Pub Date : 2017-07-01DOI: 10.1109/INDIN.2017.8104760
Chanipa Sonklin, Maolin Tang, Yu-Chu Tian
The dramatically increasing energy consumption of data centers is an important issue and one of the most efficient ways to tackle the issue is through server consolidation. The basic idea of server consolidation is to move all virtual machines (VMs) to as few energy efficient servers as possible, and then switch off unused servers. Many efficient server consolidation approaches have been proposed and one of the most efficient approaches is to use a Genetic Algorithm (GA) to find an optimal or near-optimal solution to the server consolidation problem. Aiming at reducing the computation time and the number of VM migrations incurred by server consolidation, this paper proposes a Decrease- and-Conquer Genetic Algorithm (DCGA). This DCGA adopts a decrease-and-conquer strategy to decrease the problem size and to decrease the number of VM migrations without significantly compromising the quality of solutions. The DCGA is compared with a classical GA and the most popular approach, namely FFD, for the server consolidation problem by experiments and the experimental results show that the DCGA can find a solution very close to the solution generated by the classical GA with much shorter computation time and incur much less VM migrations for all the test problems, and that the DCGA can generate a much better solution than the FFD.
{"title":"A decrease-and-conquer genetic algorithm for energy efficient virtual machine placement in data centers","authors":"Chanipa Sonklin, Maolin Tang, Yu-Chu Tian","doi":"10.1109/INDIN.2017.8104760","DOIUrl":"https://doi.org/10.1109/INDIN.2017.8104760","url":null,"abstract":"The dramatically increasing energy consumption of data centers is an important issue and one of the most efficient ways to tackle the issue is through server consolidation. The basic idea of server consolidation is to move all virtual machines (VMs) to as few energy efficient servers as possible, and then switch off unused servers. Many efficient server consolidation approaches have been proposed and one of the most efficient approaches is to use a Genetic Algorithm (GA) to find an optimal or near-optimal solution to the server consolidation problem. Aiming at reducing the computation time and the number of VM migrations incurred by server consolidation, this paper proposes a Decrease- and-Conquer Genetic Algorithm (DCGA). This DCGA adopts a decrease-and-conquer strategy to decrease the problem size and to decrease the number of VM migrations without significantly compromising the quality of solutions. The DCGA is compared with a classical GA and the most popular approach, namely FFD, for the server consolidation problem by experiments and the experimental results show that the DCGA can find a solution very close to the solution generated by the classical GA with much shorter computation time and incur much less VM migrations for all the test problems, and that the DCGA can generate a much better solution than the FFD.","PeriodicalId":6595,"journal":{"name":"2017 IEEE 15th International Conference on Industrial Informatics (INDIN)","volume":"9 1","pages":"135-140"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84562138","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 : 2017-07-01DOI: 10.1109/INDIN.2017.8104924
S. Karnouskos, Nadine Gaertner, Nemrude Verzano, Frank Beck, Andre Becker, Santo Bianchino, Daniel Kuntze, M. Pérez-Francisco, R. Roy, Serge F. L. Saelens, Michael Schmut
New Internet of Things open source technologies, middlewares, and programming languages, make the quick integration of devices, systems and cloud services easier than never before. With their utilization, complex tasks such as object detection, tracking and tracing, can be easily realized, even by embedded devices in a fraction of time. The interplay of highly heterogeneous IoT devices and open source software, has been utilized in this work as a learning tool, in order to train developers and enhance their IoT skills. By designing, implementing, testing and deploying a rapid prototype, new knowledge is acquired, assessment of technologies and concepts is carried out, and the end-result, although developed in a constraint timeframe, is technologically promising, cost-effective and feature-rich. This work sheds some light on the prototype implemented and discusses the developer experiences and benefits of this IoT integration hands-on approach.
