Two-Phase Modeling Approach for Future-State Facility Design

SIMCON employs a two-phase modeling approach for our facility simulation projects when it stands to benefit our clients and when the project requirements suggest a need for this approach. The two-phase modeling approach consists of separating the production scheduling component of the simulation into an independent model, and using the schedule generated by that model as input to drive a more detailed facility simulation which introduces system constraints such as labor and material handling. This approach can be important when the operation being scheduled is a downstream operation.

In our two-phase modeling approach, we first develop a scheduling model that uses a production plan (or equivalent data) provided by the client to create a production schedule for the facility. The scheduling model only includes the level of detail necessary to derive a valid and ideal production schedule. The schedule outputted by the scheduling model is used to drive the facility model (or set of facility models) that simulate plant operations at the level of detail necessary to evaluate the facility design as specified by the client.

This modeling approach is critical, as it ensures the results and conclusions derived from the modeling effort are based on an accurate representation of day-to-day operations at the facility. The two types of models (scheduling and facility) can be developed in parallel to streamline the delivery of value and reduce overall project length. Key questions and issues regarding longer lead-time items (e.g., large equipment, floor operations, etc.) can be addressed sooner, and labor and material handling issues which have shorter lead times can be addressed later in the project.

The scheduling and facility simulation models are designed to be completely data-driven so they can be readily adapted to support the scheduling and design of other facilities owned and operated by each client. All pertinent system parameters such as equipment configurations, staff and vehicle specifications, product definitions, and part routings are modeled as data-driven inputs which can easily be modified by updating the accompanying input data files. By taking this approach, we can leverage the models developed for this project to support the design and analysis of other client facilities without incurring the typical model development costs.