How can you use discrete-event simulation to plan logistics better?

Discrete-event simulation is a powerful tool for understanding and optimizing the behavior of complex systems. It allows analysts and decision-makers to experiment with different scenarios, policies, and configurations without the need for real-world testing, which can be expensive or impractical. By running simulations, one can gain insights into system performance, identify bottlenecks, assess resource utilization, and make informed decisions for system improvement or optimization. Applications of discrete-event simulation are diverse and include areas such as manufacturing, transportation, healthcare, finance, and logistics, where understanding and optimizing processes and systems are critical to achieving desired outcomes.

Modeling and simulation tools are decision-support tools for logisticians. The simulation should be built around phases that lead to the optimal solution by the model → Phase 1 Build the model as per the actual → Phase 2 Build a model that adheres to the organization's policies (this is supposed to be the Baseline) → Phase 3 Run optimized model The results of the optimized model should be used as a supporting tool for the decision-making

The interconnected nature of a supply chain make it a great fit with DES. A problem in one part of the supply chain can have a chain reaction to other parts, simulation is a great way to understand the impact of these chain reactions.

Simulation is a very effective way to assess your logistics network elements from the point of origin to the point of consumption. To simulate such a network you need to prepare your - model and - service level - Supply and demand constraints However, simulation is usually built based on simplicity which means simulations do not count for all elements and factors that will impact your supply network plan. But simulation always provides what-if analysis where the practitioners try to check and look at different scenarios rather than the company just stuck with the first optimal simulation provided by the simulation

Unlocking logistics excellence through discrete-event simulation! As an Operations Manager in training, I've seen how this powerful tool dives deep into our logistics processes. It helped me: Optimize Routes: Simulate different routes to find the most efficient and cost-effective ones. Resource Allocation: Ensure we allocate resources like vehicles and labor effectively. Risk Management: Prepare for uncertainties and disruptions by testing various scenarios. Performance Enhancement: Continuously improve our logistics system based on simulation results. This technology is a game-changer for modern logistics, and I'm excited to explore its full potential!

These 4 steps are the building blocks of any simulation model you will build Step 1. Scope and objective - The scope; cloud be supply networks design, or define the best inventory & customer service level - The Objective: to minimize the cost of supply network, or maximize the profit of certain product. Step 2. Define the most relevant KPI - What to and how to measure impacted by the industry and business model - Whenever you build a KPI it's important to link it into the SCOR-DS model which ultimately will be used for the company top level KPI Step 3. Building model and collecting data - the model shouldn't be complex models always lack the full reality Step 4. Use the results of the simulation as supporting decision tool

Besides all the benefits for the simulation we need to keep in mode the following - The simulation is a pure mathematical. - The results of the simulation is your supporting decision tool. - Simulation and model cannot incorporate all the real life complexity. - Simulation assume stationary

The most important part when it comes about building the model is The a mount of data and The integrity of the data How accurate the data is what makes the results of the simulation reliable.