For years, the logistical focal point of order picking has been subject to an increasing complexity trend. The variety of technology variants and organizational forms is constantly expanding. Dynamic system characteristics and performance-inhibiting interactions are increasingly becoming decisive planning aspects in the case of heterogeneously structured overall systems composed of different technology systems.
Questions about dynamic behavior cannot be answered accurately using the statically dominated planning and calculation methods used today in the concept planning phase. This lack of planning quality raises the possibility of incorrect dimensioning of dynamic-dependent components, which leads to errors in selecting a preferred variant.
This problem can be solved using simulation technology. This is currently only used in the detailed planning phase for functional verification of a chosen preferred variant. As an example, in the current work, a concept for the efficient use of simulation was developed and implemented while still in the concept planning phase. The goal was to improve the quality of the planning results without the extra effort that simulation requires.
Standardized planning and simulation models, modeling methods, and data structures for heterogeneously structured picking systems were created for this purpose. A modeling paradigm was included, as well as standard building blocks and objects of heterogeneously structured picking systems. Another component was the creation of simulation models, structures, and elements that were generated automatically.
The methods were integrated into a planning environment that assists the planner throughout the simulation-based concept planning process.
The validation performed based on an application example revealed that early simulation integration results in a significant increase in the quality of planning and results.
This is especially true for dynamic-dependent dimensioning aspects such as buffer capacities, resource dimensioning, and downstream technology dimensioning. Furthermore, a planner in the concept planning phase gains a high degree of transparency and understanding of the dynamic behavior of the considered model variants. The general feasibility of incorporating early simulation into the planning process has been demonstrated in this work, and challenges and limitations have been identified.
The use of simulation technology in the concept planning phase of heterogeneously structured order picking systems will become more established in the future through additional research and development activities.
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