Abstract
Augmented Reality (AR) is one of the leading technologies of the Industry 4.0 revolution, offering innovative interfaces to promote the diffusion of digital contents into industrial processes, thanks to flexible and robust solutions and cost-effective devices. In this context, this paper explores the adoption of AR in industrial logistics where several open issues still discourage its effective use in everyday scenarios. After a review of objectives, approaches and technics of AR integration in logistics operations, the paper presents a framework to identify goods in a warehouse, retrieve data relative to the package, display info to the user to drive operations. The approach aims at easing and speeding up the activity of the warehouseman to identify goods, check the relative information and to put each good on the correct shelf. A prototypal application was developed within the Unity platform and integrated with the company ERP system to manage data on the products and retrieve images of the identification labels. A real use case involving a primary company producing agricultural tractors is proposed to test usability of the prototype. Results showed that the developed application allows relevant benefits in terms of process effectiveness, error prevention, aiming at reducing the operator mental workload.
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References
Romero, D., Bernus, P., Noran, O., Stahre, J.: The Operator 4.0: human cyber-physical systems adaptive automation towards human-automation symbiosis work systems. In: IFIP International Conference on Advances In Production Management Systems (APMS), pp. 677–686, Iguaussu Falls (2016)
Chang, M.M.L., Ong, S.K., Nee, A.Y.C.: AR-guided product disassembly for maintenance and remanufacturing. Procedia CIRP 61, 299–304 (2017)
Eschen, H., Kötter, T., Rodeck, R., Harnisch, M., Schüppstuhl, T.: Augmented and virtual reality for inspection and maintenance processes in the aviation industry. Procedia Manuf. 19, 156–163 (2018)
Runji, J.M., Lin, C.Y.: Markerless cooperative augmented reality-based smart manufacturing double-check system: case of safe PCBA inspection following automatic optical inspection. Robot Comput. Integr. Manuf. 64, 101957 (2020)
Grandi, F., Khamaisi, R.K., Peruzzini, M., Raffaeli, R., Pellicciari, M.: A reference framework to combine model-based design and AR to improve social sustainability. Sustainability 13, 1–16 (2021)
Khamaisi, R.K., Prati, E., Peruzzini, M., Raffaeli, R., Pellicciari, M.: UX in AR-supported industrial human–robot collaborative tasks: a systematic review. Appl. Sci. 11, 1–17 (2021)
Wahid, D., Ray, G., Habiba, F.: A solution procedure for minimum convex-cost network flow problems. Global J. Sci. Front. Res. 12(10), 23–30 (2012)
Billinghurst, M., Clark, A., Lee, G.: A survey of augmented reality. Found. Trends Hum.-Comput. Interact. 8, 73–272 (2014)
Azuma, R.T.: A survey of augmented reality. Presence Teleoperators Virtual Environ. 6(4), 355–385 (1997)
Wang, W., Wang, F., Song, W., Su S.: Application of augmented reality (AR) technologies in inhouse logistics. E3S Web Conf. 145(1), 02108 (2020)
Rejeb, A.: The challenges of augmented reality in logistics: a systematic literature review. World Sci. News 134, 281–311 (2019)
Cirulis, A., Ginters, E.: Augmented reality in logistics. Procedia Comput. Sci. 26, 14–20 (2013)
Plakas, G., Ponis, S.T., Agalianos, K., Aretoulaki, E., Gayialis, S.P.: Augmented reality in manufacturing and logistics: lessons learnt from a real-life industrial application. Procedia Manuf. 51, 1629–1635 (2020)
Ginters, E., Cirulis, A., Blums, G.: Markerless outdoor AR-RFID solution for logistics. Procedia Comput. Sci. 25, 80–89 (2013)
Reif, R., Walch, D.: Augmented & virtual reality applications in the field of logistics. Vis. Comput. 24, 987–994 (2008)
Stoltz, M.H., Giannikas, V., McFarlane, D., Strachan, J., Jumyung, U., Rengarajan, S.: Augmented reality in warehouse operations: opportunities and barriers. IFAC-PapersOnLine 50, 12979–12984 (2017)
Hart, S., Staveland, L.: Development of NASA-TLX (Task Load Index): results of empirical and theoretical research. Human Mental Workload 52, 139–183 (1988)
Davis, F.D., Bagozzi, R.P., Warshaw, P.R.: User acceptance of computer technology: a comparison of two theoretical models. Manage Sci. 35, 982–1003 (1989)
CNH Industrial Homepage. https://www1.cnhindustrial.com/it-IT/Pages/homepage.aspx. Accessed 28 Mar 2022
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Casciotta, E., Khamaisi, R.K., Raffaeli, R., Peruzzini, M. (2023). An AR Tool to Support Warehouse Operations in the Context of Industry 4.0. In: Gerbino, S., Lanzotti, A., Martorelli, M., Mirálbes Buil, R., Rizzi, C., Roucoules, L. (eds) Advances on Mechanics, Design Engineering and Manufacturing IV. JCM 2022. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-031-15928-2_121
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DOI: https://doi.org/10.1007/978-3-031-15928-2_121
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