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The Benefits of Logistics Simulation Software

7Oct, 2014
The Benefits of Logistics Simulation Software

Supply chain management is a complex undertaking. It involves dealing with multiple flows of goods and information across networks of suppliers, warehouses, shippers, and carriers. One way to help manage this almost overwhelming complexity is to use sophisticated simulation software. Simulation software for logistics allows the use of real-time, real-world data to stage mathematical analyses of “what-if” scenarios.

These simulations are incredibly useful for exploring the possibilities contained within the dynamic events that drive your business and affect your supply chain. The information produced by these mathematically complex simulations can help companies optimise logistics strategies for maximal efficiency and cost-effectiveness, as well as planning for possible adverse or otherwise unexpected events predicted by the simulations.

Making use of simulation software programs can help companies to:

  • Improve lead times
  • Reduce excess inventory levels
  • Make the most efficient use of available resources
  • Resolve warehousing issues
  • Reduce inventory costs

Logistics simulation software uses advanced mathematics to predict possible outcomes and scenarios based on available real-world data. The use of simulations can help companies think ahead, and can shed light on possible events that may not have been expected or predicted otherwise.

Applications of Logistics Simulation Software

There are several areas of logistics in which computer simulations can prove highly useful. Some of the common areas of logistics explored with simulations include:

  • Supply chain management. Supply chain management simulation software works by modeling dynamic scenarios based on the many complex variables that are involved. The information produced by these simulations can be used to improve accuracy and efficiency, as well as identify areas where costs could be reduced. Data on parameters such as workers, capacities, conveyor speeds, and other relevant factors can be used to choose the most effective solutions.
  • Transportation modeling. Transporting products can easily become costly, especially with the variability of unpredictability of fuel costs. Simulations of transportation systems can help provide companies with information that can be used to maximise efficiency and reduce costs, as well as reducing transport time. The layouts of routes and stations can be modeled with precise distances, and modeling different scenarios can reveal how processes affect other events “downstream.”
  • Warehouse management. Warehouses are places with a high activity level. A lot of things going on at once, meaning there are a lot of variables that affect things further down the line. Simulation software for warehouse management can implement real data to model aspects of receiving, picking, and distribution, creating a variety of “what-if” scenarios that can help companies plan for all contingencies. Information for warehouse management simulations can reveal ways to reduce costs, increase efficiency, and maximize profitability.
  • Conveyor belt systems in warehouses and factories. The movement of goods within factories and warehouses involves many variables, which simulation software is able to model in order to predict possible courses of events. These programs can help companies to visualise where bottlenecks, backups, or other problems are occurring, and to model possible solutions in order to figure out how to best fix the problem.

Sophisticated simulation software can be used to model many aspects of logistics, producing mathematically precise information about possible courses of events. Transportation networks, intra-warehouse conveyor belt systems, supply chains, and other aspects of logistics management all constitute complex systems, and in these kinds of real-world networks, there are many variables that, in turn, affect other variables down the line. By using simulations, your company can gain key insights into problems that could arise in the future with these systems, and discover optimal solutions for both solving them, and increasing efficiency.

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