{"title":"Experiences in integrating Internet of Things and cloud services with the robot operating system","authors":"S. Karnouskos, Nadine Gaertner, Nemrude Verzano, Frank Beck, Andre Becker, Santo Bianchino, Daniel Kuntze, M. Pérez-Francisco, R. Roy, Serge F. L. Saelens, Michael Schmut","doi":"10.1109/INDIN.2017.8104924","DOIUrl":"https://doi.org/10.1109/INDIN.2017.8104924","url":null,"abstract":"New Internet of Things open source technologies, middlewares, and programming languages, make the quick integration of devices, systems and cloud services easier than never before. With their utilization, complex tasks such as object detection, tracking and tracing, can be easily realized, even by embedded devices in a fraction of time. The interplay of highly heterogeneous IoT devices and open source software, has been utilized in this work as a learning tool, in order to train developers and enhance their IoT skills. By designing, implementing, testing and deploying a rapid prototype, new knowledge is acquired, assessment of technologies and concepts is carried out, and the end-result, although developed in a constraint timeframe, is technologically promising, cost-effective and feature-rich. This work sheds some light on the prototype implemented and discusses the developer experiences and benefits of this IoT integration hands-on approach.","PeriodicalId":6595,"journal":{"name":"2017 IEEE 15th International Conference on Industrial Informatics (INDIN)","volume":"11 1","pages":"1084-1089"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80180564","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 : 2017-07-01DOI: 10.1109/INDIN.2017.8104904
Florian Schloegl, Lars Fischer, S. Lehnhoff, R. Rosen, J. C. Wehrstedt
The penetration of production systems and common infrastructure with information and communication technologies (ICT) creates new systems, called Smart Grids in energy or Industry 4.0 in production. This offers unprecedented opportunities for flexible and customized production and distribution. However, these complex and interconnected systems need new approaches for operation. Assistance system similar to those known from the automotive sector will support operators in their task to provide a safe, efficient and undisturbed operation of production systems. The paper supports, that more complex functionalities of assistance systems are based on simulation. This paper discusses the question how well co-simulation approaches are suited for this task. Co-simulation is the joint simulation of independent simulators each representing a component or subsystem of the overall system. The modularity of co-simulation reflects the modularity of production systems. It is possible to compose a simulation by using existing models. It is easy to adapt co-simulation to different configurations of production systems or changes in topology. The inherent flexibility of co-simulation makes it possible to cover broad range of requirements regarding, among others, simulation speed and precision. Co-simulation further allows to include models as “black boxes” which can be used to protect intellectual property on the modeled components. However, co-simulation always comes with additional costs for communication. Data exchange between models sets upper bounds for simulation speed. This limits the application of co-simulation: If requirements on calculation speed are very high other approaches like hybrid simulations are more suitable. For very precise simulations parallel simulation may be appropriate.
{"title":"Co-simulation techniques in assistance systems for process control","authors":"Florian Schloegl, Lars Fischer, S. Lehnhoff, R. Rosen, J. C. Wehrstedt","doi":"10.1109/INDIN.2017.8104904","DOIUrl":"https://doi.org/10.1109/INDIN.2017.8104904","url":null,"abstract":"The penetration of production systems and common infrastructure with information and communication technologies (ICT) creates new systems, called Smart Grids in energy or Industry 4.0 in production. This offers unprecedented opportunities for flexible and customized production and distribution. However, these complex and interconnected systems need new approaches for operation. Assistance system similar to those known from the automotive sector will support operators in their task to provide a safe, efficient and undisturbed operation of production systems. The paper supports, that more complex functionalities of assistance systems are based on simulation. This paper discusses the question how well co-simulation approaches are suited for this task. Co-simulation is the joint simulation of independent simulators each representing a component or subsystem of the overall system. The modularity of co-simulation reflects the modularity of production systems. It is possible to compose a simulation by using existing models. It is easy to adapt co-simulation to different configurations of production systems or changes in topology. The inherent flexibility of co-simulation makes it possible to cover broad range of requirements regarding, among others, simulation speed and precision. Co-simulation further allows to include models as “black boxes” which can be used to protect intellectual property on the modeled components. However, co-simulation always comes with additional costs for communication. Data exchange between models sets upper bounds for simulation speed. This limits the application of co-simulation: If requirements on calculation speed are very high other approaches like hybrid simulations are more suitable. For very precise simulations parallel simulation may be appropriate.","PeriodicalId":6595,"journal":{"name":"2017 IEEE 15th International Conference on Industrial Informatics (INDIN)","volume":"45 1","pages":"971-976"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78815634","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 : 2017-07-01DOI: 10.1109/INDIN.2017.8104776
Dorothea Schwung, Tim Kempe, Andreas Schwung, S. Ding
This paper presents a novel approach to the optimization of energy consumption in large scale industrial bulk good processes. The approach is based on a model-free self-learning algorithm solely based on available process data using ideas from the well known reinforcement learning framework. To this end energy consumers of the plant are integrated in the optimization framework such that each consumer learns its own optimal energy profile for a given production task. The approach is implemented on a laboratory size testbed where the task is the supply of bulk good to a subsequent dosing section. The capability of the approach is underlined by the results obtained at the testbed.
