Production Planning

Simulation is frequently used for prediction of the outcome of adjustments in production systems. Real decision processes must be represented in the simulation. To achieve this, complex real decision processes have to be transferred into the simulation. This leads to a high effort for the creation of simulation models. This is resolved by the concept of iterative optimization-based simulation. Instead of transferring complex decision processes into the simulation, the predicted parameters are exported and existing decision processes determine a solution.

The large number of systems offered on the market makes a well-founded selection process necessary from the requirement survey to the final system selection. A comprehensive model that systematically supports and simplifies this process is the subject of this two-part article. The methodology goes beyond a questionnaire-based query and verifies system capabilities using structured case studies. The first part of the article [1] describes the process steps from the survey and collection of requirements of the customer to the system to their structuring in customer specifications. The present second part outlines the process steps of the system rough selection up to its fine selection. The individual selection steps are methodically supported by practical references as well as by the use of concrete tools. Using the described methodology selected systems can be objectively compared - a prerequisite for effective and efficient system selection for industrial companies.