Pub Date : 2019-07-01DOI: 10.1109/indin41052.2019.8972183
{"title":"Low Power Smart Sensing for the Industry 4.0","authors":"","doi":"10.1109/indin41052.2019.8972183","DOIUrl":"https://doi.org/10.1109/indin41052.2019.8972183","url":null,"abstract":"","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125671253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/INDIN41052.2019.8972327
Dominik Flick, S. Gellrich, M. Filz, Li Ji, S. Thiede, C. Herrmann
The manufacturing industry today is experiencing a never seen increase in available data. These data compromise a variety of different formats, semantics, and quality. It is often distributed in different data sources, e.g. sensor data from the production line, environmental data or machine tool parameters. Coming from the field of application the paper will discuss, within a conceptual framework, the possibilities of how to integrate the diverse existing data-sources and how to pre-process the data with high quality using advanced outlier detection algorithms and developing reasonable outlier treatment values by applying machine-learning methods. The result will be validated with real manufacturing data from an automotive use-case.
{"title":"Conceptual Framework for manufacturing data preprocessing of diverse input sources","authors":"Dominik Flick, S. Gellrich, M. Filz, Li Ji, S. Thiede, C. Herrmann","doi":"10.1109/INDIN41052.2019.8972327","DOIUrl":"https://doi.org/10.1109/INDIN41052.2019.8972327","url":null,"abstract":"The manufacturing industry today is experiencing a never seen increase in available data. These data compromise a variety of different formats, semantics, and quality. It is often distributed in different data sources, e.g. sensor data from the production line, environmental data or machine tool parameters. Coming from the field of application the paper will discuss, within a conceptual framework, the possibilities of how to integrate the diverse existing data-sources and how to pre-process the data with high quality using advanced outlier detection algorithms and developing reasonable outlier treatment values by applying machine-learning methods. The result will be validated with real manufacturing data from an automotive use-case.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130514759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/INDIN41052.2019.8972193
Jakob Zietsch, N. Weinert, C. Herrmann, S. Thiede
Because the Edge Computing (EC) paradigm allows processing of vast amounts of data in proximity to the respective source, latency and quantity constraints are no longer a limiting factor. That enables the development of novel data-driven applications and the extension of the solutions space for value-added services in production. The complexity and diversity of factories, combined with the continuing discovery of new data-driven solutions, poses a challenge for practitioners to thoroughly determine where, which, and how data should be processed. This, however, is crucial for deciding how and whether to invest in EC. This paper proposes a multiphase concept for the systematic assessment of whether and where EC is most beneficial in a given production environment. It is comprised of human and machine interpretable functions. Combining multiple functions leads to a data-driven solution, which forms links between the data sources (assets) of a production environment and the desired outcome (goals). Four main criteria for EC are derived to enable the exposure of areas with increased EC potential, forming the baseline for a scoring system. The concept is designed so that its application is feasible within an industrial context. First analyses show the prospect of the approach and suggest potential benefits for providing practical implementation guidance.
{"title":"Edge Computing for the Production Industry A Systematic Approach to Enable Decision Support and Planning of Edge","authors":"Jakob Zietsch, N. Weinert, C. Herrmann, S. Thiede","doi":"10.1109/INDIN41052.2019.8972193","DOIUrl":"https://doi.org/10.1109/INDIN41052.2019.8972193","url":null,"abstract":"Because the Edge Computing (EC) paradigm allows processing of vast amounts of data in proximity to the respective source, latency and quantity constraints are no longer a limiting factor. That enables the development of novel data-driven applications and the extension of the solutions space for value-added services in production. The complexity and diversity of factories, combined with the continuing discovery of new data-driven solutions, poses a challenge for practitioners to thoroughly determine where, which, and how data should be processed. This, however, is crucial for deciding how and whether to invest in EC. This paper proposes a multiphase concept for the systematic assessment of whether and where EC is most beneficial in a given production environment. It is comprised of human and machine interpretable functions. Combining multiple functions leads to a data-driven solution, which forms links between the data sources (assets) of a production environment and the desired outcome (goals). Four main criteria for EC are derived to enable the exposure of areas with increased EC potential, forming the baseline for a scoring system. The concept is designed so that its application is feasible within an industrial context. First analyses show the prospect of the approach and suggest potential benefits for providing practical implementation guidance.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"511 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130555310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/INDIN41052.2019.8972139
M. H. Tahir, Mehdi Mahmoodpour, A. Lobov
In order to stay competitive in the global market, industrial manufacturers are implementing various methods to improve the production processes. This requires measuring important metrics and making use of performance measurement systems. Based on the data generated in manufacturing operations, various indicators can be defined and measured. These indicators serve as the basis for decision-making, control and health monitoring of a manufacturing process. In this paper an approach is presented that makes use of key performance indicators (KPIs). The KPIs used are defined in a standard known as, ISO 22400 Automation systems and integration-Key performance indicators (KPIs) that is usually applied for management of manufacturing operations. The approach uses the database of a production line to define KPIs and generates a tool for visualizing them. The KPIs are defined using a data model of Key Performance Indicator Markup Language (KPI-ML), which is an XML utilization of the ISO 22400 standard. The recommended approach paves a way for constructing generic KPI-ML visualization tools serving various industries to assess their performance with the same tool.
