Simulation-Based Digital Twins Enabling Smart Services for Machine Operations: An Industry 5.0 Approach

Abstract

The Industry 5.0 initiative seeks the sustainability and resilience of production systems through digital technologies. Derived from such an initiative, the Operator 5.0 concept surged to place the operator as the main value-creation contributor of sustainable and resilient human-machine systems. Smart service systems are data-driven services that provide intelligent capabilities to support decision-making in business processes. Despite previous research on smart services driven by multiple technologies in different contexts, further studies approaching Digital Twins as enablers of smart services in machine use phases are yet to be explored. Digital Twin, an Industry 5.0 enabler, is a technology that virtually represents physical assets that collect and analyze data from actual operations to make predictions for decision-making. Simulation-based Digital Twins generate simulation models that are continuously upgraded with asset data in real time, improving the accuracy of predictions. This paper aims to investigate how the Simulation-based Digital Twins (SDT) can enable the development of smart services in the Operator 5.0 context. We build on a multiple case study of 13 interviews from nine heavy mobile machinery manufacturers. We capture our results in categorizing SDT-enabled smart services for the use phases of the machine lifecycle. The categorization identifies the capabilities of each smart service for decision-making support and value co-creation.