Pub Date : 2016-07-20DOI: 10.1109/INDIN.2016.7819206
Hui Shao, Zhiwei Gao, K. Busawon
In this paper, linear parameter varying (LPV) modelling technique is addressed for modelling a wind turbine system, with real-time changing scheduling parameters. Based on the LPV wind turbine model, a LPV observer-based fault detection method is utilized to detect faults under four scenarios. The effectiveness of the proposed modelling and fault detection techniques is demonstrated by using the widely-recognized wind turbine benchmark system.
{"title":"LPV modelling and LPV observer-based fault detection for wind turbine systems","authors":"Hui Shao, Zhiwei Gao, K. Busawon","doi":"10.1109/INDIN.2016.7819206","DOIUrl":"https://doi.org/10.1109/INDIN.2016.7819206","url":null,"abstract":"In this paper, linear parameter varying (LPV) modelling technique is addressed for modelling a wind turbine system, with real-time changing scheduling parameters. Based on the LPV wind turbine model, a LPV observer-based fault detection method is utilized to detect faults under four scenarios. The effectiveness of the proposed modelling and fault detection techniques is demonstrated by using the widely-recognized wind turbine benchmark system.","PeriodicalId":421680,"journal":{"name":"2016 IEEE 14th International Conference on Industrial Informatics (INDIN)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117049283","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 : 2016-07-19DOI: 10.1109/INDIN.2016.7819339
C. Iatrou, L. Urbas
The implementation of software based OPCUA servers on computing platforms in actuators and sensors of the field layer remains a challenge due to the protocols high memory and bandwidth prerequisites. This paper discusses encoding aspects of OPC UA binary data representations for devices with limited random access memory and low fieldbus throughput, especially focusing on single-chip microcomputing platforms. Efficient and machine-friendly binary representations of OPC UA data models are derived by examining the structure of OPC UA data and optimizing their representation in regard to 8 bit serial, non-volatile memory components. Transport compression mechanisms, aiming to reduce bandwidth requirements in crowded or low bandwidth networks, are also introduced. While the memory usage of information models could be significantly reduced to (116 kB for Namespace 0), it was shown transport compression cannot yield bandwidth improvements unless data is compressed as a service.
{"title":"Efficient OPC UA binary encoding considerations for embedded devices","authors":"C. Iatrou, L. Urbas","doi":"10.1109/INDIN.2016.7819339","DOIUrl":"https://doi.org/10.1109/INDIN.2016.7819339","url":null,"abstract":"The implementation of software based OPCUA servers on computing platforms in actuators and sensors of the field layer remains a challenge due to the protocols high memory and bandwidth prerequisites. This paper discusses encoding aspects of OPC UA binary data representations for devices with limited random access memory and low fieldbus throughput, especially focusing on single-chip microcomputing platforms. Efficient and machine-friendly binary representations of OPC UA data models are derived by examining the structure of OPC UA data and optimizing their representation in regard to 8 bit serial, non-volatile memory components. Transport compression mechanisms, aiming to reduce bandwidth requirements in crowded or low bandwidth networks, are also introduced. While the memory usage of information models could be significantly reduced to (116 kB for Namespace 0), it was shown transport compression cannot yield bandwidth improvements unless data is compressed as a service.","PeriodicalId":421680,"journal":{"name":"2016 IEEE 14th International Conference on Industrial Informatics (INDIN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129440864","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 : 2016-07-19DOI: 10.1109/INDIN.2016.7819263
Wahyono, A. Filonenko, K. Jo
As one of the traffic monitoring tasks, detecting an illegally parked vehicle aims to prevent car crashing between parked and other vehicles. However, developing such a task becomes more complex due to weather conditions, occlusion, illumination changing, and other factors. This work addresses a framework to detect an illegally parked vehicle using a cumulative dual foreground difference. In our framework, two background models with different learning rates are generated based on a Gaussian mixture model, defined as short- and long-term models. Each model extracts foreground pixels and the stability of these pixels are then analyzed based on cumulative values and temporal positions over a certain period of time. Subsequently, the connected component labeling is performed on the static pixels to form stable regions. To determine whether the candidate region is vehicle, a rule-based filtering approach is performed. Finally, the detection-based tracking is applied to reduce false positives. The effectiveness of the proposed framework is evaluated using i-LIDS and ISLab dataset. The experiment results show that the proposed framework is efficient and robust to detect an illegally parked vehicle. Thus, it can be considered as one of the task solutions for a traffic monitoring system.
