Abstract
The demand for customized products increases, leading to smaller product volumes and batch sizes, down to batch size one. The necessary flexibility and variety places high demands on assembly and increases the complexity. Therefore, the automation of manual assembly processes is often not cost-effective. To cope with these basic conditions, workers in the manual assembly should be supported cognitively by informational assistance systems. In addition to the typical product- and process-related aspects, adaptable human-centered functionalities must be considered, aiming to improve productivity, quality, workers’ health, and motivation. Thus, this paper examines the assistance functionalities that future assistance systems should provide for manual assembly processes and presents approaches for their implementation. Design Science Research is the framework for our research activities. The starting point is the analysis of existing assembly assistance systems and a determination of process optimization potentials. Through interviews with experts and the modeling of a manual assembly process, we determine the support dimensions and required functionalities for future assistance systems. Subsequently, the overall system architecture and the subsystems are designed and implemented. Intelligent image processing and deep learning algorithms are the basis for process progress recognition and analysis of the ergonomic situation. Gamification and augmented reality are further methods used. The processual changes resulting from the application of the presented novel assistance system are modeled in a case study, and the optimized aspects and implications for both workers and companies are discussed.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
ElMaraghy, H., et al.: Product variety management. CIRP Ann – Manuf. Technol. 62, 629–652 (2013). https://doi.org/10.1016/j.cirp.2013.05.007
Scholz-Reiter, B., Freitag, M.: Autonomous processes in assembly systems. CIRP Ann. 56, 712–729 (2007). https://doi.org/10.1016/j.cirp.2007.10.002
Harari, N.S., Fundin, A., Carlsson, A.L.: Components of the design process of flexible and reconfigurable assembly systems. Procedia Manuf. 25, 549–556 (2018). https://doi.org/10.1016/j.promfg.2018.06.118
Müller, R., Vette-Steinkamp, M., Hörauf, L., Speicher, C., Bashir, A.: Worker centered cognitive assistance for dynamically created repairing jobs in rework area. Procedia CIRP 72, 141–146 (2018). https://doi.org/10.1016/j.procir.2018.03.137
Andrianakos, G., et al.: An approach for monitoring the execution human based assembly operations using machine learning. Procedia CIRP 86, 198–203 (2020). https://doi.org/10.1016/j.procir.2020.01.040
Faccio, M., Ferrari, E., Galizia, F.G., Gamberi, M., Pilati, F.: Real-time assistance to manual assembly through depth camera and visual feedback. Procedia CIRP 81, 1254–1259 (2019). https://doi.org/10.1016/j.procir.2019.03.303
Keller, T., Bayer, C., Bausch, P., Metternich, J.: Benefit evaluation of digital assistance systems for assembly workstations. Procedia CIRP 81, 441–446 (2019). https://doi.org/10.1016/j.procir.2019.03.076
Lampen, E., Teuber, J., Gaisbauer, F., Bär, T., Pfeiffer, T., Wachsmuth, S.: Combining simulation and augmented reality methods for enhanced worker assistance in manual assembly. Procedia CIRP 81, 588–659 (2019). https://doi.org/10.1016/j.procir.2019.03.160
Hinrichsen, S., Bendzioch, S.: How digital assistance systems improve work productivity in assembly. In: Nunes, I.L. (ed.) AHFE 2018. AISC, vol. 781, pp. 332–342. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-94334-3_33
Petzoldt, C., Keiser, D., Beinke, T., Freitag, M.: Requirements for an incentive-based assistance system for manual assembly. In: Freitag, M., Haasis, H.-D., Kotzab, H., Pannek, J. (eds.) LDIC 2020. LNL, pp. 541–553. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-44783-0_50
Sochor, R., Kraus, L., Merkel, L., Braunreuther, S., Reinhart, G.: Approach to increase worker acceptance of cognitive assistance systems in manual assembly. Procedia CIRP 81, 926–931 (2019). https://doi.org/10.1016/j.procir.2019.03.229
Hevner, A.R., March, S.T., Park, J., Ram, S.: Design science in information systems research. Manag. Inf. Syst. Q. (MIS Q.) 28, 75–105 (2004). https://doi.org/10.2307/25148625
