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Introducing DACAR: A Process Mapping Tool to Uncover Robotization Implications in Manufacturing

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Challenging the Future with Lean (ELEC 2023)

Abstract

To prepare a robot implementation, it is of key importance to have an overview of the technical and non-technical implications. Process modeling techniques could be used for mapping relevant implications related to robot implementation in today’s manufacturing. However, we argue that existing process mapping tools lack an in-depth perspective, making it potentially difficult for manufacturers to comprehensively and efficiently prepare their robotization project. In an attempt to enrich existing process mapping methodology, we introduce our newly developed process mapping tool in this contribution: the DACAR model. The DACAR model allows the identification of relevant technical and non-technical implications related to integrating a robot solution into a manufacturing process. In this contribution, we elaborate on DACAR’s theoretical and methodological underpinnings and present a research agenda comprising various fruitful opportunities for DACAR-related research.

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Acknowledgements

This contribution originated from research project "Robotizing Integrally” (in Dutch: Integraal Robotiseren), financially supported by the Dutch national funding agency SIA (Dutch Research Council). The authors would like to express their gratitude to Vincent Wiegel (HAN University of Applied Sciences), Aart Schoonderbeek (Windesheim University of Applied Sciences), and Rik Grasmeijer (Fieldlab Industrial Robotics) for their valuable contributions and support. The authors would like to extend their appreciation to Luuk Collou (Saxion University of Applied Sciences) for reviewing earlier versions of this contribution. His constructive feedback improved the textual quality.

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Correspondence to Peter Schuurhuis .

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Appendices

Appendix A

This appendix contains the standard worksheet to describe the situational characteristics of the to-be-robotized part of a production process (see Fig. 4). Depending on the specific context of a company being studied, it might be required to add additional items or justified to skip particular items from the standard worksheet.

Fig. 4.
figure 4

Worksheet used to fill a DACAR process box (part 1 and part 2).

Appendix B

This appendix contains an illustration of a completed DACAR process map (see Fig. 5). The model contains a series of three process boxes for (1) infeed, (2) to-be automated (manual) tasks within the manufacturing process and (3) outfeed. Each process box is complemented by seven information boxes regarding the situational characteristics. Kaizen bursts, recognizable by the black explosion icons, are added to indicate any implications with regard to implementing a robot in the modelled production system.

Fig. 5.
figure 5

Visualization of completed DACAR process map.

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Schuurhuis, P., van den Hoek, R., Wolffgramm, M., van Roij, M. (2024). Introducing DACAR: A Process Mapping Tool to Uncover Robotization Implications in Manufacturing. In: van Kollenburg, T., Kokkinou, A., McDermott, O. (eds) Challenging the Future with Lean. ELEC 2023. IFIP Advances in Information and Communication Technology, vol 681. Springer, Cham. https://doi.org/10.1007/978-3-031-63265-5_6

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  • DOI: https://doi.org/10.1007/978-3-031-63265-5_6

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