Twelve questions from industry, three places to answer them
Every DRIVE PR track starts from a question a partner company needs answered. The tracks are grouped by where the answer changes the work: the design office, the decisions in between, and the factory floor.
How a track works
A track starts with a partner's industrial case. Together with researchers, the partner sets a 2026 baseline, agrees what would count as measurable improvement, and defines the studies and demonstrations that get there. Industrial partners act as need owners and end users; researchers and research students run the studies and report progress at the project's half-year events.
Two streams run in each track. One develops and demonstrates methods and tools that are mature enough to show measurable impact by 2029. The other explores emerging digital infrastructure at lower maturity, to reduce the risk of adopting it and to prepare Phase 2.
What the tracks add up to
A common track pulls the results into the Data-Driven Product Realisation Concept: a documented workflow, with the methods and infrastructure to run it, that other manufacturers can adopt. How it works
Results, published as they mature
Capability reports follow the first-year and second-year demonstrations in 2027 and 2028, with a consolidated report in 2029. Publications, theses and demonstrators will be listed here as they become public.
The twelve questions, by impact area
In the design office
Data-Driven Engineering Design
- How do we define modular product platforms across integrators and suppliers without drowning in complexity?Modular and platform design
- How do we design for situations we cannot test enough in reality?Design using synthetic datasets
- How do we make designs robust to the variation the factory and the field will actually throw at them?Data-driven robustness
- How do we design and validate products that only work together with other products?Systems-of-systems design
Between design and factory
Digital Infrastructure and Decision Support
- How do we get factory and field data to the decision in time?Communication infrastructure
- How do we evaluate hundreds of alternatives instead of a handful?Computation infrastructure
- How do we trust the data, and the models trained on it?Data quality, interpretability and security
- How do people stay in charge when AI proposes the answer?Human in the loop
On the factory floor
Digital and Connected Factory
- How do we re-plan a factory quickly when products or volumes change?Interactive layout planning
- How do we run repair and remanufacturing as efficiently as new production?Life-cycle repair and remanufacturing
- How do we go from monitoring with a digital twin to controlling with it?Dynamic digital twins
- How do automated processes adapt to disruption without long stoppages?Automated industrial processes
Common track: the Data-Driven Product Realisation Concept, where the answers come together
How it worksThe Data-Driven Product Realisation Concept
The main deliverable of Phase 1: one workflow, run on shared infrastructure, that takes a problem statement to a better concept with less risk, uncertainty and variation. The partners learn to use the digital infrastructure through it, and the methods, tools and work practices needed to run it are developed and demonstrated in the tracks.
- Problem statement
- Contextual definition
- Define study
- Data and model generation
- Solution generator
- Evaluation
- Decision
- Improved concept, with less risk, uncertainty and variation
- Communication infrastructuregets data between sites, machines and people
- Computation infrastructureruns the data and model generation
- Life-cycle datafrom factory, field and engineering, with data management
Requirements and criteria feed back from the decision to the earlier steps, so that each pass through the workflow narrows uncertainty. The idea was first explored in the European DIAS project, where large sets of integrated product and production concepts were generated from requirements and evaluated at once for physical, producibility and supply-chain readiness.
By 2029 the concept is documented so that other manufacturers can adopt it. Phase 2 is meant to validate it more generally, prepare scale-up, and develop the technologies that enable commercial adoption.
Real infrastructure to test on
The tracks develop and demonstrate on existing infrastructure: 5G test environments at AstaZero and the CASE laboratory, the Chalmers eCommons gateway to national and European high-performance computing, the Wingquist Laboratory's virtual and physical laboratories, and the partners' own factory testbeds, production data and engineering systems.