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Factory2Fit
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Publications

ACE Factories White Paper

Human-centred factories from theory to industrial practice. Lessons learned and recommendations

View/Download: ACE Factories White Paper

Contributors:

A4BLUE  http://a4blue.eu/

Patricia Casla, Jon Larreina, IK4-TEKNIKER

Sarah Fletcher, Teegan Johnson, Cranfield University

Laure Parigot, AIRBUS Opérations SAS

Maria del Mar Otero, CESA (a division of Héroux-Devtek)

Tobias Adlon, Aaron Riegauf, RWTH Aachen University

Angelo Marguglio, Engineering Ingegneria Informatica S.p.A.

Factory2Fit  https://factory2fit.eu/

Eija Kaasinen, Susanna Aromaa, Päivi Heikkilä and Anita Honka, VTT

Stylianos Zikos, Georgios Albanis, Maria Tsourma , Anastasios Drosou ,Dimitrios Zarpalas , Petros Daras , Dimitrios Tzovaras, CERTH

Francisco Salgado, David Gutierrez Perez, Menouer Boubekeur, Cemalettin Ozturk, UTRC

Thomas Walter, Continental

Michael Bojko, Sebastian Mach, Ralph Riedel, TUC

Esko Petäjä and Mariia Kreposna, Prima Power

HUMAN  http://www.humanmanufacturing.eu/

Geir Hanssen, SINTEF

Javier Martin, Maria Jose Nunez, AIDIMME

Manuel Oliva Olvera, AIRBUS

Alfio Minissale, COMAU

Joao Costa, Maria Margoudi, Highskillz

Eva Coscia, Stefano Borgia, HOLONIX SRL

Giulio Proface, BioRobotics Institute (IUVO)

Nikos Dimitropoulos, Thodoris Togias, George Michalos, Sotiris Makris, LMS

Cesar Martin, Cesar Taboas, Royo Spain S.L.

Lorenzo Grazi, Nicola Vitiello, SSSA

Andrea Bettoni, Supsi

Simon Julier, UCL

Manuel Oliveira, Felix Mannhardt, KIT-AR

INCLUSIVE  http://www.inclusive-project.eu/

Enrico Callegati, SCM Group

Cesare Fantuzzi, UniMORE

Frieder Loch, TUM

Elisabetta Toschi, Art-ER

Valeria Villani, UniMORE

Dorota Żołnierczyk-Zreda, CIOP-PIB

MANUWORK  http://www.manuwork.eu/

Kosmas Alexopoulos, John Angelopoulos, Prof. Dimitris Mourtzis, LMS

Johan Kildal, IK4-TEKNIKER

Alvaro Segura, Bruno Simões, VICOMTECH

Margarita Anastassova, CEA List

Amit Eytan, We Plus

Masood Fathi, Amos Ng, HIS

Acknowledgments

The research leading to these results received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 723828 for A4BLUE, No. 723277 for Factory2Fit, No. 723737 for HUMAN, No. 723373 for INCLUSIVE and No. 723711 for MANUWORK. Opinions expressed in this publication reflect only the authors’ views.  The European Union is not responsible for any use that may be made of the information contained therein.

The Information at hand-Using wearable devices to display task information in the context of Industry 4.0

Schmalfuß F., Mach S., Kastrau, A. (2018)

DOI: 10.13140/RG.2.2.26144.69121

20th International Conference on Human-Computer Interaction (HCI) – Las Vegas (NV, USA) – 15th – 20th July 2018

Abstract:

Wearable technology for support of the workers is a widely discussed and investigated topic in today’s research and industry. As an interface between human and automation, the advantage of wearable devices, such as smartwatches, lies in the possibility of a location independent, direct worker-machine communication and allows fast as well as personalized notification in case of an important work-related event. Smartwatches provide the options to alert the user via vibration, sound or visual signals. This study contributes to current research by examining, which modality is suitable in an industrial environment.

More information is available at: http://2018.hci.international/

I feel you -Tactile notifications via wearable devices in the industrial environment of the future

Mach, S., Schmalfuß, F. , Roßner, M. and Krems, J.F. (2019)

DOI: 10.13140/RG.2.2.25202.56004

Chemnitz University of Technology, Department of Cognitive and Engineering Psychology¹ & Department of Factory Planning and Factory Management².

View/Download: https://www.researchgate.net/publication/333776031_I_feel_you_-Tactile_notifications_via_wearable_devices_in_the_industrial_environment_of_the_future

Technikaffinität als Ressource für die Arbeit in Industrie 4.0

Attig, C., Mach, S., Wessel, D., Franke, T., Schmalfuß, F. and Krems, J.F.

