Material flow simulation

from Wikipedia, the free encyclopedia
Areas of application of the simulation along the value chain

The material flow simulation is a simulation in connection with logistic systems . It is one of several ways of measuring performance and generating optimization knowledge. It is used in production and assembly processes , in maintenance and repair processes, in warehouses , conveyor systems , workshops , distribution centers , and airports . The planned or already existing conveyor and production elements are represented in a kind of modular box principle. The individual elements together form a network that can be used to map various systems.

The material flow simulation enables a comparative evaluation of different production scenarios without having to intervene in ongoing production. In this way, material flow optimization can be tested comprehensively before implementation. The material flow simulation is carried out with special simulation software such as Plant Simulation, AnyLogic or ExtendSim, with which the process to be considered can be modeled, parameterized, simulated and analyzed. One of the advantages of material flow simulation is to help identify external and internal (negative) influences and to predict their effects. The benefits of the material flow simulation are: speed, usability, holism and scalability.

Simulation in the planning

With the help of a simulation model, new production systems are checked for throughput , sufficient dimensions, lead times , performance limits, disruptive influences, personnel requirements and other planning parameters. In addition, various alternatives can be evaluated and compared with one another. A ranking of the planning variants is generated based on previously defined criteria. A preference relation defines the target combination by which the target system should be characterized.

Existing systems are mapped in their current state and optimized through targeted modifications within the model. For example, using a different control strategy can lead to higher throughput.

Simulation in implementation

The simulation model is used by the control programmers as a template for creating the system control . The result is faster, error-free commissioning . A coupling of the central administration computer (dispositive control computer) with the simulation model enables commissioning before use in the system. The startup behavior can be run through in various scenarios. This is particularly important when commissioning is carried out during ongoing operations and a smooth transition to the new system is required.

Simulation during operation

The predictive test of the daily program of a plant provides information about the necessary provision of personnel and resources, about order processing times and about the utilization of the plant. The optimization of the order sequence in the run-up to day-to-day operations can be verified with the help of the simulation model. The reaction of the system to malfunctions can also be examined and improved accordingly.

Simulation and modernization (retrofit)

In the case of modernizations, the simulation enables a tailor-made solution. Some programs meanwhile also offer the possibility of simulating the energy consumption and thus optimizing the operating costs in this respect as well. Similar to the re-planning of complete systems, the various influencing variables and parameters are changed until smooth integration of the modernized area into the overall system can be guaranteed.

Optimization through simulation

The simulation cannot, as with the optimization of analytically solvable problems, show the optimum. The simulation only provides result data for certain scenarios that are evaluated. Depending on the objective, the different scenarios can be ranked ordinally (“better than”, “worse than”) or cardinal (absolute values). The production system can be improved by adjusting the inputs until a better solution is found. Optimization is therefore an iterative process in which input variables are adjusted, simulation experiments are carried out, result data are processed and evaluated and, based on the objective function value, it can be decided whether the new scenario has led to an improvement in accordance with the objective. Optimization by means of simulation presupposes that a decision can be made between different alternatives (scenarios) which scenario is the best according to the objective. In an optimization project, the optimal values ​​for the individual influencing variables should first be determined. If the interaction effects of the influencing variables are to be examined in the following step, the values ​​belonging to the optima of the individual influencing variables can be combined with one another.

Cost-benefit ratio

According to VDI 3633 , the cost-benefit ratio of a material flow simulation is 1: 6. While the costs initially increase in the planning phase, they decrease considerably in the operating phase due to the lower need for improvement.

Individual evidence

  1. ↑ Material flow simulation as a means of automation. Retrieved July 19, 2019 .
  2. ↑ Simulation-based optimization
  3. ↑ Material flow accounting and simulation. Study letter from SRH Hamm, Prof. Dr. Markus Fittinghoff, 2010

Web links