{"title":"Self-optimization of energy consumption in complex bulk good processes using reinforcement learning","authors":"Dorothea Schwung, Tim Kempe, Andreas Schwung, S. Ding","doi":"10.1109/INDIN.2017.8104776","DOIUrl":"https://doi.org/10.1109/INDIN.2017.8104776","url":null,"abstract":"This paper presents a novel approach to the optimization of energy consumption in large scale industrial bulk good processes. The approach is based on a model-free self-learning algorithm solely based on available process data using ideas from the well known reinforcement learning framework. To this end energy consumers of the plant are integrated in the optimization framework such that each consumer learns its own optimal energy profile for a given production task. The approach is implemented on a laboratory size testbed where the task is the supply of bulk good to a subsequent dosing section. The capability of the approach is underlined by the results obtained at the testbed.","PeriodicalId":6595,"journal":{"name":"2017 IEEE 15th International Conference on Industrial Informatics (INDIN)","volume":"64 1","pages":"231-236"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76058807","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 : 2017-07-01DOI: 10.1109/INDIN.2017.8104899
B. Gupta, Nick Rahimi, S. Rahimi, Ashraf Alyanbaawi
In this paper, we have considered a recently reported non-DHT based structured P2P system. The architecture is based on Linear Diophantine Equation (LDE) and it is an interest-based system; it offers very efficient data lookup. However, the architecture is restricted in that a peer cannot possess more than one distinct resource type. This may reduce the scope of its application. In this paper, we have extended the work by considering a generalization of the architecture, that is, a peer can possess multiple distinct resource types. We have proposed an efficient data lookup algorithm with time complexity bounded by (2+r/2); r is the number of distinct resource types. We have discussed about an alternative lookup scheme that needs constant number of hops and constant number of message exchanges. Besides, churn handling and ring maintenance have been shown to be very efficient.
{"title":"Efficient data lookup in non-DHT based low diameter structured P2P network","authors":"B. Gupta, Nick Rahimi, S. Rahimi, Ashraf Alyanbaawi","doi":"10.1109/INDIN.2017.8104899","DOIUrl":"https://doi.org/10.1109/INDIN.2017.8104899","url":null,"abstract":"In this paper, we have considered a recently reported non-DHT based structured P2P system. The architecture is based on Linear Diophantine Equation (LDE) and it is an interest-based system; it offers very efficient data lookup. However, the architecture is restricted in that a peer cannot possess more than one distinct resource type. This may reduce the scope of its application. In this paper, we have extended the work by considering a generalization of the architecture, that is, a peer can possess multiple distinct resource types. We have proposed an efficient data lookup algorithm with time complexity bounded by (2+r/2); r is the number of distinct resource types. We have discussed about an alternative lookup scheme that needs constant number of hops and constant number of message exchanges. Besides, churn handling and ring maintenance have been shown to be very efficient.","PeriodicalId":6595,"journal":{"name":"2017 IEEE 15th International Conference on Industrial Informatics (INDIN)","volume":"74 1","pages":"944-950"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86331780","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 : 2017-07-01DOI: 10.1109/INDIN.2017.8104843
S. Bougouffa, Sebastian Diehm, Michael Schwarz, B. Vogel‐Heuser
During the lifecycle of automated production systems (aPS) additional functionalities and evolutions are realized. As a consequence, control software of aPS becomes highly complex and hard to maintain, which rises the need for evaluating and improving the quality of the control software. Tools for assessing and analyzing the quality of control software are rare and mostly lack accessible platforms that allow the use of analysis data by quality officers and stakeholders. Therefore, this paper presents a cloud platform for code-analysis, a developed tool for evaluating control software by means of Semantic Web technologies. The scalability of the cloud platform supports varied volumes of data and allows efficient use of the analysis data in a continuous integration system for trend analysis in combination with software quality model that can indicate the overall quality level of the control software.