Technikaffinität als Ressource für die Arbeit in Industrie 4.0

https://doi.org/10.14464/awic.v3i0.251

Abstract: 

Die zunehmende Digitalisierung der Arbeitswelt bietet nicht nur vielversprechende Innovationen zur arbeiterzentrierten, adaptiven Aufgabengestaltung, sondern stellt den Einzelnen auch vor die Herausforderung, in höherem Maße mit digitaler Technik zu interagieren. Für die erfolgreiche Interaktion mit Technik sind zwei Faktoren ausschlaggebend: Wissen über bzw. Erfahrung mit technischen Systemen sowie Persönlichkeitsaspekte, die sich als Interaktionsstil im Umgang mit Technik manifestieren. Wir präsentieren das Konzept der interaktionsbezogenen Technikaffinität (affinity for technology interaction, ATI) als zentrale Ressource zum erfolgreichen Umgang mit Technik, und mit der ATI-Skala eine ökonomische und reliable Skala zur Quantifizierung der ATI eines Nutzers. Neben bestehenden Evaluationsergebnissen (N > 1500) stellen wir erste Ergebnisse einer Nutzerstudie vor, die im Rahmen des Projektes Factory2Fit durchgeführt wurde. Die Probanden interagierten mit 3D-Druckern und erlebten unterschiedliche Automatisierungsgrade des Prozesses. Zusätzlich zum Automatisierungsgrad wurde die Erfahrung der Probanden durch unterschiedliche Trainingsintensitäten variiert. Die Ergebnisse liefern erste Hinweise auf die Relevanz von ATI für die Vorhersage des Interaktionserfolgs mit Technologie und damit für Usability-Evaluationen in Industrie 4.0-Umgebungen.

The publication is available here: https://www.bibliothek.tu-chemnitz.de/ojs/index.php/awlC/article/view/251/113

Unterschiedliche Verfahrung zur Messung von Workload am Arbeitsplatz: Ein Methodenvergleich

Mach, S., Gründling, J.P., Schmalfuß, F. and Krems, J.F.

Unterschiedliche Verfahrung zur Messung von Workload am
Arbeitsplatz: Ein Methodenvergleich. In: Schütz, A.C. et al. (eds.) Abstracts of the 60th Conference of Experimental Psychologists. Lengerich: Pabst Science Publishers.

Abstract

Trotz zunehmender Digitalisierung und Vernetzung im Rahmen von Industrie 4.0 wird auch zukünftig
der Industriearbeiter eine wichtige Rolle spielen. Im Forschungsprojekt „Factory2Fit“ (gefördert durch
die EU im Rahmen von Horizon2020, Vertragsnummer 723277) werden Automatisierungslösungen
für die Fabrik der Zukunft entwickelt, bei denen der Arbeiter im Zentrum steht. Dabei sollen über eine
Schnittstelle von Mensch und Automation die Bedürfnisse und Präferenzen der Mitarbeiter in Echtzeit
berücksichtigt werden. Ein Zugang stellt die Erfassung psychischer Zustände mittels Fragebögen dar.
Als Schnittstelle soll eine Smartwatch verwendet werden. In einem ersten Experiment untersuchten wir
die Übereinstimmung verschiedener Darstellungsformen des NASA-TLX, präsentiert als
Papierfragebogen und als Anzeige auf der Smartwatch. Neunundzwanzig Probanden mussten
kontinuierliche Kopfrechenaufgaben mit drei unterschiedlichen Schwierigkeitsstufen bearbeiten.
Nach jeder Aufgabe wurde der NASA-TLX ausgefüllt, wobei variiert wurde zwischen der Eingabe
über die Lünette der Smartwatch, über Touch-Eingabe und dem Ausfüllen in Papierform. Die
Ergebnisse zeigten einen signifikant niedrigeren Mentalen Workload Score bei der Papierversion im
Vergleich zur Lünetten- bzw. Touch-Eingabe. Jedoch konnten die relativen Unterschiede zwischen
den verschiedenen Aufgabenschwierigkeitsgraden in jeder Bedingung adäquat abgebildet werden.
Die Befragung via Smartwatch eignet sich somit, um zwischen unterschiedlichem Mentalen
Workload differenzieren zu können und besitzt damit großes Potenzial für den Online-Einsatz im
Industrieumfeld.

The abstract can be found here: https://www.psycharchives.org/handle/20.500.12034/712

Information at Hand – Using Wearable Devices to Display Task Information in the Context of Industry 4.0

Mach, S., Kastrau, A. and Schmalfuß, F.  (2018)

Information at Hand – Using Wearable Devices to Display Task Information in the Context of Industry 4.0. In: Stephanidis C. (eds) HCI International 2018 – Posters’ Extended Abstracts. HCI 2018. Communications in Computer and Information Science, vol 850. Springer, Cham.

