2013 ASHS Annual Conference

For many years, decision makers have been using process modeling tools to influence design and improvement of complex systems.  Typically, these efforts are associated with environments such as manufacturing or transportation systems. Conditions found in these systems are well suited to simulation modeling due to their inherent complexity, variability, and inter-connectivity of system components. If we consider the components of a nursery production system, we see a close relationship to a typical manufacturing system characterized by multiple raw materials coming together with the aid of a labor component to form a finished product. This product must be transported, re-configured, inspected, and tracked multiple times during its life while at the nursery. To this end, many process design decisions made by nursery managers, are then, no different than those made in a traditional manufacturing environment. Decisions to make process changes in order to achieve a positive result in either cycle time or throughput are historically made based on trial and error or expert judgment. An ability to model these changes and simulate their impact over time without actually making a physical change to the operation should, theoretically, result in better decisions. A discrete event simulation program was used to evaluate its effectiveness in predicting system performance resulting from various process changes to production conditions found at container nurseries in the Gulf South. The simulation tool used in this study was specifically designed for manufacturing environments, but has the flexibility to model virtually any process. For this study, a limited number of container nursery processes were investigated. Changes in process cycle time and throughput were determined after comparing various "what-if" scenarios run over many replications simulating days, weeks and months of time. Decisions including relocation of processes, changes in number of workers, changes in transport/movement parameters and additions/changes in equipment were evaluated to demonstrate the feasibility of using this modeling tool in a nursery environment. Continued use of this tool will be evaluated to determine the possibility of adding custom operating parameters to allow model use with minimal programming knowledge.