Drug allocation at the auto dispensers of a smart pharmacy - Ong, Bryan Yu (2019)
This report outlines the documentation of the development of the optimal drug allocation of Automated Storage and Retrieval Systems (ASRS) used for a highly automated smart pharmacy in Changi General Hospital (CGH). In CGH, the ASRS dispenses prescribed drugs automatically to shorten the work flow and minimise waiting time for patients. However, it is difficult to find the optimal setting of the ASRS due to its complex nature. This paper aims to find the optimal drug storage assignment in the ASRS by exploring different storage assignment methods, analysing historical drug dispensing data from the smart pharmacy in CGH and using computer simulation to compute results based on different storage assignment methods. Using MATLAB, the different storage assignment methods were simulated for the historical data of prescription orders and the total time taken for the process were compared. It was found that full-turnover-based storage assignment method were far more efficient compared to a random based storage assignment method. Simulation result shows the more optimal drug allocation method recommended for CGH to apply to their ASRS. Further refinement of the model can be done by considering a longer period of historical data to be used in the analysis. A higher accuracy of simulation can also be achieved by accounting for different reference points used. Further research can also include the interdependencies of the relevant drugs used in the historical data.