@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{4102, abstract = {{Complexity is a fundamental part of product design and manufacturing today, owing to increased demands for customization and advances in digital design techniques. Assembling and repairing such an enormous variety of components means that workers are cognitively challenged, take longer to search for the relevant information and are prone to making mistakes. Although in recent years deep learning approaches to object recognition have seen rapid advances, the combined potential of deep learning and augmented reality in the industrial domain remains relatively under explored. In this paper we introduce AR-ProMO, a combined hardware/software solution that provides a generalizable assistance system for identifying mistakes during product assembly and repair.}}, author = {{Dhiman, Hitesh and Büttner, Sebastian and Röcker, Carsten and Reisch, Raphael}}, booktitle = {{Proceedings of the 31st Australian Conference on Human-Computer-Interaction (OzCHI'19) : 2nd Dec.-5th Dec. 2019, Perth/Fremantle, WA, Australia}}, isbn = {{978-1-4503-7696-9}}, keywords = {{Augmented Reality, Deep Learning}}, location = {{Perth/Fremantle, WA, Australia}}, pages = {{ 518–522}}, publisher = {{ACM}}, title = {{{Handling Work Complexity with AR/Deep Learning}}}, doi = {{10.1145/3369457.3370919}}, year = {{2019}}, } @inproceedings{4310, abstract = {{It is generally acknowledged that technological innovation is leading to an increase in the complexity of industrial work. Hence, work assistance has emerged as an important theme in the context of cyber-physical production systems and Industry 4.0 to assist workers in assembly, logistics, maintenance and supervision. Recent research in this domain has focused on demonstrating assistance applications using mobile computing devices such as tablets, smartphones, AR/VR glasses and wearables, but the aspects of technology induced complexity in industrial work distribution, concurrency, information complexity, and variability of information interaction, and their subsequent effect on human workers is yet to be tackled. This paper has two core contributions: first, it reframes the problem of complex industrial work through activity theory, which leads to a conceptual model that couples human information needs to interactive artefacts within an activity context. Second, the problem of assistance is viewed as managing information flow between multiple devices grouped into fluid and adaptive activity contexts, managed by MiWSICx, (Middleware for Work Support in Industrial Contexts) a novel, distributed middleware designed using the actor model of concurrent computation.}}, author = {{Dhiman, Hitesh and Röcker, Carsten}}, booktitle = {{Proceedings of the International Congress and Conferences on Computational Design and Engineering (i3CDE'19), Penang, Malaysia, pp. 407 - 416}}, location = {{Penang, Malaysia}}, title = {{{Middleware for Work Support in Industrial Contexts (MiWSICx)}}}, year = {{2019}}, } @inbook{4311, abstract = {{Recent trends towards digitization in the industrial domain are also driving profound socio-technical changes. On the one hand, these technologies enable shorter product lifecycles and servitization, but on the other hand, the increasing technical complexity of the equipment makes its operation and maintenance a challenge for workers. Assistance systems using pervasive technologies can bridge the gap between the abilities of the workers and the demands of handling technical complexity by enriching workplace activities with relevant, context-dependent information. In this paper, we present an application that replaces a conventional, paper-based maintenance manual with digital, Augmented Reality based instructions that are delivered at the appropriate place and time.}}, author = {{Dhiman, Hitesh and Röcker, Carsten}}, booktitle = {{2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)}}, isbn = {{978-1-5386-9151-9}}, keywords = {{Industry 4.0, Cyber Physical Systems, Augmented Reality, Complexity, Maintenance, HoloLens}}, location = {{Kyoto, Japan}}, pages = {{95 -- 100}}, publisher = {{IEEE}}, title = {{{Worker Assistance in Smart Production Environments using Pervasive Technologies}}}, doi = {{10.1109/PERCOMW.2019.8730771}}, year = {{2019}}, } @inproceedings{4315, 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 tech- nology. However, in our view, this is not practicable in terms of real activities, as these operations involve various subtasks for which different interaction con- cepts 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 = {{International Cross-Domain Conference for Machine Learning and Knowledge Extraction}}, location = {{Canterbury, United Kingdom.