Abstract
With present day industries pressing for retrofitting of current machinery into Industry 4.0 ideas, a large effort is put into data production, storage and analysis. To be able to use such data, it is fundamental to create intelligent software for analysis and visualisation of a growing but frequently faulty amount of data, without the quality and quantity adequate for full blown data mining techniques. This article case studies a foundry company that uses the lost wax method to produce metal parts. As retrofitting is underway, modelling, simulation and smart data visualisation are proposed as methods to overcome data shortage in quantity and quality. The developed data visualisation system is demonstrated to be adapted to the requirements and needs of this company in order to approach full automation ideas. Such data visualisation system allow workers and supervisors to know in real time what is happening in the factory, or study the passage of manufacturing orders for a specific area. Data Analysts can also predict machinery problems, correct issues with slow changing deviations and gather additional knowledge on the implementation of the process itself.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Lu, Y.: Industry 4.0: a survey on technologies, applications and open research issues. J. Industr. Inf. Integr. 6, 1–10 (2017). https://doi.org/10.1016/j.jii.2017.04.005
Zysman, J., Kenney, M.: The next phase in the digital revolution: Intelligent tools, platforms, growth, employment. Commun. ACM 61, 54–63 (2018). https://doi.org/10.1145/3173550
Pattnaik, S., Karunakar, D.B., Jha, P.K.: Developments in investment casting process–a review. J. Mater. Process. Technol. 212(11), 2332–2348 (2012). https://doi.org/10.1016/j.jmatprotec.2012.06.003
Morgan, R., Grossmann, G., Schrefl, M., Stumptner, M.: A model-driven approach for visualisation processes. In: ACM International Conference Proceeding Series, art. no. a55 (2019). https://doi.org/10.1145/3290688.3290698
Sand Casting, Investment Casting and Die Casting in China. www.castingquality.com/casting-technology/investment-casting-tech/investment-casting-process.html
Q-DAS. https://www.q-das.com/en
Grafana Labs. https://grafana.com
Acknowledgements
Authors gratefully acknowledge the funding of Project MAGIC_4.0: Afinação de grão por correntes eletromagnéticas rotativas e tecnologias da indústria 4.0 para a fundição por cera perdida (POCI-01-0247-FEDER-038128), co-financed by Programa Operacional Competitividade e Internacionalização (COMPETE 2020) through Fundo Europeu de Desenvolvimento Regional (FEDER).
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
Cruz, A.B., Sousa, A., Cardoso, Â., Valente, B., Reis, A. (2020). Smart Data Visualisation as a Stepping Stone for Industry 4.0 - a Case Study in Investment Casting Industry. In: Silva, M., Luís Lima, J., Reis, L., Sanfeliu, A., Tardioli, D. (eds) Robot 2019: Fourth Iberian Robotics Conference. ROBOT 2019. Advances in Intelligent Systems and Computing, vol 1092. Springer, Cham. https://doi.org/10.1007/978-3-030-35990-4_53
Download citation
DOI: https://doi.org/10.1007/978-3-030-35990-4_53
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-35989-8
Online ISBN: 978-3-030-35990-4
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)