Special fields in logistics planning Simulation

Special fields in logistics planning

Your contacts

Michael Borowski and Martin Schöne
Michael Borowski and Martin Schöne Heads of logistics planning
+49 351 314423-200 Email

Improving and securing complex logistics planning

If planned logistics solutions are subject to particularly dynamic influences or if they are highly complex, analytical methods will eventually reach their limit. In order nevertheless to validate the feasibility realistically, simplified mapping of the reality and/or of the planned flow in the simulation model is suitable for this. In this way, various mechanisms of intransparent systems can be traced optimally and corresponding measures can be derived. For instance, early decisions regarding the most efficient system size can be made realistically and costly over and undersizing can be avoided. In accordance with the customer requirements, LOGSOL uses various tools for simulation studies, which can map both smaller solutions for buffer dimensioning and capacity proof / simulation of complex systems. The aim of a simulation is the examination and/or verifiability of a planned solution under dynamic influences.

Dynamically validated logistics solutions

  • Mapping the concept in the simulation model
  • Understanding mechanisms of intransparent systems and deriving measures
  • Determining efficient system sizes and avoiding costly over or undersizing
  • Making findings plausible by visualising the simulation runs

The simulation process

Objective

  • To clarify questions regarding the study and define the depth of detail of the simulation
  • To discuss essential KPIs for assessing the simulation study

» Close coordination with the customer

 

Process analysis and data collection

 

  • On-site recording of the processes to be mapped on a simulated basis
  • Data collection - recording
  • Sensible relationship between data collection workload, use of approximate values and quality of the simulation result
  • Data preparation including derivation of statistical distributions

Model formation

  • Modelling the process within the defined system limits and using the correct simulation software
  • Mapping serial and parallel processes, fluctuating processing times by means of statistical distributions, realistic machine availabilities, valid shift schedules…
  • Transfer control rules from process planning to simulation study (based on concept)
  • Implement measurement variables to make the task to be mapped assessable in the model

Validation

 

  • Verify consistency of the implemented model with the system to be mapped (limiting performance, plausibility test)

Experimentation

 

  • Generation of an original experiment on the basis of the process analysis with sensible values for the parameters to be varied
  • Determination of the design of experiments for the efficient performance of the simulation study
  • Sensitivity analyses for the exact determination of the system behaviour
  • Prepare and interpret results of the simulated scenarios in table/chart form
  • Presentation of the findings acquired by means of simulation for the real system and recommendation of suitable system configurations

» Close coordination with the customer

Animation

 

  • Animated presentation of the simulation runs as a film clip for plausibility check, validation and presentation purposes
  • Graphic presentation of system changes using meaningful diagrams
  • Highlighting capacity utilisations, potential and bottlenecks