| Summary: | The main objective of this study is to investigate whether any of three selected MRP methods could reduce inventory and inventory related costs at NUHI’s central storeroom. NUHI recently adopted the JIT/Kanban so an evaluation of their new system was made by comparing NUHI expenses with the consumer price index (CPI). However, the focus of this research was on NUHI’s central storeroom, which services the JIT/Kanban system but itself uses a s,S inventory policy. Three Material Requirement Planning (MRP) lot-sizing techniques, The Economic Order Quantity (EOQ), The Silver-Meal heuristic (SM) and The Least Unit Cost heuristic (LUC) were compared to the central storerooms current system of choice. NUHI provided daily demand data for 60 items which were chosen with an ABC analysis. The data was analyzed and used as an input for an inventory simulator created to compare the four inventory control methods. Under simulation there the current s,S policy performed significantly best by returning the least total cost. The simulation also shows that the amount of money tied up in inventory can be reduced significantly by improving visibility and adjusting the service level. The research concludes that NUHI must define the goals and parameters of its supply chain in order to properly evaluate its supply chain system. Furthermore, a way to improve visibility and reduce inventory at the central storeroom is suggested. Also, all methods are discussed theoretically and a literature review presented with theoretical and case studies relevant to this research. Aðal markmið þessarar rannsóknar var að ákvarða hvort einhver þriggja MRP aðferða gætu bætt núverandi birgðastýringu á birgðastöð Landspítala – Háskólasjúkrahúss og minnkað tengdan kostnað. Landspítalinn tók Kanban í gagnið árið 2004 og var árangur þeirrar innleiðingar metinn með því að bera saman kostnað við rekstur spítalans við vísitölu neysluverðs. Rannsóknin einblíndi þó á birgðastöð spítalans sem þjónustar Kanban kerfið en notar s,S kerfi til að stjórna sínum lager. ...
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