by Dusan Sormaz and Mandvi Malik (Ohio University)
As presented at the 2017 Winter Simulation Conference
Order picking is the most expensive operation in a distribution center. Due to a large amount of labor used in order picking, the cost associated with the labor is high. The objective of this paper is to build a simulation model that would help distribution center managers to forecast their throughput by optimizing the worker configuration. The research uses a hierarchical approach to build a simulation model. The simulation model is divided into small submodels. The submodels are completely independent of each other. The submodels can be combined to make various different complete models. In this research, the submodels are used to build a simulation model of an actual industrial distribution center. The model is then run for twenty-four hours and the results are compared with the flat simulation model of the same distribution center.
Introduction
Simulation has become a potent technique used by supply chain companies as a decision support tool [1]. There are many benefits of simulation in supply chain as it can help in identifying the bottleneck and performing experiments to minimize the risk of changes [2]. The objective of this research is to build a simulation model that can be reused to make various different distribution center models. The model is built using Simio [3].
There are two approaches to solve a problem in Simio. The first approach is to make a model in which entity flow logic is done separately for each object and repeated for each similr object. This model is called flat simulation model using standard objects. A second approach is a hierarchical approach that is to divide the problem into several small subproblems. In hierarchical approach, a library of submodels is created. The submodels are used as objects to create a comprehensive model. The submodels can be reused to make another model. The present paper uses hierarchical approach. The benefits of creating a simulation model using hierarchical approach over flat simulation model are following [4]:
- All the options to solve a problem can be included which is not possible in a flat simulation model,
- The validation and verification are done faster and they are more reliable since the logic would be tested at small submodel levels,
- Modifications of the model are done faster,
- Through multiple models and different approaches to the model design, we can eventually build better models in the future.
For our study, applying the hierarchical approach allows the following benefits:
- Low level model can be reused for different distribution center configurations,
- Component models can be used for other order arrival policies,
- Verification of component models individually enables faster model development.