Click to access 10.1007%2F978-3-319-92270-6_13.pdf

Abstract: 

Abstract In the context of Industry 4.0 and the extensive interconnection of every part of the production process, the industrial worker will still maintain a key role. It is important to support the workers by utilizing ongoing digitalization at work and also to provide suitable concepts for communication between human and automation. A possible solution could be the application of wearable devices such as smartwatches. They are able to automatically collect data about the state of the worker as well as provide relevant information for the worker about the status of machines. The aim of the present research is to investigate whether smartwatches are a suitable alternative to conventional methods of displaying information in an industrial environment – despite some limitations of smartwatches, like the small screen. Therefore, we conducted a laboratory study displaying different amount of information (a list of six tasks vs. only the next task) on different devices (monitor screen vs. smartwatch screen). We asked 32 participants to follow the displayed instructions and fulfill the tasks (crossword puzzles, Sudoku, number connection task). Afterwards, the participants rated the different types of information display with questionnaires (e.g., User Experience Questionnaire). Results show significant differences in some aspects of user experience supporting the advantage of utilizing smartwatches in an industrial context. However, information on a smartwatch should be as short and meaningful as possible.

The publication is available here: https://link.springer.com/chapter/10.1007/978-3-319-92270-6_13

10th International Conference on Applied Human Factors and Ergonomics (AHFE 2019)

Mach, S.¹, Schmalfuß, F. ¹, Bojko2, M., Riedel, R. ², Kreusslein, M. ¹, Beggiato, M. ¹ & Krems, J.F. ¹

Chemnitz University of Technology, Department of Cognitive and Engineering Psychology¹ & Department of Factory Planning and Factory Management².

View/Download: AHFE 2019 academic poster_Final.

More information is available at:
https://www.ahfe2019.org/

Gamification concepts for leveraging knowledge sharing in Industry 4.0.

Tsourma M., Zikos S., Albanis G., Apostolakis K. C., Lithoxoidou E. E., Drosou A., Zarpalas D., Daras P., & Tzovaras, D.  (2019)

Gamification concepts for leveraging knowledge sharing in Industry 4.0. In: International Journal of Serious Games,  2019, Vol. 6(2), pp.75 – 87. https://doi.org/10.17083/ijsg.v6i2.273

Abstract: 

This paper presents gamification concepts implemented by a gamification engine which is incorporated in a knowledge sharing web-based application. The engine aims at increasing user’s motivation and participation in knowledge sharing and training processes taking place on a factory’s shop floor, enhance socialization and support corrective feedback and positive reinforcement. In particular, it motivates workers to participate in discussions, propose solutions to work-related problems, and upload/view useful content even when being at the workplace. The gamification engine makes use of various gamification elements and is highly configurable in terms of management of gamified tasks. It is designed to support access by both standard display devices (PCs, tablets, mobile phones) as well as Mixed/Augmented Reality platforms, such as Microsoft HoloLens, which are gaining significant traction with industry verticals. The main novelty of the gamification concepts presented is the ability to utilize dynamic worker profile information which is stored in a central database, in order to improve the effectiveness of the gamified tasks, targeting at more effective usage of the knowledge sharing platform in the Industry 4.0 domain.

The publication is available here: http://journal.seriousgamessociety.org/index.php/IJSG/article/view/273

User Acceptance Evaluation of a Gamified Knowledge Sharing Platform for Use in Industrial Environments

Zikos S., Tsourma M., Lithoxoidou E. E., Drosou A., Ioannidis D., & Tzovaras, D. (2019)

User Acceptance Evaluation of a Gamified Knowledge Sharing Platform for Use in Industrial Environments. In: International Journal of Serious Games, 2019, Vol. 6(2), pp.89 – 108. DOI: https://doi.org/10.17083/ijsg.v6i2.275

Abstract

This study evaluates user acceptance of a gamification-enabled collaboration and knowledge sharing platform that has been developed for use by personnel in industrial work environments, aiming at increasing motivation for knowledge exchange. The platform has been evaluated at two manufacturing industries by two groups of users, workers and supervisors, with regard to five criteria: usability, knowledge integration, working experience, user acceptance and overall impact. Results showed that even though the ratings from both industries were positive on all criteria, there is room for improvement on user acceptance and knowledge integration. Driven by this fact, a rule-based adaptive gamification approach which exploits information about workers is proposed in order to further increase motivation and engagement. Based on feedback received from the evaluation, guidelines related to functionalities and design of a gamified collaboration platform are provided. These guidelines can be followed when implementing collaboration tools with gamification support for industrial environments.

