@inproceedings{4761,
  abstract     = {{Maintenance is an important set of various activities related to preserving from failure or decline. Improper or lack of maintenance may result in excessive component wear, production quality deterioration, or even longer downtime. However, today's production facilities strive to devote the least amount of necessary maintenance time in order to maximize production time. Therefore, new solutions for deliberate and efficient maintenance are needed. The solution proposed in this paper benefits from the newest trends and innovations in industry, namely the Asset Administration Shell (AAS) which is part of the Industrie 4.0 (I4.0) concept. The AAS shall contain the maintenance submodel which shall be used for supporting humans during the maintenance process. The submodel provides a standardized description of required tools and parts as well as step-by-step instructions which also include safety concerns and multimedia files, such as pictures and videos. In this way, maintenance can be carried out more reliably, resulting in reduced downtime. In addition, feedback from the maintenance process shall be stored in the submodel and fed through an I4.0-compliant network to other processes from different phases of the life cycle in order to improve them.}},
  author       = {{Lang, Dorota and Grunau, Sergej and Wisniewski, Lukasz and Jasperneite, Jürgen}},
  booktitle    = {{17th International Conference on Industrial Informatics (IEEE-INDIN 2019)}},
  isbn         = {{978-1-7281-2928-0 }},
  issn         = {{1935-4576}},
  keywords     = {{maintenance, Asset Administration Shell}},
  location     = {{Helsinki-Espoo, Finland}},
  pages        = {{768--773}},
  publisher    = {{IEEE}},
  title        = {{{Utilization of the Asset Administration Shell to Support Humans During the Maintenance Process}}},
  doi          = {{10.1109/indin41052.2019.8972236}},
  year         = {{2019}},
}

@inproceedings{4327,
  abstract     = {{In ever changing world, the industrial systems become more and more complex. Machine feedback in the form of alarms and notifications, due to its growing volume, becomes overwhelming for the operator. In addition, expectations in relation to system availability are growing as well. Therefore, there exists strong need for new solutions guaranteeing fast troubleshooting of problems that arise during system operation. The approach proposed in this study uses advantages of the Asset Administration Shell, machine learning, and human-machine interaction in order to create the assistance system which holistically addresses the issue of troubleshooting complex industrial systems.}},
  author       = {{Lang, Dorota and Wunderlich, Paul and Heinz, Mario and Wisniewski, Lukasz and Jasperneite, Jürgen and Niggemann, Oliver and Röcker, Carsten}},
  booktitle    = {{14th IEEE International Workshop on Factory Communication Systems (WFCS)}},
  keywords     = {{Maintenance engineering, Adaptation models, Machine learning, Data models, Standards, Software, Bayes methods}},
  location     = {{Imperia, Italy }},
  publisher    = {{IEEE}},
  title        = {{{Assistance System to Support Troubleshooting of Complex Industrial Systems}}},
  doi          = {{10.1109/WFCS.2018.8402380}},
  year         = {{2018}},
}

@inproceedings{4600,
  author       = {{Ali Khan, Waqas and Wisniewski, Lukasz and Lang, Dorota and Jasperneite, Jürgen}},
  booktitle    = {{26th IEEE International Symposium on Industrial Electronics (ISIE 2017)}},
  title        = {{{Analysis of the Requirements for offering Industrie 4.0 applications as a Cloud Service }}},
  year         = {{2017}},
}

@inproceedings{4601,
  author       = {{Ehrlich, Marco and Trsek, Henning and Lang, Dorota and Wisniewski, Lukasz and Wendt, Verena and Jasperneite, Jürgen}},
  booktitle    = {{Automation 2017}},
  pages        = {{1}},
  publisher    = {{VDI}},
  title        = {{{Security Concept for a Cloud-based Automation Service}}},
  year         = {{2017}},
}