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Retrofitting Industrial Machines with WebAssembly on the Edge

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Web Information Systems Engineering – WISE 2022 (WISE 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13724))

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Abstract

Tapping into previously inaccessible data sources promises new potential for value creation in the manufacturing industry. However, asset-heavy shopfloors, long machine replace cycles, and equipment heterogeneity demand major investments to achieve smart manufacturing, which small businesses struggle with. Retrofitting is a sustainable means of equipping aged machines with low-cost sensors and microcontrollers to read and forward machine data. In this paper, we present a concept and a prototype to retrofit industrial scenarios using lightweight web technologies on the edge. We propose using WebAssembly as a new bytecode standard that runs on browsers and bare-metal hardware alike, thus providing a uniform development environment from cloud to edge. We confirm its applicability by achieving near-native performance together with modularity known from container-based service architectures. Our prototype is evaluated with a real industrial robot within a showcase factory, including measurements of data exchange with a state-of-the-art data lake setup. We are convinced that our groundwork paves the way to an easier-to-implement and more sustainable Industry 4.0.

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Notes

  1. 1.

    cf. https://developer.bosch.com/products-and-services/sdks/xdk.

  2. 2.

    cf. https://github.com/appcypher/awesome-wasm-langs.

  3. 3.

    cf. https://madewithwebassembly.com/.

  4. 4.

    cf. https://github.com/mbasso/awesome-wasm.

  5. 5.

    cf. https://github.com/internet-of-production/WasmRetrofittingESP32.

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Acknowledgement

Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy - EXC-2023 Internet of Production - 390621612.

Author information

Authors and Affiliations

  1. Chair of Databases and Information Systems, RWTH Aachen University, Aachen, Germany

    Otoya Nakakaze & Ralf Klamma

  2. Chair of Process and Data Science, RWTH Aachen University, Aachen, Germany

    István Koren

  3. Institut für Textiltechnik, RWTH Aachen University, Aachen, Germany

    Florian Brillowski

Authors
  1. Otoya Nakakaze
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  2. István Koren
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  3. Florian Brillowski
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  4. Ralf Klamma
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Corresponding author

Correspondence to Otoya Nakakaze .

Editor information

Editors and Affiliations

  1. University of Pau and Pays de l'Adour, Anglet, France

    Richard Chbeir

  2. The University of Queensland, Brisbane, QLD, Australia

    Helen Huang

  3. Sapienza Università di Roma, Rome, Italy

    Fabrizio Silvestri

  4. Open University of Cyprus, Nicosia, Cyprus

    Yannis Manolopoulos

  5. The New Cyber Research Department, Peng Cheng Laboratory, Shenzhen, China

    Yanchun Zhang

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Nakakaze, O., Koren, I., Brillowski, F., Klamma, R. (2022). Retrofitting Industrial Machines with WebAssembly on the Edge. In: Chbeir, R., Huang, H., Silvestri, F., Manolopoulos, Y., Zhang, Y. (eds) Web Information Systems Engineering – WISE 2022. WISE 2022. Lecture Notes in Computer Science, vol 13724. Springer, Cham. https://doi.org/10.1007/978-3-031-20891-1_18

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  • DOI: https://doi.org/10.1007/978-3-031-20891-1_18

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