For more information, find the full publication here: http://journal.seriousgamessociety.org/index.php/IJSG/article/view/275

Empowering and Engaging Industrial Workers with Operator 4.0 Solutions

Kaasinen E., Liinasuo M., Schmalfuß F., Koskinen H., Aromaa S., Heikkilä P., Honka A., Mach S., Malm, T., (2019)

A Worker-Centric Design and Evaluation Framework for Operator 4.0 Solutions that Support Work Well-Being. In: Barricelli B. et al. (eds) Human Work Interaction Design. Designing Engaging Automation. HWID 2018. IFIP Advances in Information and Communication Technology, vol 544. Springer, Cham. ISBN: 978-3-030-05297-3, DOI: https://doi.org/10.1007/978-3-030-05297-3_18

Abstract: 

Future factory work is developing towards knowledge work, making it more demanding but also more enriched and flexible. The change described as Operator 4.0 has high potential to increase work well-being but it will require careful design of future factory tools and work practices focusing on the worker point of view. We introduce a design and evaluation framework that supports design, evaluation and impact assessment activities that target at Operator 4.0 solutions with a positive impact on work well-being.

The publication is available here:   https://link.springer.com/chapter/10.1007/978-3-030-05297-3_18 

IFIP Working Conference on Human Work Interaction Design

Kaasinen E., Schmalfuß F., Özturk C., Aromaa S., Boubekeuer M., Heilala J., Heikkilä P., Kuula T., Liinasuo M., Mach S., Mehta R., Petäjä E., Walter, T. (2019)

Empowering and engaging industrial workers with Operator 4.0 solutions, In: Computers & Industrial Engineering, 2019, Elsevier, ISSN 0360-8352, DOI: doi.org/10.1016/j.cie.2019.01.052.

Abstract

Industry 4.0 has potential for qualitative enrichment of factory work: a more interesting working environment, greater autonomy and opportunities for self-development. A central element of Industry 4.0 is human-centricity, described as development towards Operator 4.0. Our Operator 4.0 vision includes smart factories of the future that are perfectly suited for workers with different skills, capabilities and preferences. The vision is achieved by solutions that empower the workers and engage the work community. Empowering the worker is based on adapting the factory shop floor to the skills, capabilities and needs of the worker and supporting the worker to understand and to develop his/her competence. Engaging the work community is based on tools, with which the workers can participate in designing their work and training, and share their knowledge with each other. We gathered requirements from three manufacturing companies in different industries and interviewed 44 workers in four factories in order to study their expectations and concerns related to the proposed Operator 4.0 solutions. Adaptation was considered useful both in manufacturing systems and in production planning. However, worker measuring and modelling raised many doubts within workers and also with factory management. Therefore it is important to provide early demonstrations of the ideas and to design them further with the workers in order to find acceptable and ethically sustainable ways for worker modelling. The workers would like to be more involved in the design of the work place and manufacturing processes, and they thought that participation would decrease many problems that they currently face in their work. However, there were also doubts concerning whether they really could have possibilities to impact on their work. The results show that there are clear needs for knowledge sharing and adaptive learning solutions that would support personalized competence development and learning while working. An easily accessible platform for knowledge sharing could evolve to a forum where good work practices and ways to solve problems are shared not only within the work community, but also with machine providers and other stakeholders. The interviewees saw the virtual factory as a promising platform for participatory design and training.

For more information, find the full publication here: www.sciencedirect.com/science/article/pii/S036083521930066X?via%3Dihub 

User Evaluation of Industry 4.0 Concepts for Worker Engagement

Aromaa S., Liinasuo M., Kaasinen E., Bojko M., Schmalfuß F., Apostolakis K.C., Zarpalas D., Daras P., Özturk C., Boubekeuer M. (2018)

User Evaluation of Industry 4.0 Concepts for Worker Engagement. In: Human Systems Engineering and Design. IHSED 2018. Advances in Intelligent Systems and Computing, vol 876, pp. 34-40. Springer, Cham. ISBN: 978-3-030-02053-8, DOI: https://doi.org/10.1007/978-3-030-02053-8_6

Abstract:

Industry is undergoing a digital transition that will change the design and setup of human-machine systems. One part of this change is increasing possibilities of workers to influence their work. In this paper, we present four components of the Factory2Fit project that contribute to this change by engaging workers: (1) knowledge sharing and collaboration via a discussion platform; (2) visualisation of information via augmented reality (AR) glasses; (3) participatory design of workplaces and tasks by means of a 3D simulation software programme, and (4) an on-site training tool utilising a training platform. The demonstrators were evaluated with workers to identify foreseen benefits, challenges and impact on their work. Most of the concepts seem to be well accepted and they have high potential to improve work well-being and work performance. The results of this study are encouraging, but long-term field studies with actual prototypes will be needed to evolve the concepts.