{"title":"KPI-ML based integration of industrial information systems","authors":"M. H. Tahir, Mehdi Mahmoodpour, A. Lobov","doi":"10.1109/INDIN41052.2019.8972139","DOIUrl":"https://doi.org/10.1109/INDIN41052.2019.8972139","url":null,"abstract":"In order to stay competitive in the global market, industrial manufacturers are implementing various methods to improve the production processes. This requires measuring important metrics and making use of performance measurement systems. Based on the data generated in manufacturing operations, various indicators can be defined and measured. These indicators serve as the basis for decision-making, control and health monitoring of a manufacturing process. In this paper an approach is presented that makes use of key performance indicators (KPIs). The KPIs used are defined in a standard known as, ISO 22400 Automation systems and integration-Key performance indicators (KPIs) that is usually applied for management of manufacturing operations. The approach uses the database of a production line to define KPIs and generates a tool for visualizing them. The KPIs are defined using a data model of Key Performance Indicator Markup Language (KPI-ML), which is an XML utilization of the ISO 22400 standard. The recommended approach paves a way for constructing generic KPI-ML visualization tools serving various industries to assess their performance with the same tool.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130875695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/INDIN41052.2019.8972131
Z. Chew, Tingwen Ruan, M. Zhu
This paper presents strategies for batteryless energy harvesting powered wireless sensor nodes based on IEEE 802.15.4e standard to join the network successfully with minimal attempts, which minimizes energy wastage. This includes using a well-sized capacitor and different duty cycles for the network joining. Experimental results showed a wireless sensor node that uses a 100 mF energy storage capacitor can usually join the network in one attempt but multiple attempts may be needed if it uses smaller capacitances especially when the harvested power is low. With a duty-cycled network joining, the time required to form a network is shorter, which reduces the overall energy usage of the nodes in joining the network. An energy harvesting powered wireless sensor network (WSN) was successfully formed in one attempt by using the proposed methods.
{"title":"Energy Harvesting Powered Wireless Sensor Nodes With Energy Efficient Network Joining Strategies","authors":"Z. Chew, Tingwen Ruan, M. Zhu","doi":"10.1109/INDIN41052.2019.8972131","DOIUrl":"https://doi.org/10.1109/INDIN41052.2019.8972131","url":null,"abstract":"This paper presents strategies for batteryless energy harvesting powered wireless sensor nodes based on IEEE 802.15.4e standard to join the network successfully with minimal attempts, which minimizes energy wastage. This includes using a well-sized capacitor and different duty cycles for the network joining. Experimental results showed a wireless sensor node that uses a 100 mF energy storage capacitor can usually join the network in one attempt but multiple attempts may be needed if it uses smaller capacitances especially when the harvested power is low. With a duty-cycled network joining, the time required to form a network is shorter, which reduces the overall energy usage of the nodes in joining the network. An energy harvesting powered wireless sensor network (WSN) was successfully formed in one attempt by using the proposed methods.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126235868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/INDIN41052.2019.8972247
Frieder Loch, Saskia Böck, M. Zou, B. Vogel‐Heuser
Integration of older employees into the workforce is critical for a successful manufacturing industry due to demographic change. However, technological developments to create more flexible manufacturing environments are leading to increasingly complex machinery that has to be operated by an aging workforce. Virtual training systems prepare operators for the interaction with industrial machines. Current virtual training systems do not address the perceptive and cognitive abilities of older users to enable a satisfying and efficient training. This article develops adaptations of the visualization and the interaction techniques of a virtual training system to address the abilities of older operators. The results of a between-subjects study indicate that the adaptations improve the subjective perception of the training system and decrease the training time. The paper concludes that adaptive training systems can support the participation of diverse user groups in the manufacturing industry by providing more effective and satisfying training.
