Problem
Design optimization: balancing processes, sub-processes, and buffer sizes in assembly line design.
Mechanical problem prediction: Identify and resolve critical issues such as dimensions, speed, force, torque, interference, and collisions in advance of physical realization.
Compliance with required performance: ensuring speed, availability, and quality of performance in accordance with customer requirements.
Machine reconfiguration: enable machines to adapt to new scenarios, product variants, and technological updates, and assess the impact on existing designs.
The specific objectives of the project
Develop, integrate, and demonstrate a new Simulation Based Digital Twin (SBDT) of a car brake assembly line production system, leveraging the expertise of EnginSoft, Cosberg, and MADE;
Demonstrate the advantages of this Simulation Based Digital Twin approach to new potential customers through integration with DIGITBrain;
Improve Cosberg’s ability to design customized solutions that improve cost efficiency, consumption times, time to market, quality, and reliability.
Develop a new Manufacturing As A Service (MaaS) business model based on the implementation of Digital Twin based on simulation on Digital Agora;
Take advantage of the DIH Test Before Invest scenario, facilitating exploitation and replication of the end-user market.
The results
The development of a digital twin based on the simulation of a pilot car assembly line to be integrated into the Digital Agora.
Provide the right architecture on the first attempt, balancing processes, subprocesses, and buffer sizes.
Provide the right mechanical solutions, anticipating critical issues before physical equipment testing to avoid incorrect dimensions/speeds, force, torque/potential interference, collisions, or defects;
Ensure performance (speed, availability, quality) in line with customer requirements;
Enable machine reconfiguration to support different scenarios: new product variants, revamping, technological upgrades, estimating the impact on the current design.
The role of MADE4.0
The Test Before Invest methodology, by improving testing in non-competitive scenarios, has increased market transfer while minimizing innovation risk.
It has leveraged its European network of Digital Innovation Hubs and the innovation community (industry, business associations, universities) to exploit the results of the projects.
Strengthened synergies with EU regional networks, improving the scale of the experiment within interregional funding opportunities.
The “Test Before Invest” methodology, by improving testing in non-competitive scenarios, has increased market transfer while minimizing innovation risk.
Dissemination activities developed in cooperation with the DIGITBrain consortium and selected experiments.
