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The current methods of economic justification are not suitable for identifying the benefits of automated manufacturing systems. This study is an introduction to Flexible Manufacturing Systems (FMS), its main features, and the economic benefits that can be expected. The models are designed to perform the following analyses: 1. Analysis of direct cost savings. 2. Analysis of the impact of incremental implementation on capital recovery costs. 3. Analysis of the cost effects of improving machine utilization and reducing manufacturing lead time. 4. Sensitivity analysis of the after-tax equivalent uniform annual cost of a FMS and a conventional system. The models are built to (1) utilize readily available data or output data from simulation studies, (2) provide reliable results, and (3) simplify reality to a small package of information that facilitates effective decision making. To explain the models and to analyze empirically the economic performance of an FMS, the models were fed with published, assumed, or generated data. The output of each analysis is summarized in tables, depicted in graphs, and specific conclusions are synthesized at the end of each model presentation.

At this time there is an increasing emphasis in Florida on developing large, multipurpose complexes which include shopping, entertainment, and accommodations for tourists. In all cases a major design problem is people transportation. For best efficiency the primary mode of transportation, the car, must be exchanged for other people movers within the complex, which will afford more security, flexibility, and better movement of people to their ultimate destination. Economically speaking, this would not only conserve fuel, but would allow consolidation of automobile parking into a less desirable area and the grouping of facilities for more shopping and recreation convenience. An example could be typified by a large complex of scattered hotel/motels, which must handle people and their belongings efficiently. One such case is the hotel operations at Walt Disney World. At the present time, only the Polynesian and Contemporary hotels are operating; however, future hotels are planned. Permitting cars to drive directly to the hotel introduces much confusion, traffic congestions, and additional effort on the part of guests and host. A cursory review of WDW hotel operations reveals the alrge amount of effort which typically much be expended into processing the guests and their belongings to and from their room. To be meaningful any such study must include all aspects of guess processing and the interrelationships of the major functions, such as transportation, material handling, and guest treatment. Because of the size and complexity, this can only be done by simulation. This research used simulation to test the Guest Welcome Center concept. The proposed Walt Disney World Guest Welcome Center would feature a luggage unloading area, special parking lot for hotel guest vehicles, convenient reception and registrations, orientation for new guests, and transportation to the hotels and Theme Park. It would further feature luggage containerization, with a special container tram running to and from the hotels. A computer simulation model of the proposed Guest Welcome Center was developed, and its performance analysed. The measures of performance were the maximum length of waiting lines and the maximum number of facility service channels needed, both by hour of the day and the average waiting time spent by hotel guests at various locations. The model performance defined staffing requirements and floor space requirements for guest waiting lines and luggage storage. Further, the simulation study lent insight into the nature of the system and suggested changes which might improve it.

This thesis describes the development of a Model Analyzer prototype for the Simulation Model Development Environment that analyzes the specifications of a discrete-event simulation model. The Model Analyzer provides early feedback by operating on model specifications instead of waiting until an executable version is produced. Analysis of model specifications allows the modeler to detect errors early in the life-cycle and provides information about the model that may prove helpful in the verification, validation, and eventual translation of the model. With the help of a graphical user interface, the Model Analyzer provides automated and semi-automated support to the modeler. The Condition Specification, a world-view independent specification, of a model is parsed and stored in a relational database. Using graph-based diagnostic techniques, the Model Analyzer presents graphical representations of the model and performs analytical, comparative, and informative diagnosis. Also, an expert system is developed that uses generic simulation knowledge to simplify one graphical representation of the model. Based on the accomplishment of the design objectives, an evaluation of the Model Analyzer is conducted. Results from the expert system and Model Analyzer are provided that indicate the Model Analyzer and the expert system are helpful analysis tools. / Master of Science