{"title":"Adapting Virtual Training Systems for Industrial Procedures to the Needs of Older People","authors":"Frieder Loch, Saskia Böck, M. Zou, B. Vogel‐Heuser","doi":"10.1109/INDIN41052.2019.8972247","DOIUrl":"https://doi.org/10.1109/INDIN41052.2019.8972247","url":null,"abstract":"Integration of older employees into the workforce is critical for a successful manufacturing industry due to demographic change. However, technological developments to create more flexible manufacturing environments are leading to increasingly complex machinery that has to be operated by an aging workforce. Virtual training systems prepare operators for the interaction with industrial machines. Current virtual training systems do not address the perceptive and cognitive abilities of older users to enable a satisfying and efficient training. This article develops adaptations of the visualization and the interaction techniques of a virtual training system to address the abilities of older operators. The results of a between-subjects study indicate that the adaptations improve the subjective perception of the training system and decrease the training time. The paper concludes that adaptive training systems can support the participation of diverse user groups in the manufacturing industry by providing more effective and satisfying training.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120967561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/INDIN41052.2019.8972061
Friedrich Volz, Ljiljana Stojanović, Robin Lamberti
Smart Factory Web is a platform for smart factories to enable flexible sharing and management of assets and resources to maximize efficiency and provide visibility on a global market. To join the Smart Factory Web, participants describe their factory capabilities, which are modelled in an ontology. AutomationML is used to assist with this modelling. OPC UA is used as a communication protocol for factory live-data from the machines. However, factory owners are hesitant to share critical production data. Therefore, the communication has to be secure and in the best case, provide control mechanisms for the data owners. The International Data Space is a peer-to-peer network that will support secure exchange of data and data usage control. In this paper, the Smart Factory Web approach is discussed and extended by an implementation with the current state of the International Data Space.
{"title":"An Industrial Marketplace - the Smart Factory Web Approach and Integration of the International Data Space","authors":"Friedrich Volz, Ljiljana Stojanović, Robin Lamberti","doi":"10.1109/INDIN41052.2019.8972061","DOIUrl":"https://doi.org/10.1109/INDIN41052.2019.8972061","url":null,"abstract":"Smart Factory Web is a platform for smart factories to enable flexible sharing and management of assets and resources to maximize efficiency and provide visibility on a global market. To join the Smart Factory Web, participants describe their factory capabilities, which are modelled in an ontology. AutomationML is used to assist with this modelling. OPC UA is used as a communication protocol for factory live-data from the machines. However, factory owners are hesitant to share critical production data. Therefore, the communication has to be secure and in the best case, provide control mechanisms for the data owners. The International Data Space is a peer-to-peer network that will support secure exchange of data and data usage control. In this paper, the Smart Factory Web approach is discussed and extended by an implementation with the current state of the International Data Space.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131119461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/INDIN41052.2019.8972256
E. Sebastian, A. Sikora, Manuel Schappacher, Zubair Amjad
One of the main requirements of spatially distributed Internet of Things (IoT) solutions is to have networks with wider coverage to connect many low-power devices. Low-Power Wide-Area Networks (LPWAN) and Cellular IoT(cIOT) networks are promising candidates in this space. LPWAN approaches are based on enhanced physical layer (PHY) implementations to achieve long range such as LoRaWAN, SigFox, MIOTY. Narrowband versions of cellular network offer reduced bandwidth and, simplified node and network management mechanisms, such as Narrow Band IoT (NB-IoT) and Long-Term Evolution for Machines (LTE-M). Since the underlying use cases come with various requirements it is essential to perform a comparative analysis of competing technologies. This article provides systematic performance measurement and comparison of LPWAN and NB-IoT technologies in a unified testbed, also discusses the necessity of future fifth generation (5G) LPWAN solutions.