{"title":"Detecting illegally parked vehicle based on cumulative dual foreground difference","authors":"Wahyono, A. Filonenko, K. Jo","doi":"10.1109/INDIN.2016.7819263","DOIUrl":"https://doi.org/10.1109/INDIN.2016.7819263","url":null,"abstract":"As one of the traffic monitoring tasks, detecting an illegally parked vehicle aims to prevent car crashing between parked and other vehicles. However, developing such a task becomes more complex due to weather conditions, occlusion, illumination changing, and other factors. This work addresses a framework to detect an illegally parked vehicle using a cumulative dual foreground difference. In our framework, two background models with different learning rates are generated based on a Gaussian mixture model, defined as short- and long-term models. Each model extracts foreground pixels and the stability of these pixels are then analyzed based on cumulative values and temporal positions over a certain period of time. Subsequently, the connected component labeling is performed on the static pixels to form stable regions. To determine whether the candidate region is vehicle, a rule-based filtering approach is performed. Finally, the detection-based tracking is applied to reduce false positives. The effectiveness of the proposed framework is evaluated using i-LIDS and ISLab dataset. The experiment results show that the proposed framework is efficient and robust to detect an illegally parked vehicle. Thus, it can be considered as one of the task solutions for a traffic monitoring system.","PeriodicalId":421680,"journal":{"name":"2016 IEEE 14th International Conference on Industrial Informatics (INDIN)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114762271","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 : 2016-07-19DOI: 10.1109/INDIN.2016.7819330
Steffen Henning, J. Otto, O. Niggemann
Manufacturing plants become more complex as the desire for modern individual products increases. Programming such plants is a challenging task that consumes a lot of time. This paper proposes a new control-code synthesis algorithm, which aids the programmer by automatically generating parts of the control-code. With the new algorithm, the programmer only has to specify and parametrize the general production process, e.g. drill a hole then paint the workpiece. The control-code for all intermediate processes, like transporting the workpiece from the drilling machine to the paint-spray station is generated automatically. This saves much engineering time and enables the programmer to focus on more challenging tasks, such as process optimisation.
{"title":"Pattern-based control-code synthesis","authors":"Steffen Henning, J. Otto, O. Niggemann","doi":"10.1109/INDIN.2016.7819330","DOIUrl":"https://doi.org/10.1109/INDIN.2016.7819330","url":null,"abstract":"Manufacturing plants become more complex as the desire for modern individual products increases. Programming such plants is a challenging task that consumes a lot of time. This paper proposes a new control-code synthesis algorithm, which aids the programmer by automatically generating parts of the control-code. With the new algorithm, the programmer only has to specify and parametrize the general production process, e.g. drill a hole then paint the workpiece. The control-code for all intermediate processes, like transporting the workpiece from the drilling machine to the paint-spray station is generated automatically. This saves much engineering time and enables the programmer to focus on more challenging tasks, such as process optimisation.","PeriodicalId":421680,"journal":{"name":"2016 IEEE 14th International Conference on Industrial Informatics (INDIN)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124051105","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 : 2016-07-19DOI: 10.1109/INDIN.2016.7819174
Abdelkrim Ali Zazou, E. Grolleau, Emilie Chevrier, P. Richard, J. Gaubert, Ladjel Bellatreche
In this paper a network reconfiguration model aimed to be used in an industrial context is presented. It is based on a min-cost flow problem (MCFP) and a simplified power flow calculation. Mixed Integer Quadratic Constrained Programming (MIQCP) and Mixed Integer Non linear Programming (MINLP) are used and compared to compute the network reconfiguration with off-the-shelf optimization solvers. Two test cases are presented, a small academic network and a real case study. The paper shows experimentally that simplification on model level can be more efficient than simplification on the solving level for real world problems.
