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Electromobility laboratory Aachen - eLAB: Big Data in battery production
Big Data demonstrator in lithium-ion cell production to reduce end-of-line test costs
Introduction
Application examples:
Education and training,
Manufacturing industry
What were the challenges to be solved and what specific benefits were achieved?
The aim of this project is to develop a procedure for plant linking and analysis of the cause-effect relationships. Various technologies will be integrated into the demonstration line for cell production in Aachen and a detailed approach will be developed together with the technology partners. First production tests at the plants are used to validate the developed procedure.
This results in the following benefits:
Integrated selected cause-effect relationship in the control centre with derived and validated algorithm for process control
Method for the detection of cause-effect relationships
Method for tool integration
How can the Industrie 4.0 approach be described?
Basis for the implementation of the project is the information and equipment available at PEM in the field of the lithium-ion battery and its production. In the three working periods of the project, results are achieved on the basis of set goals and findings for the further working period are generated. The highly iterative and agile innovation process is described on a principle-, process- and method level. The generated backlog serves as the basis for the final result of a detailed procedure for the system link.
What could be achieved?
The desired result shows the procedure and methodology used in Aachen and in its own plant engineering in a structured manner and thus provides a detailed basis for a possible plant linking with industrial partners. Obstacles and difficulties as well as possible solutions are presented in addition to the general approach. Finally, a validation and final evaluation is carried out for the possible transfer.
What measures have been taken to achieve the solution?
The project structure was divided into three working periods of 30 days each. All project steps were carried out on the equipment technology of PEM at RWTH Aachen University. The systems are located at eLAB in Aachen. First the electrode manufacturing process on the intensive mixer and the coating system were integrated into a control station with additional sensors. In the second step, the control station was extended by additional systems and sensors. Parallel to this, the SmartData data analysis was carried out. In the last step the identified cause-effect relationships were analysed more closely and the methodology was validated.
What can others learn from it?
The project identified many success factors for the holistic implementation of a Big Data application. In addition to the general methodology, a list of criteria and a list of requirements was developed. In addition, there were many lessons learned in the field of the integration of the plant- and control partners for the necessary integration of the machines.
