With this service, companies can explore how AI-powerd production planning – using advanced techniques such as reinforcement learning – can address key manufacturing challenges and improve production efficiency, scheduling and resource management.
The service is designed as a structured experimentation process, consisting of the following steps:
1. Use Case Analysis and Data Assessment
An in-depth analysis is conducted of the company’s production environment, including workflows, available data, bottlenecks, and scheduling constraints. This step identifies opportunities where AI-driven production planning can deliver measurable improvements.
2. AI Factory Planner Configuration and Customization
The AI Factory Planner is tailored to the specific needs of the company and applied to real or representative production data. This phase demonstrates the potential impact of AI-based planning and optimization, and includes:
– Creation of a digital twin of the production environment to simulate realistic production scenarios
– Application of advanced production planning and optimization algorithms to improve scheduling and resource allocation
– Validation of results against current production performance
3. Performance Evaluation and Reporting
A detailed evaluation report is provided, outlining the results of the experiment. The report highlights potential improvements in production planning, efficiency gains, and optimized scheduling performance.
To ensure accurate analysis, realistic simulation, and effective AI-driven production planning, customer is expected to provide the following data and information:
– Production process information
– Production and planning data
– Resource and capacity data
– IT and integration context (e.g. ERP, MES systems in use)
– Use case definition and objectives
During the experimentation process, intermediate results are reviewed, and the AI models are refined based on feedback and observed performance. Through iterative testing and validation, the solution becomes increasingly robust and ready for real-world deployment.
Once validated, the AI Factory Planner can be scaled and integrated with existing manufacturing systems, such as ERP, MES, or other production management platforms, enabling seamless adoption within a smart factory environment.
