MultiPEP – Multi-criteria personnel resource planning taking into account the robustness of production systems

Production planning faces the challenge of efficiently managing production systems despite high demand volatility and scarce human resources. Traditional planning methods focus primarily on maximizing productivity in the short term and often neglect system stability. Fluctuating machine availability, varying process times and complex production processes make robust planning difficult. MultiPEP addresses these challenges by integrating robustness analyses into production planning.

Objective of the project

The aim of MultiPEP was to develop an innovative planning method that increases the robustness of production systems and at the same time enables efficient production planning. The method:

• Considers system stability and production restrictions as central optimization variables.
• Uses mathematical models to analyze process reliability and machine availability.
• Minimizes throughput times and optimizes the use of resources.
• Uses constraint programming methods to efficiently control production processes.
• Enables dynamic adaptation to changing production conditions.

Advantages

• Increased production stability : Systematic consideration of robustness indicators to avoid unplanned downtimes.
• Improved efficiency:  Optimised use of resources reduces waiting times and bottlenecks.
• Flexible production planning: Adaptability to variable production conditions without loss of productivity.
• Optimised scheduling: Intelligent allocation of operating resources maximises system performance.

Procedure

As part of MultiPEP, a robustness analysis was first developed in order to create mathematical models for evaluating the stability of production systems. Building on this, the project investigated the influence of machine availability and process times on the overall performance of production systems. This served as the basis for the development of a multi-criteria optimization method for the robust control of production processes. Finally, the method was validated using various production scenarios.

Are you interested in automated planning in production?

Contact Max Eggers via e-mail at eggers@ifw.uni-hannover.de or by phone +49 511 762 4341.