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3 Ways Simulation Modeling Optimizes Distribution Center Design

Tim Duket | 30 May 2019

System simulation modeling is a very effective strategy to validate the future-state design of a distribution center, but the benefits don’t end there. The insights that arise from modeling can also become valuable data points for design optimization.

Discrete-event simulation packages like FlexSim are driven by strong logical and graphical engines that provide the ability to view an entire operation represented in 3-D space, constructed with real data and system logic. Seeing facilities come to life in this way can help bring about fresh perspectives and new ideas that can then be virtually adjusted and proven within the model.

Let’s discuss a few applications and design questions for which simulation modeling is often applied.

simulation_modeling_flexsim_4Full System Validation

One of the most common applications of material handling simulation is to validate and optimize a full system design. As systems and operations grow in complexity, simulation can be a critical step in confirming that the design will work as expected. It is also a valuable tool to run sensitivity analysis and show how various potential changes would affect a facility’s future state.

There are innumerable questions to which a simulation model can provide insight. Here are a few examples that are commonly addressed:

  • Is the concepted facility capable of handling average and peak volumes as designed?
  • If we ‘stress test’ the design with extra volume, what area becomes the earliest bottleneck to arise? How can we alleviate this bottleneck?
  • Are the interactions between different functional areas optimized? How can they be improved?
  • Is there sufficient equipment processing capacity, buffer storage, conveyor accumulation, etc.? Would the design work better with more or less in some areas?

As these questions are addressed, they will spur additional considerations and new ideas on how the design can be better optimized. These insights often arise from the dynamic interaction between subsystems and can be difficult to observe otherwise.

Once a model has been developed through a focused simulation effort, it can also serve as an ongoing operational support tool for years to come. FlexSim’s user-friendly interface allows models to be set up so that different staffing plans, shift schedules, or slotting schemas can be quickly uploaded, tested, and compared.

simulation_modeling_flexsim_3Operator Functions

Along with equipment optimization, validation of operator functions and staffing requirements is a common initiative for simulation modeling. Designs can be sensitive to the interaction between manual functions and automation. Modeling the two can help address this sensitivity upfront, and there is a low cost to making adjustments or enhancements.

Some examples of questions and test cases for operator functions include:

  • What are the staffing requirements to run each functional area smoothly?
  • Are the processing tasks defined appropriately for each function?
  • Are the right operators performing the right process steps? E.g. work preparation, quality checks, manual handling vs. conveyor support, etc.
  • What is the breakdown of operator tasks between active processing time, travel time, delay times, etc.? Can the design be tweaked to minimize non-value-added tasks?

simulation_modeling_flexsim_1Proof of Concept

Sometimes, an individual task or piece of equipment is the driving force behind a simulation effort. In these cases, a smaller-scope proof of concept model may be the most effective way to quickly test and optimize the design. With a more limited scope, these can result in greater attention and scrutiny being given to the critical design components, often yielding significant benefits.

As an example, let’s consider a sawtooth merge. In high-volume distribution environments, sawtooth merges are often tasked with marrying substantial carton and tote traffic from various areas into one organized stream. This requires careful equipment design and controls logic, thus making them prime candidates for simulation optimization.

Some commonly-addressed details for such a simulation include:

  • Fine-tuning of conveyor lengths, conveyor speeds, and accumulation behavior
  • Placement of scan points, gapping belts, and photo-eyes
  • Optimization of controls parameters, such as slug size, release sequence, and gap size
  • Sensitivity analysis around overall rates, rates by infeed lines, no-read percentage, and wave sizes

Learn More

While every simulation model will have its own questions and objectives, powerful packages like FlexSim exist to provide a flexible and customizable tool to optimize systems design. Contact us today to learn more and discuss the benefits that simulation could bring to your design effort!

Author: Tim Duket

Tim is a Senior Engineering Consultant working out of Bastian Solutions’ Indianapolis Headquarters. He received his Bachelor’s and Master’s degrees in Industrial Engineering from Purdue University. As part of Bastian Consulting, Tim supports clients with design engineering as well as system validation through simulation modeling, spanning everything from small process improvement initiatives up to highly-automated facility design.

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