Internal Transportations Optimization Supported by Simulation Model for Evraz

Internal Transportations Optimization Supported by Simulation Model for Evraz

Creating a simulation model to assess the initiatives of internal logistics optimization. Using the simulation to compare the internal logistic network design options for EVRAZ, one of top-3 metallurgical holdings in Russia.

Period: May 2015 – October 2015
Industry: Mining
Client / Partner: EVRAZ / BearingPoint

Project objective

Assess the initiatives of internal logistics optimization

The main stages of work and characteristics of the model

  • The simulation model concept development
  • Development and testing of a simulation model on the AnyLogic 6 platform
  • Taking part in preparing the data for modeling
  • Verification of the model on historical data
  • Scenario analysis using the simulation model
  • Support consultants’ team on scenario analysis and results interpretation phase

Model input data

  • Logistic categories of materials and their dimension and weight measurements
  • Historical data of internal cargo flows by materials, storage locations, workshops and equipment
  • Technical characteristics of transport (average speed of transportation, capacity, current number of vehicles in fleet, etc.)
  • Loading and unloading performance by logistic categories, storage locations and recipients (workshops and equipment)

The main structural elements of the model

  • Input data file of scenario in MS Excel format
  • Simulation model with interactive presentation
  • Data aggregation module that allows to generate MS Excel files with the simulation results

Model output data

  • Total costs within the period of modeling
  • Weighted average delivery price of materials
  • Service level of supply
  • Transportation and loading resources time utilization
  • Logistic resources utilization
  • Volume of materials stored in central warehouse
  • Average inventory cost

Project result

  • Allocation of storage capacities and materials transportation options between workshops were suggested
  • Internal logistics optimization suggestions were evaluated
  • The effect of central warehouses consolidation and transition to fully centralized distribution of materials was calculated