12.2: Points Made in the Case Study

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This FMS case study shows how optimization models and simulation models can be used together to address system design and operation issues. An optimization model is used to assign parts, and consequently the tools need to operate on the parts, to machines. A simulation model is used to assess how well the system operates using this assignment.

In modeling an FMS system, each machine and each tool is modeled as a resource. In addition, the model must keep track of which tool is on which machine. Thus, complex logic for assigning resources representing machines and tools to work on parts represented by entities is required. How to choose between alternative resources must be specified. Here, a choice between machines to perform the same operation must be made.

The simulation model must include the concurrent use of two resources, one a machine and another a tool. Furthermore, a selection among available machines must be made. Such logic may be coded in a high level programming language, such as C, and referenced from the simulation model.

Complex system control logic may be included in a simulation model. In this FMS model, a part waits to begin an operation until the required tool and any of the machines that can operate on it are available. A list of such waiting parts must be maintained. When tool and machines resources enter the free state, the model must search the entire list of waiting parts until one that can be processed by the newly freed resources is found. It is possible that no such part will be found. If the simulation engine does not examine each entity waiting for a resource, then logic to search the entire list of waiting transactions must be specified by the modeler.

Previously, arrivals in a model represented a single entity entering a system. In this case study, parts arrive to the FMS in a batch. Thus, an entity arrival in the model represents a batch of parts. An arriving entity is cloned to create one entity for each part.

A system may be sufficiently complex that simulation is necessary for analysis, design, and understanding even if no quantities are modeled using probability distributions. This is due to the structural variability in the system. Pritsker (1989) estimated that about one-third of all simulation projects employ deterministic models. In this case study, the assignment of tools and part operations to machines over time is sufficiently complex that an intuitive understand of system dynamics is not possible. Simulation is necessary to assess the affect of proposed assignments on system operations.

The length of the simulation run need not be specified as a constant time but could be specified as a condition to be met. In this case, the ending simulation time is the makespan of a production run, a performance measure of interest.