Smart Machine and Production Design

By setting up and operating pilot lines and plants, the work group at BITC provides an infrastructure that enables battery production processes to become more efficient, flexible and needs-oriented, whether these processes are self-designed or located at clients’ or project partners’ plants. The objective is to achieve optimal plant and factory control under the aspects of cost, stability and performance.

Based on intensive experience in complex ceramic manufacturing processes and industrial sensor technology, the work group provides the hardware and software structures to systematically evaluate, vary and optimize technical manufacturing steps in battery production.

The researchers accompany clients along the entire chain – from the selection and development of suitable measuring and testing technology (destructive [NDE], non-destructive [NDT]), through the technical and economic evaluation of pilot lines and plants, to the reconfiguration of plant components and/or production lines. In close cooperation with the work group Industrial Data Concepts, clients receive a deep understanding of the multifactorial correlations in battery production as well as the scenarios that can be derived from them to improve industrial workflows, plant and factory control systems.

 

Competencies

      

• Efficient and scalable instrumentation and networking of process steps
• Development and expansion of standardized frameworks and microservices
• Automated statistical design of experiments with integrated evaluation
• Development of self-optimizing processes and their integration into pilot lines
• Concepts for integrated self-monitoring and -calibration
• Application and in-house development of control algorithms, especially for interdependencies
• Directly and indirectly integrated workflow management (including smart scheduling, dependency management, error handling, orchestration)
• Integrated security concepts

Services offered

 

Instrumentation

• System modification and integration in pilot lines and data structures
• Demand-oriented integration of sensors, system components, control and regulation technology
• Implementation and adaptation of workflows
• Interface definition for innovative sensor components and concepts

Networking

• Definition and creation of microservices for communication within the production chain and with higher-level data structures
• Development and integration of data storage and workflows in manufacturing (smart scheduling, data-driven process variation)
• Implementation of robust, cross-process control algorithms
• Implementation of methods of statistical design of experiments
• Development of methods for self-optimizing process chains (e.g. AI)

Evaluation

     

• Provision of pilot lines with systematic variation of the processes for data and pattern generation
• Scenario analyses for production costs
• Preparation of process data and extraction of findings