{"title":"Test and Measurement of LPWAN and Cellular IoT Networks in a Unified Testbed","authors":"E. Sebastian, A. Sikora, Manuel Schappacher, Zubair Amjad","doi":"10.1109/INDIN41052.2019.8972256","DOIUrl":"https://doi.org/10.1109/INDIN41052.2019.8972256","url":null,"abstract":"One of the main requirements of spatially distributed Internet of Things (IoT) solutions is to have networks with wider coverage to connect many low-power devices. Low-Power Wide-Area Networks (LPWAN) and Cellular IoT(cIOT) networks are promising candidates in this space. LPWAN approaches are based on enhanced physical layer (PHY) implementations to achieve long range such as LoRaWAN, SigFox, MIOTY. Narrowband versions of cellular network offer reduced bandwidth and, simplified node and network management mechanisms, such as Narrow Band IoT (NB-IoT) and Long-Term Evolution for Machines (LTE-M). Since the underlying use cases come with various requirements it is essential to perform a comparative analysis of competing technologies. This article provides systematic performance measurement and comparison of LPWAN and NB-IoT technologies in a unified testbed, also discusses the necessity of future fifth generation (5G) LPWAN solutions.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131441701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/INDIN41052.2019.8972115
Felix Gehlhoff, Hamied Nabizada, A. Fay
Shorter product lifecycles and increasing product complexity are important trends that drive the need for increased flexibility of production companies. One way to cope with this problem is to engage in flexible production networks where companies can find missing production capabilities and offer their own ones. To enable this connection across company borders and software platforms, an agent-based communication approach is proposed that is based on the OPC UA standard. This paper also develops an optimization concept that can increase a company’s benefits, i.e. profits, by applying a learning algorithm as well as an approach to calculate optimal margins, which is encapsulated in an optimization agent.
{"title":"Optimization of multi-agent auctioning processes in flexible production networks","authors":"Felix Gehlhoff, Hamied Nabizada, A. Fay","doi":"10.1109/INDIN41052.2019.8972115","DOIUrl":"https://doi.org/10.1109/INDIN41052.2019.8972115","url":null,"abstract":"Shorter product lifecycles and increasing product complexity are important trends that drive the need for increased flexibility of production companies. One way to cope with this problem is to engage in flexible production networks where companies can find missing production capabilities and offer their own ones. To enable this connection across company borders and software platforms, an agent-based communication approach is proposed that is based on the OPC UA standard. This paper also develops an optimization concept that can increase a company’s benefits, i.e. profits, by applying a learning algorithm as well as an approach to calculate optimal margins, which is encapsulated in an optimization agent.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"159 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131520709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/INDIN41052.2019.8972211
M. Carratù, S. D. Iacono, A. Pietrosanto, V. Paciello
In this paper a method for IMU and MARG alignment in two wheeled vehicles suspension control system is presented. Nowadays, the initial alignment of the device with respect to the vehicle frame is obtained thanks to algorithms available in literature based on the estimation of the attitude and simple geometrical rules to determine. However, these classical procedures do not allow to obtain a precise measurement of the initial device attitude. The proposed method aims to fuse data between classical methods results and GPS/GNSS signals to improve the existing methodologies. The algorithm has been implemented on a low cost platform to demonstrate its feasibility and it has been tested on a motorcycle during real ride conditions. The performed experiments have demonstrated the repeatability of the procedures and its high accuracy.
{"title":"Self-alignment procedure for IMU in automotive context","authors":"M. Carratù, S. D. Iacono, A. Pietrosanto, V. Paciello","doi":"10.1109/INDIN41052.2019.8972211","DOIUrl":"https://doi.org/10.1109/INDIN41052.2019.8972211","url":null,"abstract":"In this paper a method for IMU and MARG alignment in two wheeled vehicles suspension control system is presented. Nowadays, the initial alignment of the device with respect to the vehicle frame is obtained thanks to algorithms available in literature based on the estimation of the attitude and simple geometrical rules to determine. However, these classical procedures do not allow to obtain a precise measurement of the initial device attitude. The proposed method aims to fuse data between classical methods results and GPS/GNSS signals to improve the existing methodologies. The algorithm has been implemented on a low cost platform to demonstrate its feasibility and it has been tested on a motorcycle during real ride conditions. The performed experiments have demonstrated the repeatability of the procedures and its high accuracy.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121636016","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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