{"title":"Power distribution network reconfiguration based on min-cost flow problem","authors":"Abdelkrim Ali Zazou, E. Grolleau, Emilie Chevrier, P. Richard, J. Gaubert, Ladjel Bellatreche","doi":"10.1109/INDIN.2016.7819174","DOIUrl":"https://doi.org/10.1109/INDIN.2016.7819174","url":null,"abstract":"In this paper a network reconfiguration model aimed to be used in an industrial context is presented. It is based on a min-cost flow problem (MCFP) and a simplified power flow calculation. Mixed Integer Quadratic Constrained Programming (MIQCP) and Mixed Integer Non linear Programming (MINLP) are used and compared to compute the network reconfiguration with off-the-shelf optimization solvers. Two test cases are presented, a small academic network and a real case study. The paper shows experimentally that simplification on model level can be more efficient than simplification on the solving level for real world problems.","PeriodicalId":421680,"journal":{"name":"2016 IEEE 14th International Conference on Industrial Informatics (INDIN)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133588223","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 : 2016-07-19DOI: 10.1109/INDIN.2016.7819265
Haijun Zhang, Jingxuan Li, Yuzhu Ji, Heng Yue
This paper presents a character-level sequence-to-sequence learning method, RNNembed. Specifically, we embed a Recurrent Neural Network (RNN) into an encoder-decoder framework and generate character-level sequence representation as input. The dimension of input feature space can be significantly reduced as well as avoiding the need to handle unknown or rare words in sequences. In the language model, we improve the basic structure of a Gated Recurrent Unit (GRU) by adding an output gate, which is used for filtering out unimportant information involved in the attention scheme of the alignment model. Our proposed method was examined in a large-scale dataset on a task of English-to-Chinese translation. Experimental results demonstrate that the proposed approach achieves a translation performance comparable, or close, to conventional word-based and phrase-based systems.
{"title":"A character-level sequence-to-sequence method for subtitle learning","authors":"Haijun Zhang, Jingxuan Li, Yuzhu Ji, Heng Yue","doi":"10.1109/INDIN.2016.7819265","DOIUrl":"https://doi.org/10.1109/INDIN.2016.7819265","url":null,"abstract":"This paper presents a character-level sequence-to-sequence learning method, RNNembed. Specifically, we embed a Recurrent Neural Network (RNN) into an encoder-decoder framework and generate character-level sequence representation as input. The dimension of input feature space can be significantly reduced as well as avoiding the need to handle unknown or rare words in sequences. In the language model, we improve the basic structure of a Gated Recurrent Unit (GRU) by adding an output gate, which is used for filtering out unimportant information involved in the attention scheme of the alignment model. Our proposed method was examined in a large-scale dataset on a task of English-to-Chinese translation. Experimental results demonstrate that the proposed approach achieves a translation performance comparable, or close, to conventional word-based and phrase-based systems.","PeriodicalId":421680,"journal":{"name":"2016 IEEE 14th International Conference on Industrial Informatics (INDIN)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131869432","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 : 2016-07-19DOI: 10.1109/INDIN.2016.7819258
Max Hoffmann, Philipp Thomas, D. Schütz, B. Vogel‐Heuser, Tobias Meisen, S. Jeschke
In terms of current industrial manufacturing sites, a major challenge is to deal with growing complexity by enabling intelligence on the shop floor of existing production processes. A possible solution to reach this goal consists in an integration of smart cyber-physical production systems into the automation systems of a production. One promising approach to do so is based on the agent paradigm. By deploying Multi-Agent Systems into the manufacturing components, each production step is able to gain a self-representation and to achieve intelligent behavior of the entire system. One problem though is the formalization of agent based systems and their communication among each other, which is currently rather hard-coded or application-specific. In this research paper, we propose an architectural approach for a Multi-Agent System that is based on OPC UA as modeling interface and as semantic approach for the integration of agent-based systems into existing manufacturing sites. For this purpose, we define a domain ontology for the representation of intelligent software agents and for the mapping of an agent-based communication by making use of the OPC UA meta model. Due to this conceptual approach, the integration of intelligent entities such as agents into grown manufacturing systems can be performed in a structured and well-defined way as well as by using existing interfaces and semantic standards. The according agent representation intends to upgrade all production resources that can be linked through OPC UA with intelligent behavioral skills. We evaluate the proposed concept by means of an Industry 4.0 demonstrator implementing agents for the representation actual manufacturing machinery based on Raspberry Pi devices.
