VProSaar

Vgranted ProInduction for the saarThe domestic automotive industry: Sustainable, networked, resilient

problem

The ongoing structural change (due to decarbonisation, electrification, etc.) in the automotive sector will inevitably lead to the adaptation of existing but also to the development of completely new innovative products and services. In order to maintain competitiveness and consolidate the position of production facilities (especially SMEs), it is necessary to adapt to technological challenges (frequent process and product innovations, resource and energy efficiency, optimised machine utilisation, etc.) as well as socio-economic challenges (fluctuations in demand, globalisation, demographic change). In order to be able to react to changing boundary conditions at short notice, flexibility and reconfigurability (configurability) of production environments and plants are indispensable. In addition, it is crucial to promote employee centricity and to be able to communicate production status and production capabilities internally and across companies. Through technological innovations and a stronger focus on internal (network production) and external (distributed production) information exchanges, small and medium-sized enterprises can assert themselves in global and intra-group competition.

objective

The aim of the research project is to investigate the basics and technologies for distributed, networked and human-centered production in order to ensure a higher adaptability in the economy. In order to ensure portability, the following basic building blocks are addressed:

• Standardization of interfaces, data exchange formats and semantics for simplified data exchange and data understanding
• Communication and networking of production resources for automatic horizontal and vertical information transmission
• Operational and attack security of the communicating production resources
• Adaptability and resilience of production resources (considering robot systems as a common component in process automation)
• Handling and organization of changed production system structures and competence profiles of employees
• Modeling of partial and total systems to ensure transparency and to identify optimization potentials

approach

Within the research project, these basic building blocks are to be cast into a common digital image of real production systems. The project is divided into the following work packages:
The following priorities are addressed in relation to the respective work packages:
1. Conception and demarcation of fundamental system components: Selection and definition of standards and concepts for controlled access to all information of a production asset (product, process and equipment data) - comparable to a management shell (AP1)
2. Product development/manufacturing: Development of an expert system for employee support in the parameterization of novel manufacturing processes (AP2)
3. Agile adaptive production resources: Development of an agile, adaptive resource based on smart materials to directly support the employee on shop floor level and ensure the data flow between real and digital components (asset) (AP3)
4. Adaptive robotics: Development and implementation of conventional and learning approaches for simulative investigation (collision investigations, accessibility tests, web planning) of existing intelligent robot systems for digital verification and transmission into the real production environment (AP4)
5. Planning & Optimization: Ability matching between changing product specifications and operational resources to execute simulation-driven optimization strategies (AP5)
6. Production system orchestration: Development of a software system (highly flexible manufacturing execution system, MES) for orchestrating production resources (AP6)
7. Multisensor system & Data fusion: Development of an overarching approach for the predictive analysis of wear parts on the production system and enrichment of the digital twin with relevant conclusions (AP7)
8. Industrial security: Enrichment of the developed digital twin with relevant security information and development of automated security checks based on this information (AP8)
9. Project management and implementation in a demonstrator: Development of a physical demonstrator with software-based modules for the realization of distributed production at ZeMA (AP9)

Recovery concept

The scientific success prospects of ZeMA are further increased by setting standards in the field of networked production and setting up a representative demonstrator scenario. The technical verification of the research results by the practical implementation of the results within a demonstrator on an industrial standwheel provides both the basis for the proof of the prospects of success as well as for the transferability to other industries.
Furthermore, the demonstrator can be increasingly used for teaching and for further training measures. There are, for example, training courses and seminars in the field of networked production, the construction of digital twins, data security and quality, as well as further research projects on topics such as virtual plant commissioning and the energy-efficient operation of plants, etc. In addition, offers can be developed in cooperation with, for example, the Saarland automotive network. Ultimately, the results developed here can be used directly in the context of transfer projects. Within the framework of current projects and their successor projects (KomZetSaar - Mittelstand-4.0 Kompetenzzentrum, RZzKI - Regional Future Center for AI and Digital Transformation, scientifically developed findings can be shared directly with regional companies, in particular SMEs.

Project management: Max Eichenwald, M.Sc.
Duration: 01.10.2022 – 30.09.2026
Funded by: EU (ERDF), Saarland State Chancellery

Ministry of Economy, Innovation, Digital and Energy