}}, publisher = {{Springer}}, title = {{{A Multi-Device Assistive System for Industrial Maintenance Operations}}}, year = {{2019}}, } @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{4319, abstract = {{With the introduction of intelligent and autonomous systems into factory environments, workplaces where human employees work alongside digital counterparts will become increasingly informational. We develop a generic framework for hypothetical workplaces to investigate how complexities create to uncertainties. Complexity may be explained through the Level of Abstractions used to model a system, and it is encountered in its dynamic form as an alteration of information flow between agents in a phenomenological relationship. Analyzing these systems as ‘information flows’ brings to light the uncertainity(ies) the workers of the future will have to cope with. We develop first concepts that can be used to develop heuristics to manage these uncertainties in complex manufacturing environments. These heuristics may also be useful in creating optimized workplaces that combine the individual abilities of both humans and machines. The framework proposed in this paper may be subject for an empirical validation of these heuristics in the future.}}, author = {{Dhiman, Hitesh and Plewe, D. A. and Röcker, Carsten}}, booktitle = {{Advances in Manufacturing, Production Management and Process Control}}, editor = {{Karwowski, Waldemar and Trzcielinski, Stefan and Mrugalska, Beata and Di Nicolantonio, Massimo}}, isbn = {{978-3-319-94195-0}}, keywords = {{Uncertainties, Complexity, Human-machine interaction}}, location = {{Orlando, Florida, USA}}, pages = {{103+114}}, publisher = {{Springer}}, title = {{{Addressing Uncertainties in Complex Manufacturing Environments: A Multidisciplinary Approach}}}, doi = {{10.1007/978-3-319-94196-7_10}}, volume = {{793}}, year = {{2018}}, } @inproceedings{4323, abstract = {{The latest generation of head-mounted displays such as HoloLens pro- vide mixed reality capabilities that claim to better integrate the real and virtual worlds. In this paper, we would like the share our experiences in implementing a user interface for an assembly assistance system using the HoloLens. We carried out a preliminary evaluation of the applicability of mixed reality using the per- spective of developers and expert users in an assembly scenario that allows us to operate and compare two interfaces - a state-of-the-art projector display system and the HoloLens. We believe our findings may contribute towards a better un- derstanding of the effects of new display technologies such as the HoloLens in developing and using assistance systems in other fields as well. Areas that may be of future research are also highlighted.}}, author = {{Dhiman, Hitesh and Martinez, Sascha and Paelke, Volker and Röcker, Carsten}}, booktitle = {{HCI in Business, Government, and Organizations}}, editor = {{Fui-Hoon Nah, Fiona and Sophia Xiao, Bo}}, isbn = {{978-3-319-91715-3}}, keywords = {{Human machine interaction, Assembly assistance system, Qualitative study, HoloLens}}, location = {{Las Vegas, NV, USA}}, pages = {{67--78}}, publisher = {{Springer}}, title = {{{Head-Mounted Displays in Industrial AR-Applications: Ready for Prime Time?}}}, doi = {{10.1007/978-3-319-91716-0_6}}, volume = {{10923}}, year = {{2018}}, } @inproceedings{4325, abstract = {{With the introduction of intelligent and autonomous systems into factory environments, workplaces where human employees work alongside digital counterparts will become increasingly informational. We develop a generic framework for hypothetical workplaces to investigate how complexities create to uncertainties. Complexity may be explained through the Level of Abstractions used to model a system, and it is encountered in its dynamic form as an alteration of information flow between agents in a phenomenological relationship. Analyzing these systems as ‘information flows’ brings to light the uncertainity(ies) the workers of the future will have to cope with. We develop first concepts that can be used to develop heuristics to manage these uncertainties in complex manufacturing environments. These heuristics may also be useful in creating optimized workplaces that combine the individual abilities of both humans and machines. The framework proposed in this paper may be subject for an empirical validation of these heuristics in the future. }}, author = {{Dhiman, Hitesh and Plewe, D. A. and Röcker, Carsten}}, booktitle = {{International Conference on Applied Human Factors and Ergonomics}}, isbn = {{978-3-319-94195-0}}, keywords = {{Uncertainties, Complexity, Human-machine interaction}}, location = {{Orlando, Florida, USA}}, pages = {{ 103--114}}, publisher = {{Springer}}, title = {{{Addressing Uncertainties in Complex Manufacturing Environments: A Multidisciplinary Approach}}}, doi = {{10.1007/978-3-319-94196-7_10}}, volume = {{793}}, year = {{2018}}, }