{"title":"Semantic integration of multi-agent systems using an OPC UA information modeling approach","authors":"Max Hoffmann, Philipp Thomas, D. Schütz, B. Vogel‐Heuser, Tobias Meisen, S. Jeschke","doi":"10.1109/INDIN.2016.7819258","DOIUrl":"https://doi.org/10.1109/INDIN.2016.7819258","url":null,"abstract":"In terms of current industrial manufacturing sites, a major challenge is to deal with growing complexity by enabling intelligence on the shop floor of existing production processes. A possible solution to reach this goal consists in an integration of smart cyber-physical production systems into the automation systems of a production. One promising approach to do so is based on the agent paradigm. By deploying Multi-Agent Systems into the manufacturing components, each production step is able to gain a self-representation and to achieve intelligent behavior of the entire system. One problem though is the formalization of agent based systems and their communication among each other, which is currently rather hard-coded or application-specific. In this research paper, we propose an architectural approach for a Multi-Agent System that is based on OPC UA as modeling interface and as semantic approach for the integration of agent-based systems into existing manufacturing sites. For this purpose, we define a domain ontology for the representation of intelligent software agents and for the mapping of an agent-based communication by making use of the OPC UA meta model. Due to this conceptual approach, the integration of intelligent entities such as agents into grown manufacturing systems can be performed in a structured and well-defined way as well as by using existing interfaces and semantic standards. The according agent representation intends to upgrade all production resources that can be linked through OPC UA with intelligent behavioral skills. We evaluate the proposed concept by means of an Industry 4.0 demonstrator implementing agents for the representation actual manufacturing machinery based on Raspberry Pi devices.","PeriodicalId":421680,"journal":{"name":"2016 IEEE 14th International Conference on Industrial Informatics (INDIN)","volume":"186 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116144635","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 : 2016-07-19DOI: 10.1109/INDIN.2016.7819295
Chiehyeon Lim, P. Maglio, Kwang-Jae Kim, Min-Jun Kim, Ki-hun Kim
Various types and massive amounts of data are being collected through physical and social sensing. In many cases of data use, the results and value of data analytics are conveyed to specific beneficiaries (e.g., individuals and organizations) within a service system, such as a transportation, energy supply, or healthcare service system. Thus, data-use can be directed and improved based on considerations of the relevant service system. In this paper, we suggest that effective use of data analytics can be guided by the question, “How does data analytics contribute to the creation of a smarter service system?” To facilitate answers to this question, we define a smart service system from a data application perspective, and propose a specific approach, serviceoriented data analytics, based on eight case studies related to smart service systems. We introduce an ongoing case study to demonstrate the applicability and utility of our proposals.