Peffers, K., Tuunanen, T., Rothenberger, M.A., Chatterjee, S.: A design science research methodology for information systems research. J. Manag. Inf. Syst. 24, 45–77 (2007). https://doi.org/10.2753/mis0742-1222240302
Chinosi, M., Trombetta, A.: BPMN: an introduction to the standard. Comput. Stand Interfaces 34, 124–134 (2012). https://doi.org/10.1016/j.csi.2011.06.002
Asadi, N., Jackson, M., Fundin, A.: Drivers of complexity in a flexible assembly system- a case study. Procedia CIRP 41, 189–194 (2016). https://doi.org/10.1016/j.procir.2015.12.082
VDMA Maschinen- und Anlagenbau Kompetenzmatrix der Assistenzsysteme (2018). https://www.vdma.org/v2viewer/-/v2article/render/26008848. Accessed 20 Feb 2020
Bundesministerium für Gesundheit Betriebliche Gesundheitsförderung – Vorteile (2019). https://www.bundesgesundheitsministerium.de/themen/praevention/betriebliche-gesundheitsfoerderung/vorteile.html. Accessed 30 Sep 2019
Resnick, M.L., Zanotti, A.: Using ergonomics to target productivity improvements. Comput. Ind. Eng. 33, 185–188 (1997). https://doi.org/10.1016/s0360-8352(97)00070-3
Eklund, J.A.E.: Relationships between ergonomics and quality in assembly work. Appl. Ergon. 26, 15–22 (1995). https://doi.org/10.1016/0003-6870(95)95747-n
Lin, L., Drury, C.G., Kim, S.W.: Ergonomics and quality in paced assembly lines. Hum. Factors Ergon. Manuf. 11, 377–382 (2001). https://doi.org/10.1002/hfm.1020
Bornewasser, M., Bläsing, D., Hinrichsen, S.: Informatorische Assistenzsysteme in der manuellen Montage: Ein nützliches Werkzeug zur Reduktion mentaler Beanspruchung? Zeitschrift für Arbeitswissenschaft 72(4), 264–275 (2018). https://doi.org/10.1007/s41449-018-0123-x
Hemphälä, H., Eklund, J.: A visual ergonomics intervention in mail sorting facilities: effects on eyes, muscles and productivity. Appl. Ergon. 43, 217–229 (2012). https://doi.org/10.1016/j.apergo.2011.05.006
Carlopio, J.R., Gardner, D.: Direct and interactive effects of the physical work environment on attitudes. Environ. Behav. 24, 579–601 (1992)
Moore, S.M., Torma-Krajewski, J., Steiner, L.J.: Practical demonstrations of ergonomic principles. Rep. Invest. 9684(2011–191), 1–57 (2011)
DIN EN ISO 6385. Ergonomics principles in the design of work systems (ISO 6385:2016); German version EN ISO 6385:2016 (2016)
Daub, U., Gawlick, S., Blab, F.: Ergonomische Arbeitsplatzgestaltung: Prinzipien aus Trainings-, Sport- und Arbeitswissenschaft zur Entlastung des Bewegungsapparates. Stuttgart (2018)
DIN EN 12464-1. Light and lighting - Lighting of work places - Part 1: Indoor work places; German version EN 12464-1:2011 (2011)
Fraunhofer, I.P.A., Daub, U.: Ergonomic Assembly 4.0 (2017)
Funk, M., Kosch, T., Kettner, R., Korn, O., Schmidt, A.: motionEAP: an overview of 4 years of combining industrial assembly with augmented reality for industry 4.0. In: Proceedings of 16th International Conference Knowledge Technologies and Data-driven Business, pp. 2–5 (2016)
Fraunhofer IOSB-INA, Röcker C: XTEND Assistance System (2018)
Arkite, B.V.: ARKITE Human Interface Mate (2016). https://www.arkite.be/him/. Accessed 24 Feb 2020
Lange, W., Windel, A.: Kleine Ergonomische Datensammlung, 16th edn. TÜV Media GmbH, Dortmund (2017)
Claeys, A., Hoedt, S., Van Landeghem, H., Cottyn, J.: Generic model for managing context-aware assembly instructions. IFAC-PapersOnLine 49, 1181–1186 (2016). https://doi.org/10.1016/j.ifacol.2016.07.666
Mattsson, S., Fast-Berglund, L.D.: Evaluation of guidelines for assembly instructions. IFAC-PapersOnLine 49, 209–214 (2016). https://doi.org/10.1016/j.ifacol.2016.07.598
Korn, O.: Context-Aware Assistive Systems for Augmented Work . A Framework Using Gamification and Projection. Universität Stuttgart (2014)
Hinrichsen, D., Riediger, D., Unrau, A.: Assistance systems in manual assembly. In: Production Engineering and Management. 6th International Conference. OWL University of Applied Sciences, Lemgo, pp. 3–14 (2016)
DIN 33402-2. Ergonomics - Human body dimensions - Part 2: Values, Corrigenda to DIN 33402-2:2005-12 (2007)
Zare, M., Bodin, J., Cercier, E., Brunet, R., Roquelaure, Y.: Evaluation of ergonomic approach and musculoskeletal disorders in two different organizations in a truck assembly plant. Int. J. Ind. Ergon. 50, 34–42 (2015). https://doi.org/10.1016/j.ergon.2015.09.009
