Simulation is the process of developing and experimenting with a computer model of an existing or proposed system to predict, test, and verify its performance under a variety of scenarios. By creating a digital laboratory, we can evaluate alternative configurations of equipment and processes for an integrated system and identify those that result in the best overall performance.
Simulation allows for testing and evaluating the impact of changes in demand, inventory mix, peak volumes, order types, resources, and more on performance prior to deploying a new solution or investing in costly modifications to an existing solution — ultimately improving performance and mitigating risk.
Simulation models offer the following key benefits for organizations throughout the design, engineering, and post-commissioning phases of an automated warehouse or distribution center (DC) project:
- Simulation allows a proposed design to be evaluated to ensure it meets the stated objectives prior to incurring significant costs for solution deployment and real-world testing.
- Simulations can capture and evaluate the current state of existing operations based on customer data, including order profiles, demand forecasts, equipment specifications, and staffing levels. This helps to identify bottlenecks, material flow problems, and capacity constraints. It also enables experimentation with slotting configurations, the number of picking workstations, vehicle fleet sizes and more.
- Sub-systems within an operation can be modeled in isolation more quickly to test and ensure proper functionality prior to integration into a comprehensive model of the larger system. This is useful for assessing the potential impact of a new piece of equipment or targeted modifications to a portion of an existing operation to build confidence in the solution prior to deployment.
- Once a solution concept is finalized, simulation is used to flesh out the design more precisely (from “feet to inches”) and address specific engineering concerns by testing a variety of operating configurations. This is particularly crucial when engineering complex systems comprised of multiple automated material handling technologies and/or mobile automated vehicles (MAVs). Simulation also supports testing of different algorithms and prioritization schemes that are then translated into programming rules for the actual system control software.
- Post-commissioning, simulation models that are maintained to accurately reflect the current state of the deployed solution can be used to test alternative scenarios and quantify the benefits of proposed changes without incurring costly disruptions to day-to-day operations. It is both faster and less expensive to answer questions in a simulation model than to make modifications to a real-world system. For example, simulation can be used to determine the number of MAVs needed to achieve target throughput for continually evolving demand profiles, or if throughput is improved by dedicating one shift to replenishment and a second to picking and packing.
Is simulation right for your operational needs? Wherever you are in your operational improvement journey, KPI’s simulation experts can help you explore your options. Contact us today.