Internship: Graduation Thesis Master
Machine Learning decision tree for slow movers
Are you looking for a graduation master internship? Gordian offers an internship for a graduate student, starting September 2021.
The clients of Gordian are dealing with slow moving parts, which means that there are not a lot of historical demand requests available. To compute a forecast on historical demand becomes a challenge. That is why we also use other input sources such as business knowledge of engineers, the installed base, criticality analysis and general part information (such as failure prediction, MTBF). However we would like to have a standard model to come up with the optimal stocking strategy.
Your assignment is to create an inventory strategy for slow-moving items which provides outcomes on whether or not to stock a part, quantities, locations, etc. To do so, we would like you to develop several decision trees with which we can determine the optimal strategy per item. Using machine learning techniques you will create the input and content of the decision trees. By calculating different scenarios you find out which techniques give us the best trade-off between downtime and inventory costs. Finally you show the improvement of the new model by computing the new balance between stock availability, ordering costs and stock value and compare these results with other solutions.