Current State Simulation Scope of Improvement and Forecast Demand Analysis at AstraZeneca using Discrete Event Simulation.

University essay from Mälardalens högskola/Akademin för innovation, design och teknik

Abstract: In this rapidly changing product demand market, the pharmaceutical companies have adapted their production system to be more flexible and agile. In order to meet the demand, production lines need to be more efficient and effective. Even a small improvement is a great achievement as these production lines are designed to produce large volumes of medicines. To test the efficiency and effectiveness of the lines by analyzing production data would be time taking and needs the involvement of experts from different departments. When production lines are subjected to change, previous analysis done will no longer be valid and needs to be repeated again. Instead, this can be replaced with discrete even simulation analysis (DES).     DES is one of the key technology in developing a production system in this industry 4.0 era. As the production systems become more and more complicated it becomes difficult to understand and analyze the behavior of the system if there are any changes brought up in the system. Simulation is the right technology to analyze and understand the behavior of the real system when undergone small or big changes.  The purpose of this case study is to make use of DES using ExtenSim as a simulation tool at the case company in order to develop a virtual model of a production system containing five production lines to understand the behavior and analyze the production lines to identify possible improvement and evaluate the feasibility of production system to achieve the forecasted demand. Possible improvements are identified from the simulation results of the current state model and a future state simulation model is developed with the improvements. Furthermore, this future state simulation model is used to analyze the feasibility of production lines for forecasted demand. By developing the simulation model was identified that the production lines were not efficient and are underutilized as that the company assumed.  

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