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AI Planning

MPDV Mikrolab GmbH

Production planning with artificial intelligence

Production planning can be very time-consuming and complex, in particular if a great number of orders and operations related to each other is involved. A manual planning quickly reaches its limits. The use of artificial intelligence (AI) offers a means to manage this complexity in planning.

The mApp AI Planning uses reinforcement learning, a field-proven AI method, to allocate operations to machines and resources in the best possible way. The user defines the optimization objectives such as minimizing setup times or ensuring compliance with deadlines.

If configured accordingly, the planning with artificial intelligence also integrates the availability of material and personnel. After the automatic planning run, the user can still change or refine the planning result.

Benefits of AI Planning

Significantly reduce planning costs and profit from the global optimization of artificial intelligence. Increase productivity in your company.

AI Planning promotes sustainability

If production orders are planned with little idle times and short lead times, machines and other resources do not cause unnecessary costs. Also, a temporary storage of semi-finished products costs money. Clear planning with APS FEDRA supports companies in reducing this waste. If enhanced by the AI-based planning with the application AI Planning, all cost-driving factors of production are optimized.

Technical information

The mApp AI Planning is included in the Advanced Scheduling and Optimization category of the APS FEDRA and part of the AI Suite.

The mApp uses data of the Virtual Production Reality (ViPR) of MPDV's Manufacturing Integration Platform (MIP).

AI Planning in the MIP ecosystem

There are different methods used in production planning. MPDV provides the following mApps for this purpose:

  • Detailed Scheduling: Simple planning of production orders
  • Rule Designed Planning: Automatic planning according to defined rules
  • Simulation: Compare different planning scenarios

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