{"title":"Scalable cloud based semantic code analysis to support continuous integration of industrial PLC code","authors":"S. Bougouffa, Sebastian Diehm, Michael Schwarz, B. Vogel‐Heuser","doi":"10.1109/INDIN.2017.8104843","DOIUrl":"https://doi.org/10.1109/INDIN.2017.8104843","url":null,"abstract":"During the lifecycle of automated production systems (aPS) additional functionalities and evolutions are realized. As a consequence, control software of aPS becomes highly complex and hard to maintain, which rises the need for evaluating and improving the quality of the control software. Tools for assessing and analyzing the quality of control software are rare and mostly lack accessible platforms that allow the use of analysis data by quality officers and stakeholders. Therefore, this paper presents a cloud platform for code-analysis, a developed tool for evaluating control software by means of Semantic Web technologies. The scalability of the cloud platform supports varied volumes of data and allows efficient use of the analysis data in a continuous integration system for trend analysis in combination with software quality model that can indicate the overall quality level of the control software.","PeriodicalId":6595,"journal":{"name":"2017 IEEE 15th International Conference on Industrial Informatics (INDIN)","volume":"29 1","pages":"621-627"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83862558","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 : 2017-07-01DOI: 10.1109/INDIN.2017.8104857
Elisabet Estévez-Estévez, F. Pérez, D. Orive, M. Marcos
Nowadays, the constantly changing market demands make modern automation systems offer more strict flexibility and efficiency requirements as energy efficiency, performance optimization and tolerance to process or controllers faults… The introduction of reconfiguration mechanisms within production automation systems allow meeting some of these requirements but, at the same time, they lead more complex design and implementation of the automation system. This paper explores the advantages of Model Driven Engineering techniques to manage such complexity. The proposed approach is based on two well spread standards in the automation field: AutomationML and IEC 61131-3 which have a Markup Language notation (AML and PLCopen XML respectively).
{"title":"A novel approach for flexible automation production systems","authors":"Elisabet Estévez-Estévez, F. Pérez, D. Orive, M. Marcos","doi":"10.1109/INDIN.2017.8104857","DOIUrl":"https://doi.org/10.1109/INDIN.2017.8104857","url":null,"abstract":"Nowadays, the constantly changing market demands make modern automation systems offer more strict flexibility and efficiency requirements as energy efficiency, performance optimization and tolerance to process or controllers faults… The introduction of reconfiguration mechanisms within production automation systems allow meeting some of these requirements but, at the same time, they lead more complex design and implementation of the automation system. This paper explores the advantages of Model Driven Engineering techniques to manage such complexity. The proposed approach is based on two well spread standards in the automation field: AutomationML and IEC 61131-3 which have a Markup Language notation (AML and PLCopen XML respectively).","PeriodicalId":6595,"journal":{"name":"2017 IEEE 15th International Conference on Industrial Informatics (INDIN)","volume":"23 1","pages":"695-699"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83979839","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 : 2017-07-01DOI: 10.1109/INDIN.2017.8104947
K. Adedeji, Y. Hamam, B. Abe, A. Abu-Mahfouz
The analysis of water piping system has been presented by several authors in the past and in recent years proposing several solution algorithms. Among the notable methods are the Hardy cross method, linear approximation method, Newton Raphson method and the hybrid method to mention but a few, to solve a system of partly linear, and partly non-linear hydraulic equations. In this paper, the authors demonstrate the use of Excel solver to verify the Hardy Cross method for the analysis of flow in water piping networks. A single-loop water network derived from real situation was used as numerical example and case study. Detailed numerical data are presented to explain the results of the studied network.
