Adaptive retrofitting for industrial machines: utilizing webassembly and peer-to-peer connectivity on the edge

World Wide Web, vol. 27

Abstract

Abstract Leveraging previously untapped data sources offers significant potential for value creation in the manufacturing sector. However, asset-heavy shop floors, extended machine replacement cycles, and equipment diversity necessitate considerable investments for achieving smart manufacturing, which can be particularly challenging for small businesses. Retrofitting presents a viable solution, enabling the integration of low-cost sensors and microcontrollers with older machines to collect and transmit data. In this paper, we introduce a concept and a prototype for retrofitting industrial environments using lightweight web technologies at the edge. Our approach employs WebAssembly as a novel bytecode standard, facilitating a consistent development environment from the cloud to the edge by operating on both browsers and bare-metal hardware. By attaining near-native performance and modularity reminiscent of container-based service architectures, we demonstrate the feasibility of our approach. Our prototype was evaluated with an actual industrial robot within a showcase factory, including measurements of data exchange with a cutting-edge data lake system. We further extended the prototype to incorporate a peer-to-peer network that facilitates message routing and WebAssembly software updates. Our technology establishes a foundational framework for the transition towards Industry 4.0. By integrating considerations of sustainability and human factors, it further extends this groundwork to facilitate progression into Industry 5.0.

Authors 4

1. Otoya Nakakaze corresponding Aachen Chair of Databases and Information Systems

   RWTH Aachen University

   Affiliation as printed

   Chair of Databases and Information Systems, RWTH Aachen University, Ahornstraße 55, Aachen, 52074, Germany

2. István Koren corresponding Aachen Chair of Process and Data Science

   RWTH Aachen University

   Affiliation as printed

   Chair of Process and Data Science, RWTH Aachen University, Ahornstraße 55, Aachen, 52074, Germany

3. Florian Brillowski Aachen Institute of Textile Technology

   RWTH Aachen University

   Affiliation as printed

   Institute of Textile Technology, RWTH Aachen University, Otto-Blumenthal-Straße 1, Aachen, 52074, Germany

4. Ralf Klamma Aachen Chair of Databases and Information Systems

   RWTH Aachen University

   Affiliation as printed

   Chair of Databases and Information Systems, RWTH Aachen University, Ahornstraße 55, Aachen, 52074, Germany