The publication is available here: https://link.springer.com/chapter/10.1007/978-3-030-02053-8_6

Quantified Factory Worker – Designing a Worker Feedback Dashboard

Heikkilä P., Honka A., Kaasinen E. (2018)

Quantified Factory Worker – Designing a Worker Feedback Dashboard, In: NordiCHI ’18: 10th Nordic Conference on Human-Computer Interaction – Proceedings, N.10, pp. 515-523. ACM Press. New York, New York, USA, ISBN 978-1-4503-6437-9 DOI: 10.1145/3240167.3240187

Abstract:

Factory work is changing towards knowledge work, demanding problem-solving skills and managing complexity. Providing factory workers the possibility to receive meaningful self-tracking feedback at work, could empower them to cope better with the increasing complexity of their work. We apply the Quantified Self approach to factory work by introducing the concept and prototype of a Worker Feedback Dashboard, which presents various automatically tracked well-being and work performance metrics to workers. Based on user interviews, we created user experience goals for the Dashboard, and identified the following design implications: Keep positive (but truthful), Give personal feedback, Enable reflection, and Do not disturb the worker. After designing the prototype, we studied its user acceptance. Even though the interviewed factory workers’ first reactions to tracking personal metrics at work were rather negative, the attitudes became more positive after presenting the prototype. The results encourage implementing the Worker Feedback Dashboard prototype to a functional application.

The publication is available here: https://dl.acm.org/citation.cfm?id=3240187

Quantified Factory Worker – Expert Evaluation and Ethical Considerations of Wearable Self-tracking Devices

Heikkilä P., Honka A., Mach S., Schmalfuß F., Kaasinen E., Väänänen K. (2018)

Quantified Factory Worker – Expert Evaluation and Ethical Considerations of Wearable Self-tracking Devices. In: Mindtrek ’18 – 22nd International Academic Mindtrek Conference – Proceedings, No. 22, p202-211. ACM Press. New York, New York, USA,  ISBN: 9781450365895, DOI: https://doi.org/10.1145/3275116.3275119

Abstract: 

Following the Quantified Self trend, everyday self-tracking practices have become common. Still, self-monitoring of people at work is a rather new research topic. Self-tracking of employees’ activities, mental state and emotions enables data-based feedback, which could improve the employees’ awareness of issues influencing their well-being and performance. We contribute to this topic from two perspectives. First, we explored the potential of wearable self-tracking devices for providing personal feedback to machine operators working in a factory. We used the expert evaluation method to lay ground to the user perspective of self-tracking at work. User experience experts evaluated five tracking devices for their user experience, perceived accuracy and fit to factory workers. Second, we conducted a workshop with the experts to systematically assess the ethical considerations that may arise when adopting self-tracking at work. The results provide insights into the potential of the use of self-tracking devices in a factory context.

The publication is available here: https://dl.acm.org/citation.cfm?id=3275119

The 2nd International Symposium on Small-scale Intelligent Manufacturing Systems

Tsourma M., Zikos S., Drosou A., Tzovaras D. (2018)

Online task distribution simulation in smart factories, In: 2018 2nd International Symposium on Small-scale Intelligent Manufacturing Systems (SIMS), Cavan, 2018, pp. 1-6.

ISBN: 978-1-5386-4437-9, DOI: 10.1109/SIMS.2018.8355301

Abstract:

Resource management and allocation is an important issue for industries that want to manage their time correctly and allocate their resources effectively and efficiently, without lowering productivity. This paper presents a Task Distribution Engine (TDE) aiming to automate and optimize the task scheduling and resource assignment procedure in industrial environments. The presented engine includes an interactive user interface and supports both real-time and simulation modes, though this work focuses mainly on the simulation mode. Simulation mode provides efficiency, training familiarization, evaluation of the workload and the schedule of each shift and has the advantage of simulating events occurring on the shop floor. A constrained optimization method, which employs hard and soft constraints of various criteria, is applied, in order to evaluate different solutions and select the one with the maximum score. Case study results demonstrate that the simulation functionality of the task distribution engine is useful for determining the importance of parameters considered when assigning tasks.

