Abstract
Production lines modelling has many problems that are difficult to be solved using analytical solutions, due to uncertainty and/or variability in variables and parameters. This paper is targeting unreliable production lines with finite buffers for the objective of evaluating and analysing the current situation and identifying bottlenecks. We use discrete event simulation to model a real production line based on one-year historical data about the breakdowns of all the production line's machinery. This data is used to find appropriate probability distributions to represent each machinery downtime and uptime. The simulation model is built using AnyLogic software to abstract the actual production line, and the model is validated using the actual data and information about the production line. Improvement scenarios are proposed to resolve the observed bottlenecks, and therefore give managerial insights to increase the throughput according to the increasing demand. Finally, production plans are set for different demands along the year.
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