Experiment 14: Digital Twin to optimize design of cars braking system assembly line (DigiTBreak)

Motivation of the Experiment

Producer of manufacturing assembly lines faces unprecedented challenges in optimizing design and engineering to meet evolving market needs while ensuring, efficiency and productivity challenges.

  • Providing a first-time right architecture, by balancing processes, sub-processes, buffers sizes;
  • Providing the right mechanical solutions, by predicting critical problems before physical equipment testing to avoid wrong sizing/speed, force, torque/potential interferences, collisions or defect;
  • Guaranteeing performances (rates, availability, quality) complying with customer’s requirements;
Pilot Assembly line at MADE - Test before invest

Pilot Assembly line at MADE - Test before invest

  • Enabling the re-configuration of the machines to support different scenarios: new product variants, revamping, technology upgrading, by estimating the impact on the current design.

To solve these challenges, DIGITBreak aims at

  • Developing, integrating and demonstrating a novel Simulation Based Digital Twin of a car brake assembly line production system leveraging EnginSoft, Cosberg and MADE competences
  • Demonstrating advantages of such SBDT approach to new potential customers through the integration with DIGITBrain;
  • Enhancing Cosberg ability to design customized solution allowing for improved cost efficiency; time consuming, time to market, quality and reliability;
  • Developing a new MaaS business model, based on SBDT deployment on the Digital Agora
  • Exploit DIH Test Before Invest scenario, facilitating end user market exploitation and replication

Purpose of the Experiment

The purpose of the experiment is to exploit digital twin to accomplish the following manufacturing scenario for the end-user:

 

Scenarios Application fields Key-Users Drivers KPI Target Simulating Approaches
1. Performance Green field
Brown field
Designers
Production
Manager
Architecture
Bill of Material
Technologies
Process parameter
#1 Throughput
(Pieces/minute)
Digital and Physical
2. Downtime Green field
Brown field
Designers
Production
Manager
Technologies
Process parameter
#2 Availability
(Running time/total time)
Digital
3. Quality Green field
Brown field
Designers
Production
Manager
Technologies
Process parameter
#3 Quality Index
(Pieces OK /total pieces)
Theoretical
4. Revamping
Technological
Upgrade
Brown field Designers Architecture
Bill of Material
Technologies
Process parameter
#4 OEE
(Throughput,
Availability,
Quality)
Digital
5. Resource
Optimisation
Brown field Production
Manager
Bill of Material
Process parameter
#5b Material
(Bill of devices)To be monitored:
#4 OEE
Physical

 

The project uses a Simulation Based Digital Twin (SBDT), based on Discrete Event Simulation models (DES) relying on engineering. knowledge and data to represent the behaviour of the plant. The underlying simulation model is used to obtain high-fidelity predictions, including production forecasts of new scenarios for which no past data are available. DES model requires limited computational resources: a full day of production of an assembly line with a complex production mix is simulated within seconds on a laptop. Exploiting the Test Before Invest the project will deploy different approaches:

  • Digital and Physical: digital simulation of events and physical application by real testing on the pilot machine (scenario 1 – Productivity, scenario 5 – Revamping, scenario 4 – Resources Optimization);
  • Only Digital: digital simulation of events, without any chance to test physically the solution (scenario 2 - Downtime);
  • Theoretical evaluation: study the effects of simulating new events and haw could affect target KPIs (Scenario 3 - Quality).
Discrete event simulation models of the assembly line

Discrete event simulation models of the assembly line

Technical Impact

The experiment follow Test Before Invest (TBI) methodology deploying use case installed at MADE Competence Center - Digital Innovation Hub. This scenario allow for simulation in real operational environment (TRL 7) minimizing technical and business risk of technology transfer to market both for end user and Individual Software Vendor.
The experiment builds on the following blocks: (i) pilot assembly line at MADE - TBI (ii) line monitoring system and data flow thereof, (iii) information synthesis layer, (iv) discrete event simulation models of the assembly line, (v) DIGITbrain framework, including the Digital Agora.

Economic Impact of DigiTBreak Experiment

The DIGITBRAKE project released
6 digital model on specific manufacturing scenarios formalized to develop and test the feasibility of solutions: improving performance; reducing downtime; increasing the quality of the processed product; revamping plant with technology overhaul; and optimizing plant resources, with the same performance;
1 interface, supporting manufacturing operators and manager to deploy
1 app integrated into the DIGITBrain platform
+ 4 new employee focused on digital manufacturing skills
+ 3 business model innovated, for end user, technical provider, DIH
+ 5 new contacts for business and R&D opportunities

Watch DigiTBreak's Experiment Video:

Watch DigiTBreak presentation at Hannover Fair 2021:

Project Partners

 

Cosberg S.P.A, Italy

serves as the end-user in this experiment.

EnginSoft SpA., Italy

serves as the technology partner.

MADE s.c.a r.l., Italy

serves as DIH in this experiment.

START4.0 is the Digital Innovation Hub with the role of experiment supervisor.