{"title":"A spreadsheet tool for the analysis of flows in small-scale water piping networks","authors":"K. Adedeji, Y. Hamam, B. Abe, A. Abu-Mahfouz","doi":"10.1109/INDIN.2017.8104947","DOIUrl":"https://doi.org/10.1109/INDIN.2017.8104947","url":null,"abstract":"The analysis of water piping system has been presented by several authors in the past and in recent years proposing several solution algorithms. Among the notable methods are the Hardy cross method, linear approximation method, Newton Raphson method and the hybrid method to mention but a few, to solve a system of partly linear, and partly non-linear hydraulic equations. In this paper, the authors demonstrate the use of Excel solver to verify the Hardy Cross method for the analysis of flow in water piping networks. A single-loop water network derived from real situation was used as numerical example and case study. Detailed numerical data are presented to explain the results of the studied network.","PeriodicalId":6595,"journal":{"name":"2017 IEEE 15th International Conference on Industrial Informatics (INDIN)","volume":"12 1","pages":"1213-1218"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82956696","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 : 2017-07-01DOI: 10.1109/INDIN.2017.8104797
Haibo Cheng, Lingling Xue, Peng Wang, P. Zeng, Haibin Yu
This paper presents an approach to enabling ontology-based web service integration for flexible manufacturing systems based on industry 4.0 demonstration production line. The mass personalized customization requires increased agility and flexibility in manufacturing systems to adapt incessant changes in manufacturing environments and requirements. The fundamental for this method lies in the incorporation of knowledge expressed by ontologies concerning order, products, industrial equipment, manufacturing process, event and service. It is a significant method to use ontology for representing manufacturing knowledge in a computer-interpretable way. This knowledge model can be used by automated decision-making to configure the control component that monitors and harmonizes the whole manufacturing system. The semantic model of the flexible manufacturing systems can be automatically updated based on event notifications sent by the specialized web services. The architecture and knowledge model have been demonstrated in a pilot case named industry 4.0 demonstration production line and can be applied to other flexible manufacturing systems.
{"title":"Ontology-based web service integration for flexible manufacturing systems","authors":"Haibo Cheng, Lingling Xue, Peng Wang, P. Zeng, Haibin Yu","doi":"10.1109/INDIN.2017.8104797","DOIUrl":"https://doi.org/10.1109/INDIN.2017.8104797","url":null,"abstract":"This paper presents an approach to enabling ontology-based web service integration for flexible manufacturing systems based on industry 4.0 demonstration production line. The mass personalized customization requires increased agility and flexibility in manufacturing systems to adapt incessant changes in manufacturing environments and requirements. The fundamental for this method lies in the incorporation of knowledge expressed by ontologies concerning order, products, industrial equipment, manufacturing process, event and service. It is a significant method to use ontology for representing manufacturing knowledge in a computer-interpretable way. This knowledge model can be used by automated decision-making to configure the control component that monitors and harmonizes the whole manufacturing system. The semantic model of the flexible manufacturing systems can be automatically updated based on event notifications sent by the specialized web services. The architecture and knowledge model have been demonstrated in a pilot case named industry 4.0 demonstration production line and can be applied to other flexible manufacturing systems.","PeriodicalId":6595,"journal":{"name":"2017 IEEE 15th International Conference on Industrial Informatics (INDIN)","volume":"6 1","pages":"351-356"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86792829","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 : 2017-07-01DOI: 10.1109/INDIN.2017.8104796
Benjamin Brandenbourger, Milan Vathoopan, Alois Zoitl
A technical plant behavior using a functional description forms the basis for common understanding of different disciplines and is used for the draft of hardware and software. Correlations between specific functions of the automation components and system can be allowed or denied in the behavior model describing the tended reaction. This contribution proposes an approach for modeling and verifying formal behavioral constraints of automation systems. The approach is realized either with finite state machines or with regular expressions. Furthermore, this work presents a methodology to convert verbalized constraints into finite state machines or regular expressions. The approach is evaluated by means of a pick & place unit.
{"title":"Modeling and verifying behavioral constraints for automation systems","authors":"Benjamin Brandenbourger, Milan Vathoopan, Alois Zoitl","doi":"10.1109/INDIN.2017.8104796","DOIUrl":"https://doi.org/10.1109/INDIN.2017.8104796","url":null,"abstract":"A technical plant behavior using a functional description forms the basis for common understanding of different disciplines and is used for the draft of hardware and software. Correlations between specific functions of the automation components and system can be allowed or denied in the behavior model describing the tended reaction. This contribution proposes an approach for modeling and verifying formal behavioral constraints of automation systems. The approach is realized either with finite state machines or with regular expressions. Furthermore, this work presents a methodology to convert verbalized constraints into finite state machines or regular expressions. The approach is evaluated by means of a pick & place unit.","PeriodicalId":6595,"journal":{"name":"2017 IEEE 15th International Conference on Industrial Informatics (INDIN)","volume":"25 1","pages":"345-350"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89115672","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：