The publication is available here: https://ieeexplore.ieee.org/document/8355301

INCOM2018 Conference

Chen X., Bojko M,. Riedel R., Apostolakis K. C., Zarpalas D., Daras P., (2018)

Human-centred Adaptation and Task Distribution utilizing Levels of Automation.  In: Marco Macchi, László Monostori, Roberto Pinto (Eds.): 16th IFAC Symposium on Information Control Problems in Manufacturing INCOM 2018, Bergamo, Italy, 11–13 June 2018, Proceedings, S. 54-59. – International Federation of Automatic Control (IFAC), IFAC Proceedings Volumes (IFAC-PapersOnline), Volume 51, Issue 11, 2018, ISSN 2405-8963, DOI: 10.1016/j.ifacol.2018.08.234

Abstract:

Considered as one of the key enablers of smart factories, human-machine adaptation and improved task distribution plays an important role for the realization of effectiveness, efficiency and satisfaction of factory staff. In this paper, with a view to the researches and practices related to the common results of automation adaptation, existing approaches have been revealed as being too general to be put into practice, or being focused too detailed on one industry and therefore cannot be imposed in others. With this in mind, an applicable concept is developed for the setup of an adaptation system, which stems from the EU funded Factory2Fit research project. Within the proposed concept, production automation levels are captured and defined to adapt to the skills and experience of the user. An adaptation engine with human-centered automation is further designed. Based on this, a demonstrator with the scenario of an automobile supplier company is established, which helps to validate the approach proposed within the paper.

The publication is available here: https://doi.org/10.1016/j.ifacol.2018.08.234

The 51st Congress of the German Psychological Society (DGPs), Frankfurt, Germany, 15-20 September 2018

Schmalfuß F., Mach S., Bojko M., Riedel R., Krems J, F., (2018)

Presentation on the ‘Effects of automation level, training and preferences on well-being, subjective workload and performance in the working context’

See the full presentation at: https://www.dgpskongress.de/

Factory2Fit at HCI International 2018

Mach S., Kastrau A., Schmalfuß F. (2018)

Information at Hand – Using Wearable Devices to Display Task Information in the Context of Industry 4.0. In: Stephanidis C. (eds) HCI International 2018 – Posters’ Extended Abstracts. HCI 2018. Communications in Computer and Information Science, vol 850. Springer, Cham.

Abstract

In the context of Industry 4.0 and the extensive interconnection of every part of the production process, the industrial worker will still maintain a key role. It is important to support the workers by utilizing ongoing digitalization at work and also to provide suitable concepts for communication between human and automation. A possible solution could be the application of wearable devices such as smartwatches. They are able to automatically collect data about the state of the worker as well as provide relevant information for the worker about the status of machines. The aim of the present research is to investigate whether smartwatches are a suitable alternative to conventional methods of displaying information in an industrial environment – despite some limitations of smartwatches, like the small screen. Therefore, we conducted a laboratory study displaying different amount of information (a list of six tasks vs. only the next task) on different devices (monitor screen vs. smartwatch screen). We asked 32 participants to follow the displayed instructions and fulfil the tasks (crossword puzzles, Sudoku, number connection task). Afterwards, the participants rated the different types of information display with questionnaires (e.g., User Experience Questionnaire). Results show significant differences in some aspects of user experience supporting the advantage of utilizing smartwatches in an industrial context. However, information on a smartwatch should be as short and meaningful as possible.

The extended abstract of the poster is available here:
https://doi.org/10.1007/978-3-319-92270-6_13

TeaP 2018: 60th Conference of Experimental Psychologists – Abstracts

Mach S., Gründling J.P., Schmalfuß F., Krems J.F. (2018)

Different Ways to Measure Workload at the Workplace: A Methodology Comparison, In: TeaP 2018: 60th Conference of Experimental Psychologists – Abstracts. Pabst Science Publishers. Chemnitz, Germany. DOI: http://dx.doi.org/10.23668/psycharchives.913

The publication is available here:  https://www.psycharchives.org/static/pdfjs/web/viewer.html?file=/bitstream/20.500.12034/712/1/TeaP_2018_Abstracts_20180308.pdf

Technical Affinity as a Resource for Working in Industry 4.0

Attig C., Mach S., Wessel D., Franke T., Schmalfuß F., Krems J.F. (2018)

Technical affinity as a resource for working in Industry 4.0, In: Innteract, 2018, Vol.3. Wissenschaft und Praxis. Chemnitz, Germany, ISSN 2569-3468, DOI: 10.14464/awic.v3i0.251

Abstract

The increasing digitization of the workplace not only offers promising innovations for worker-centered, adaptive task design, but also challenges individuals to interact more with digital technology. Two factors are decisive for the successful interaction with technology: knowledge about or experience with technical systems as well as aspects of personality that manifest themselves as an interaction style in dealing with technology. We present the concept of affinity for technology interaction (ATI) as a central resource for the successful use of technology, and the ATI scale, an economical and reliable scale for quantifying a user’s ATI. In addition to existing evaluation results ( N> 1500) we present the first results of a user study, which was carried out as part of the Factory2Fit project. The subjects interacted with 3D printers and experienced different degrees of automation of the process. In addition to the degree of automation, the experience of the subjects was varied by different training intensities. The results provide first indications of the relevance of ATI for predicting the success of interaction with technology and thus for usability evaluations in Industrie 4.0 environments.

