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Accepted Paper
Paper short abstract
Industrial digital twins establish new forms of pre-emptive modelling aimed at the simultaneous integration of remote control and prediction. Drawing on a technography of the Siemens Xcelerator platform, the paper examines how digital twin infrastructures stabilize regimes of logistical prediction.
Paper long abstract
Industrial digital twins establish new forms of pre-emptive modelling by aiming at the simultaneous integration of remote control and prediction in industrial practices and processes. Based on bidirectional data processing, models govern physical products, systems, and workflows. In doing so, digital twins stabilize regimes of logistical prediction in which models no longer merely represent futures but intervene in and operationalize them in real time within software infrastructures and global supply chains (Horn and Richardson 2025). Big Tech companies such as Siemens, Palantir, and Nvidia promote these technologies as technocratic forms of logistical control and prediction that seek to govern processes before they occur, thereby regulating the future in the present (Halpern 2025; Korenhof et al. 2023; Smith 2024).
Beyond techno-libertarian promises and market speculation, industrial digital twins consolidate infrastructures composed of sensor networks, global supply chains, algorithms, labour, and proprietary data centres. Adopting an infrastructural perspective, this paper examines how pre-emptive modelling through industrial digital twins is co-constituted by industrial software infrastructures. Methodologically, it draws on a technography of the Siemens Xcelerator Marketplace, a platform that integrates industrial software applications, digital twin models, and developer interfaces to sensor networks and cloud infrastructures such as AWS, Azure, and Nvidia Omniverse (Van Der Vlist 2024). Drawing on developer materials, platform documentation, and corporate publications, the paper analyses how Siemens Xcelerator structures labour hierarchies, operational logics, as well as imaginaries and epistemologies of modelling, thereby stabilizing specific infrastructures and temporal regimes of logistical prediction.
When models act: Forecasting, automation and the politics of future-making
Session 2