Development of Materials Management System : Case Black Bruin Inc.
Saukkonen, Anton (2017)
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This thesis work was assigned by a manufacturing company called Black Bruin Inc. BB Inc. is the world leading supplier of radial piston hydraulic motors and rotators. The aim of this study was to develop the company’s materials management system, which included the inventory control and costing model. In addition, the optimization of the total inventory cost was implemented regarding the optimal values of the decision variables. During the research process, the author used the mixed research method, which included elements of both qualitative and quantitative methodologies. The core data for the study was obtained from a literature review, interviews, observations and case-study examples. Based on the collected information, the author identified the most appropriate inventory control solution for the Black Bruin Inc. case and constructed it in Excel by using VBA (Visual Basic for Applications) code features. Furthermore, the constructed model included a costing model where the elements of the total inventory cost could be seen, analysed and calculated on a common or separate basis. As a result, the constructed model could be used as a tool in the decision-making process regarding the inventory operations. The model can compute the optimal order quantity and reorder point decision variables regarding the minimum objective value of the total cost. Moreover, the model calculates the values of inventory performance measures and allows adjustment of the decision variables, indicating the effect of change on performance measures and the total cost of inventory. Furthermore, the model also includes a sensitivity analysis which emphasizes the most uncertain input-data elements and allows their alignment. Finally, the study as well as the constructed model were analysed, and the essential outcomes derived. At the end of the research process, the author outlined the advantages and disadvantages of the model as well as its most sensitive and uncertain elements. In addition, guidelines for the model’s usage, suggestions for improvements and further research recommendations were given and thoroughly explained.