For more information, find the full publication here: https://www.bibliothek.tu-chemnitz.de/ojs/index.php/awlC/article/view/251ww.sciencedirect.com/science/article/pii/S036083521930066X?via%3Dihub 

TBI2017 Conference – Tage des Betriebs- und Systemingenieurs

Bojko M., Riedel R., Chen X., Müller E. (2017)

Factory2Fit – Empowerment und partizipative Anpassung der Fabrikautomation an die Bedürfnisse der Arbeitnehmer. In: Müller, Egon (Ed.): Arbeitswelten 4.0 – Chancen, Herausforderungen, Lösungen. 16. Tage des Betriebs- und Systemingenieurs – TBI2017. Chemnitz: TU Chemnitz, Wissenschaftliche Schriftenreihe des Institutes für Betriebswissenschaften und Fabriksysteme, Sonderheft 23, S. 361-369, 2017, ISSN 0947-2495

Abstract

The European manufacturing industry is facing major changes driven by increasing customer demand for customised and / or smart products, Industry 4.0 solutions, the opening up of process chains for newcomers as well as the shift to value chains, where the roles of suppliers, manufacturers and retailers are blurred. This dynamically changing environment requires adaptability of employees, production tools and processes. New ICT-based solutions facilitate a paradigm shift that sees factory workers as future “knowledge workers” in smart factories and that cannot succeed only by introducing new technologies into factories. Workflows need to be redesigned and new approaches for continuous development are needed. When shifting work tasks to knowledge work, the adaptation of work environments increasingly requires consideration of differences in cognitive abilities. The Factory2Fit research project presented in this paper aims to take human-centered manufacturing to a new level by giving employees a leadership role in adapting and developing their own tasks. The main goal of the project is to develop and pilot adaptive automation solutions that improve the workflow, help employees develop their skills, empower employees to share knowledge and participate in designing their own work.

The publication is available here (in German):
http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-230572 (CC-BY 4.0 OA License)

More information on the conference is available here (in German):
https://www.tu-chemnitz.de/mb/FabrPlan/tagung.php

Factory2fit at the 2017 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)

Zioulis N., Papachristou A., Zarpalas D., Daras P. (2017)

Improving Camera Pose Estimation via Temporal EWA Surfel Splatting, In: 2017 IEEE International Symposium on Mixed and Augmented Reality (ISMAR), Nantes, 2017, pp. 1-10.
doi: 10.1109/ISMAR.2017.17

Abstract:

Camera pose estimation is a fundamental problem of Augmented Reality and 3D reconstruction systems. Recently, despite the new better performing direct methods being developed, state-of-the-art methods are still estimating erroneous poses due to sensor noise, environmental conditions and challenging trajectories. Adding a back-end mapping process, SLAM systems achieve better performance and are more robust, but require higher computational resources, limiting their applicability. Therefore, lighter solutions to improve the accuracy of pose estimates are required. In this work we demonstrate the effectiveness of lighter data structures, namely surface elements, and exploit the temporality of sensor data streams to accumulate moving camera frames and improve tracking. This representation allows us to splat a photometric and geometric model simultaneously and use it to improve the performance of dense RGB-D camera pose estimation methods. Exploiting Elliptical Weighted Average splatting to produce high quality photometric results also allows us to detect erroneous poses through a novel visual quality analysis process. We show evidence of the EWA temporal model’s effectiveness in publicly available datasets and argue that point-based representations are a good candidate for building lighter systems that should be further explored.

For more information, find the full paper here

Potential of Wearable Devices for Mental Workload Detection in Different Physiological Activity Conditions

Schmalfuß, F., Mach, S., Klüber, K., Habelt, B., Beggiato, M., Körner, A., & Krems, J. F. (2017)

Potential of Wearable Devices for Mental Workload Detection in Different Physiological Activity Conditions, In: Proceedings of the Human Factors and Ergonomics Society Europe Chapter 2017 Annual Conference, Rome, Italy. HFES Press. 2017, ISSN 2333-4959

Abstract

Wearable devices have gained high popularity in the last years, especially for health
monitoring. Some devices aim at identifying mental states, but scientific studies on
the potential of wearable devices for identifying mental states are rather sparse.
Heart rate parameters proved to be valuable indicators for increasing mental
workload and growing levels of physical activity. The question arises, if wearable
devices can be used to identify high mental workload in different physiological
activity conditions. Thirty-two participants (18 female) participated in an experiment
with a 2 (mental workload) x 4 (physiological activity) factorial within-subject
design. Participants sat, stood, stepped or cycled while they fulfilled either no
secondary task (5 minutes) or a counting backwards task (5 minutes). Heart Rate
was measured via a wrist-worn mobile device and a stationary device. Results
showed that measurements of the two devices did not correlate consistently. Heart
Rate and Inter-Beat Intervals, measured via the stationary device differed
significantly with varying levels of physical activity and mental workload. Data
from the wearable device showed only the physical activity effect. Findings indicate
that wearable devices are not fully capable of identifying mental workload. Still,
wearable devices have potential for identifying and fostering reduction of high
physical load in everyday usage.

