.
{"title":"Automated process planning for cyber-physical production systems","authors":"Antje Rogalla, O. Niggemann","doi":"10.1109/ETFA.2017.8247683","DOIUrl":"https://doi.org/10.1109/ETFA.2017.8247683","url":null,"abstract":"New products or product varieties require adapted processes and new production configurations of Cyber-Physical Production Systems. In this paper the focus is on production planning. The planning task is placed into the existing theory of automated planning. The system should automatically generate new production processes and react to new situations in dynamic environments. A new concept of planning and a new algorithm are presented, so that automated planning methods are applicable in real industrial environments.","PeriodicalId":6522,"journal":{"name":"2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)","volume":"60 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78139965","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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