Interconnected digital twins and the future of digital manufacturing: Insights from a Delphi study
Marc van Dyck, Dirk Lüttgens, Frank T. Piller, Sebastian Brenk
kHUB post date: Aug 1, 2023
Originally published: June 04, 2023 (PDMA JPIM • Vol 40, Issue 4 • July 2023)
Read time: 65 minutes
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Digital twins (DTs) are virtual representations of real-world entities like production assets, processes, or products. They are updated at a defined fidelity and frequency along the entire life cycle from development and engineering over the production or implementation of a product or process until its usage stage. Interconnected digital twins (IDTs) are DTs shared and connected across organizations with the objective to create holistic simulation and decision models of an entire physical system. In this paper, we investigate how IDTs shape future digital manufacturing scenarios and impact innovation management. We present the results of a real-time Delphi study, analyzing quantitative and qualitative estimates on a set of 24 projections, forecasting the future of digital manufacturing with a projection horizon towards 2030. Using this data and 22 additional use cases of IDTs in manufacturing companies, we present a baseline scenario where our Delphi panel reached a consensus, representing a likely future of digital manufacturing in 2030. By analyzing projections where our expert panels' evaluations vary widely, we identify key design decisions that may impact innovation management along the dimensions of variation, choice, and control in digital manufacturing. We explain how IDTs will impact external knowledge inflows, the emergence and governance of industrial data spaces, and the potential of data-driven and AI-enabled applications for prediction and regulation to drive better decision-making and continuous innovation.
Practitioner points
- The paper presents the results of a Delphi study forecasting the future of digital manufacturing with a projection horizon towards 2030.
- Based on the assessments of 35 international experts from industry and academia, we derive a base scenario indicating that future digital manufacturing is likely to be (1) decentralized in the structure of its technical data exchange, (2) transparent to increase environmental sustainability, (3) automated through AI-assisted decision-making, and (4) outcome-oriented through subscription models enabled by real-time bidirectional data flows.
- A core technology of future digital manufacturing systems is interconnected digital twins (IDTs), understood as a network of virtual representations of physical objects or systems to communicate and exchange data across lifecycles in real time and optimize performance and decision-making through simulation models on the system level.
- A complementary analysis of 22 use cases derives a set of design choices that can help overcome the challenges posed by IDTs and capture the value promised by this new technology.