{"title":"Toward smarter service systems through service-oriented data analytics","authors":"Chiehyeon Lim, P. Maglio, Kwang-Jae Kim, Min-Jun Kim, Ki-hun Kim","doi":"10.1109/INDIN.2016.7819295","DOIUrl":"https://doi.org/10.1109/INDIN.2016.7819295","url":null,"abstract":"Various types and massive amounts of data are being collected through physical and social sensing. In many cases of data use, the results and value of data analytics are conveyed to specific beneficiaries (e.g., individuals and organizations) within a service system, such as a transportation, energy supply, or healthcare service system. Thus, data-use can be directed and improved based on considerations of the relevant service system. In this paper, we suggest that effective use of data analytics can be guided by the question, “How does data analytics contribute to the creation of a smarter service system?” To facilitate answers to this question, we define a smart service system from a data application perspective, and propose a specific approach, serviceoriented data analytics, based on eight case studies related to smart service systems. We introduce an ongoing case study to demonstrate the applicability and utility of our proposals.","PeriodicalId":421680,"journal":{"name":"2016 IEEE 14th International Conference on Industrial Informatics (INDIN)","volume":"844 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116424519","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 : 2016-07-19DOI: 10.1109/INDIN.2016.7819365
T. Brandt, M. Grawunder, Hans-Jürgen Appelrath
Machine Condition Monitoring (MCM) is an important topic for the reliability of industrial machines in increasingly interconnected production facilities. The analysis of a huge amount of data to get information about the machine's condition is a difficult challenge. Current solutions for these analyses are often very specific, need a lot of manual configuration or are difficult to apply. In this paper, we present a system that uses anomaly detection in data streams to find hints for faulty machines in the data. The basis of this system is a Data stream management system (DSMS), which can handle huge amounts of streaming data and simplifies the definition of analyses. Due to the anomaly detection algorithms, the approach can be applied to a variety of data and scenarios. The outcome is a system that allows live analysis of machine data for MCM.
{"title":"Anomaly detection on data streams for machine condition monitoring","authors":"T. Brandt, M. Grawunder, Hans-Jürgen Appelrath","doi":"10.1109/INDIN.2016.7819365","DOIUrl":"https://doi.org/10.1109/INDIN.2016.7819365","url":null,"abstract":"Machine Condition Monitoring (MCM) is an important topic for the reliability of industrial machines in increasingly interconnected production facilities. The analysis of a huge amount of data to get information about the machine's condition is a difficult challenge. Current solutions for these analyses are often very specific, need a lot of manual configuration or are difficult to apply. In this paper, we present a system that uses anomaly detection in data streams to find hints for faulty machines in the data. The basis of this system is a Data stream management system (DSMS), which can handle huge amounts of streaming data and simplifies the definition of analyses. Due to the anomaly detection algorithms, the approach can be applied to a variety of data and scenarios. The outcome is a system that allows live analysis of machine data for MCM.","PeriodicalId":421680,"journal":{"name":"2016 IEEE 14th International Conference on Industrial Informatics (INDIN)","volume":"318 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125776701","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 : 2016-07-19DOI: 10.1109/INDIN.2016.7819179
F. Quintanilla, O. Cardin, A. L'Anton, P. Castagna
This work intends to introduce a new implementation framework, based on the classical holonic paradigm, for partly distributing the intelligence surrounding cyber-physical production systems in the cloud. In order to achieve this transfer, an innovative framework is proposed and the interface between local and cloud platform is extensively justified and described. A performance evaluation of this framework is achieved through its implementation on a fully automated industrial-sized assembly line equipped with 6 axis robots. The chosen performance indicator is the volume of data exchanged during production in order to validate the positioning of the interface in the framework. The results show a low volume of messages exchanged through the interface and a distribution of the volume along time making it valuable for further developments.
{"title":"Implementation framework for cloud-based holonic control of cyber-physical production systems","authors":"F. Quintanilla, O. Cardin, A. L'Anton, P. Castagna","doi":"10.1109/INDIN.2016.7819179","DOIUrl":"https://doi.org/10.1109/INDIN.2016.7819179","url":null,"abstract":"This work intends to introduce a new implementation framework, based on the classical holonic paradigm, for partly distributing the intelligence surrounding cyber-physical production systems in the cloud. In order to achieve this transfer, an innovative framework is proposed and the interface between local and cloud platform is extensively justified and described. A performance evaluation of this framework is achieved through its implementation on a fully automated industrial-sized assembly line equipped with 6 axis robots. The chosen performance indicator is the volume of data exchanged during production in order to validate the positioning of the interface in the framework. The results show a low volume of messages exchanged through the interface and a distribution of the volume along time making it valuable for further developments.","PeriodicalId":421680,"journal":{"name":"2016 IEEE 14th International Conference on Industrial Informatics (INDIN)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124674593","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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