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

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.