@article{4897,
  abstract     = {{Assistance is becoming increasingly relevant in carrying out industrial work in the context of cyber-physical production systems (CPPSs) and Industry 4.0. While assistance in a single task via a single interaction modality has been explored previously, crossdevice interaction could improve the quality of assistance, especially given the concurrent and distributed nature of work in CPPSs. In this paper, we present the theoretical foundations and implementation of MiWSICx (Middleware for Work Support in Industrial Contexts), a middleware that showcases how multiple interactive computing devices such as tablets, smartphones, augmented/virtual reality glasses, and wearables could be combined to provide crossdevice industrial assistance. Based on activity theory, MiWSICx models human work as activities combining multiple users, artifacts, and cyber-physical objects. MiWSICx is developed using the actor model for deployment on a variety of hardware alongside a CPPS to provide multiuser, crossdevice, multiactivity assistance.}},
  author       = {{Dhiman, Hitesh and Röcker, Carsten}},
  issn         = {{2288-4300 }},
  journal      = {{Journal of Computational Design and Engineering}},
  keywords     = {{human–technology interaction, human–computer interaction, crossdevice interaction, cyber-physical systems, assistance, smart factory, middleware, actor model, information system design, industry 4.0}},
  number       = {{1}},
  pages        = {{428--451}},
  publisher    = {{Oxford University Press}},
  title        = {{{Middleware for providing activity-driven assistance in cyber-physical production systems}}},
  doi          = {{10.1093/jcde/qwaa088}},
  volume       = {{8}},
  year         = {{2021}},
}

@inproceedings{238,
  abstract     = {{In future, advancing digitalization will entail extensive change for businesses. To date, there are only sporadically implemented examples of Smart Factories and these are rather technically (specifically information technology) oriented. Phoenix Contact therefore decided to use a tailor-made approach to implement the digital transition towards becoming a Smart Factory. With the participation of the senior management affected, other internal support areas and the works council, an image of the future for the  Smart Factory was developed. Based on the main future processes the appropriate organizational structure was selected and all participants could now be trained in the performance of new tasks. In addition, this allows for technological concepts to be chosen and judiciously incorporated in further stages. In this paper, the “SmartOrg@Combicon” project will be illustrated as the initial phase in the course of Smart Factory implementation.
}},
  author       = {{Dobrzanski, P. and Jungkind, Wilfried}},
  booktitle    = {{Production engineering and management}},
  editor       = {{Villmer, Franz-Josef and Padoano, Elio}},
  isbn         = {{978-3-946856-03-0}},
  keywords     = {{Industry  4.0, Smart  Factory, Digital  transformation, Staff  and  organizational development}},
  location     = {{Lemgo}},
  number       = {{1}},
  pages        = {{147--158}},
  title        = {{{Human Resources and Organizational Development in the Context of Industry 4.0}}},
  year         = {{2018}},
}

@inproceedings{4318,
  abstract     = {{Recent advances in the field of industrial digitization and automation lead to an increasing need for assistance systems to support workers in various fields of activity, such as assembly, logistics and maintenance. Current assistance systems for the maintenance area are usually based on a single visualization technology. However, in our view, this is not practicable in terms of real activities, as these operations involve various subtasks for which different interaction concepts would be advantageous. Therefore, in this paper, we propose a concept for a multi-device assistive system, which combines multiple devices to provide workers with relevant information over different subtasks of a maintenance operation and present our first prototype for such a system.}},
  author       = {{Heinz, Mario and Dhiman, Hitesh and Röcker, Carsten}},
  booktitle    = {{Machine Learning and Knowledge Extraction :Second IFIP TC 5, TC 8/WG 8.4, 8.9, TC 12/WG 12.9 International Cross-Domain Conference, CD-MAKE 2018}},
  editor       = {{Holzinger, Andreas and Kieseberg, Peter and Tjoa, A Min and Weippl, Edgar}},
  isbn         = {{978-3-319-99739-1}},
  keywords     = {{Human-machine-interaction, Multimodal feedback, Assistive systems, Augmented-reality, Smart factory}},
  location     = {{Hamburg}},
  pages        = {{239 -- 247}},
  publisher    = {{Springer}},
  title        = {{{A Multi-Device Assistive System for Industrial Maintenance Operations}}},
  doi          = {{10.1007/978-3-319-99740-7_16}},
  volume       = {{11015}},
  year         = {{2018}},
}

@inproceedings{4324,
  abstract     = {{On the long term, the current wave of digitization and automation in the industrial environment will result in a progressively higher complexity and heterogeneity in the industrial environment. In this context, a growing need arises for the development of digital assistance systems to support workers in various fields of activities. Current systems are generally limited to visualizations and visual feedback. Therefore, in the scope of this paper, we take a look at the major challenges and opportunities for the integration of multimodal feedback systems in today’s and future industrial environments. It shows that the integration of multimodal feedback is subject to a complex combination of technical, user-cenric and legal aspects.}},
  author       = {{Heinz, Mario and Röcker, Carsten}},
  booktitle    = {{Machine Learning and Knowledge Extraction :Second IFIP TC 5, TC 8/WG 8.4, 8.9, TC 12/WG 12.9 International Cross-Domain Conference, CD-MAKE 2018}},
  editor       = {{Holzinger, Andreas and  Kieseberg, Peter and Tjoa, A Min and Weippl, Edgar}},
  isbn         = {{978-3-319-99739-1}},
  keywords     = {{Human-machine-interaction, Multimodal feedback, Assistive systems, Augmented-reality, Smart factory}},
  location     = {{Hamburg}},
  publisher    = {{Springer}},
  title        = {{{Feedback Presentation for Workers in Industrial Environments–Challenges and Opportunities}}},
  doi          = {{10.1007/978-3-319-99740-7_17}},
  volume       = {{11015}},
  year         = {{2018}},
}

@inproceedings{4255,
  abstract     = {{Increasingly, production processes are enabled and controlled by Information Technology (IT), a development being also referred to as “Industry 4.0”. IT thereby contributes to flexible and adaptive production processes, and in this sense factories become “smart factories”. In line with this, IT also more and more supports human workers via various assistance systems. This support aims to both support workers to better execute their tasks and to reduce the effort and time required when working. However, due to the large spectrum of assistance systems, it is hard to acquire an overview and to select an adequate system for a smart factory based on meaningful criteria. We therefore synthesize a set of comparison criteria into a consistent framework and demonstrate the application of our framework by classifying three examples.}},
  author       = {{Fellmann, Michael and Robert, Sebastian and Büttner, Sebastian and Mucha, Henrik and Röcker, Carsten}},
  booktitle    = {{ Machine Learning and Knowledge Extraction : First IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio, Italy, August 29 – September 1, 2017, Proceedings}},
  editor       = {{Holzinger, Andreas}},
  isbn         = {{978-3-319-66807-9}},
  keywords     = {{Assistance systems, Smart factory, Production processes}},
  location     = {{Reggio, Italy}},
  pages        = {{59--68}},
  publisher    = {{Springer}},
  title        = {{{Towards a Framework for Assistance Systems to Support Work Processes in Smart Factories}}},
  doi          = {{10.1007/978-3-319-66808-6_5}},
  volume       = {{10410}},
  year         = {{2017}},
}