Romero, D., et al.: Towards an operator 4.0 typology: a human-centric perspective on the fourth industrial revolution technologies. In: International Conference on Computers & Industrial Engineering (CIE46), Tianjin, China, pp. 1–11 (2016)
Schuldt, J., Friedemann, S.: The challenges of gamification in the age of industry 4.0: focusing on man in future machine-driven working environments. In: IEEE Global Engineering Education Conference, EDUCON, pp 1622–1630. IEEE Computer Society (2017)
Koivisto, J., Hamari, J.: Demographic differences in perceived benefits from gamification. Comput. Hum. Behav. 35, 179–188 (2014). https://doi.org/10.1016/j.chb.2014.03.007
Beinke, T., Freitag, M., Schamann, A., Feldmann, K.: Beruflich-betriebliche Weiterbildung 4.0 - Gamification im E-Learning in Verbindung mit individueller Spieleapplikation für die mitarbeiterorientierte Weiterbildung der Zukunft. Ind. 4.0 Manag. 35, 13–17 (2019). https://doi.org/10.1016/j.enavi.2017.05.006
Keiser, D., Petzoldt, C., Beinke, T., Freitag, M.: Einsatz von Gamification zur Motivationssteigerung in manuellen Montageassistenzsystemen - Methodik zur Auswahl geeigneter Spiel-Design-Elemente. Ind. 4.0 Manag. 38, 49–52 (2020)
Karbasi, M., et al.: Real-Time Hand detection by depth images: a survey. J. Teknol. 78 (2016). https://doi.org/10.11113/jt.v78.5292
Kinali, G., Kara, S., Yıldırım, M.S.: Electromyographic analysis of an ergonomic risk factor: overhead work. J. Phys. Ther. Sci. 28, 1924–1927 (2016). https://doi.org/10.1589/jpts.28.1924
Lowe, B.D., et al.: Evaluation of a workplace exercise program for control of shoulder disorders in overhead assembly work. J. Occup. Environ. Med. 59, 563–570 (2017). https://doi.org/10.1097/jom.0000000000001030
Sood, D., Nussbaum, M.A., Hager, K.: Fatigue during prolonged intermittent overhead work: reliability of measures and effects of working height. Ergonomics 50, 497–513 (2007). https://doi.org/10.1080/00140130601133800
Khan, N.U., Wan, W.: A review of human pose estimation from single image. In: ICALIP 2018 - 6th International Conference on Audio, Language and Image Processing. Institute of Electrical and Electronics Engineers Inc., pp. 230–236 (2018)
Dang, Q., Yin, J., Wang, B., Zheng, W.: Deep learning based 2D human pose estimation: a survey. Tsinghua Sci. Technol. 24, 663–676 (2019). https://doi.org/10.26599/tst.2018.9010100
Sarafianos, N., Boteanu, B., Ionescu, B., Kakadiaris, I.A.: 3D Human pose estimation: a review of the literature and analysis of covariates. Comput. Vis. Image Underst. 152, 1–20 (2016). https://doi.org/10.1016/j.cviu.2016.09.002
Fang, H.S., Xie, S., Tai, Y.W., Lu, C.: RMPE: regional multi-person pose estimation. In: ICCV (2017)
Li, J., et al.: CrowdPose: efficient crowded scenes pose estimation and a new benchmark. In: Proceedings of IEEE Computer Society of Conference on Computer Vision and Pattern Recognition, June 2019, pp. 10855–10864 (2018)
Xiu, Y., Li, J., Wang, H., Fang, Y., Lu, C.: Pose flow: efficient online pose tracking. In: British Machine Vision Conference, BMVC 2018 (2018)
Acknowledgment
The authors would like to thank the European Regional Development Fund (EFRE) and the Bremer Aufbau-Bank (BAB) for their support within the project AxIoM - Gamified AI assistance system for support of manual assembly processes (funding code: FUE0619B). We would like to thank Jichen Guo, Fabian Siekmann, Muhammad Husnain Ul Abdeen, and Joel Egharevba for their valuable contributions to literature research and algorithm implementation.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Petzoldt, C., Keiser, D., Beinke, T., Freitag, M. (2020). Functionalities and Implementation of Future Informational Assistance Systems for Manual Assembly. In: Freitag, M., Kinra, A., Kotzab, H., Kreowski, HJ., Thoben, KD. (eds) Subject-Oriented Business Process Management. The Digital Workplace – Nucleus of Transformation. S-BPM ONE 2020. Communications in Computer and Information Science, vol 1278. Springer, Cham. https://doi.org/10.1007/978-3-030-64351-5_7
Download citation
DOI: https://doi.org/10.1007/978-3-030-64351-5_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-64350-8
Online ISBN: 978-3-030-64351-5
eBook Packages: Computer ScienceComputer Science (R0)