The full publication is available here: https://www.hfes-europe.org/wp-content/uploads/2017/10/Schmalfuss2017.pdf

Psychological View on Demands and Potentials for Industrial Workers in Times of Industry 4.0

Mach, S. (2017)

Psychological view on demands and potentials for industrial workers in times of Industry 4.0, In: 3rd Berlin Summer School Human Factors 2017 – Proceedings, Nr.14, MMI-Interaktiv. Berlin, Germany 2017, ISSN: 1439-7854

For more information, find the full paper here: http://www.mmi-interaktiv.de/fileadmin/mmi-interaktiv.de/Ausgabe_14/BSSHF_Proceedings.pdf

Herbstkonferenz der Gesellschaft für Arbeitswissenschaft, Chemnitz

The autumn conference of the Society for Ergonomics in Chemnitz

Riedel, Ralph; Schmalfuß, Franziska; Bojko, Michael; Mach, Sebastian:
Flexible Automatisierung in Abhängigkeit von Mitarbeiterkompetenzen und –beanspruchung. In: Gesellschaft für Arbeitswissenschaft e.V. (Hrsg.): Dokumentation der Herbstkonferenz der Gesellschaft für Arbeitswissenschaft e.V.; 28. und 29. September 2017 in Chemnitz; Dortmund: GfA-Press, 2017; ISBN 978-3-936804-23-2

Abstract

Industry 4.0 and current developments in the field of manufacturing companies require high adaptability of people and machines alike. Smart factories turn production workers into knowledge workers. In addition to new, intelligent, technical solutions, this also requires new approaches to work organisation and training as well as qualification concepts that flexibly work together with adaptable technical systems. The EU-funded Factory2Fit project develops solutions for human-machine interaction in automated production systems that provide a high level of adaptability to the skills, competencies and preferences of individual employees, while meeting the challenges of highly customised production. This paper presents the basic goals and ideas of the project as well as the approaches of the quantified self in the working context, the adaptive automation including the different levels of automation and the specific application of participatory design. In the next steps of the project, it is important to implement and validate these concepts. The interdisciplinary approach and the close contact between scientific, development and application partners should help to successfully meet the challenges of the realisation and to implement future-oriented smart factory solutions.

The publication is available here (in German):
http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-231812 (Copyright: GfA-Press)

8th International Conference on Applied Human Factors and Ergonomics (AHFE)

Factory2Fit was represented at the 8th International Conference on Applied Human Factors and Ergonomics (AHFE), held at the Westin Bonaventure Hotel in Los Angeles, California 17th-21st July 2017.

The conference objective was to provide an international forum for the dissemination and exchange of scientific information on theoretical, generic, and applied areas of human factors and ergonomics. The conference comprised a keynote presentation, parallel sessions, demonstration and poster sessions, tutorials, exhibitions, and meetings of special interest groups.

Professor Josef Krems from Factory2Fit partner organisation Chemnitz University of Technology (TUC) participated in the conference. On July 20th, Professor Krems along with his team held an interactive poster demonstration where they introduced Factory2Fit.

The poster, authored by Sebastian Mach, Franziska Schmalfuß, Matthias Beggiato and Professor Krems from the Department of Cognitive and Engineering Psychology at TUC, presented the requirements for implementing worker-centred design.

More information is available at: ahfe2017.org

Human Factors and Ergonomics Society European Chapter’ (HFES) Conference

The conference ‘Human Factors and Ergonomics Society European Chapter’ (HFES) was held in Rome from 28-30 September 2017 (http://www.hfes-europe.org/annual-meeting/).

The topic of this year’s conference was ‘Varieties of interaction: from user experience to neuroergonomics’.

Franziska Schmalfuß from Factory2Fit partner organisation Chemnitz University of Technology (TUC) presented research on the detection of mental workload using wearable devices and exchanged experiences with other researchers interested in the same topic.

Conference participants were very interested in the Factory2Fit project and the other presentations and posters gave us much food for thought for our future research.

Factory2Fit

Empowering and participatory adaptation of factory automation to fit for workers

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Acknowledgement

Numerous images used on this site are © Continental GmBH and are used with permission. All rights reserved. No unauthorised reproduction permitted without written consent.

The Factory2Fit project has received funding from Horizon 2020 (H2020/2014-2020), the European Union’s Programme for Research and Innovation under grant agreement n° 723277

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