A network simulation model of a fish processing facility

Abstract

Quick-freezing, the single, most important production method in the fish processing industry, involves a number of production workstations. The mathematical analysis of such a system not only involves the process flow but also includes such factors as scheduling priorities, machine failures, and types of inputs and outputs. The resulting mathematical analysis is extremely com plex to conduct and difficult to explain to the production managers.

A network-based simulation model is developed to analyze a fish processing facility, and the quick-freezing process in a typical fish processing plant is described. The network simulation model is then developed using the Simulation Language for Alternative Modeling (SLAM). Among the results from the model are statistics on utilization of machines and workers in the process, size of in-process inventory at different locations in the process, and throughput times. Sensitivity analysis is performed on some of the major factors that can affect the efficiency of the system. A front-end interface to the simulation model is developed which facilitates the user in entering input parameters to the model without the need to learn the simulation language. The model provides a methodology for evaluating alternative production strategies for a fish processing facility, and provides the production manager with a tool to develop short-term production policies.