Dynamic Thresholding Leading to Optimal Inventory Maintenance

Suresh K. Choubey, Ryan Benton, Tom Johnsten

Abstract: Optimal inventory management always requires the right number and types of parts to be available at the right time at the right place. However, this has become even more critical in the age of prescriptive maintenance, which seeks to predict an impending failure along with what part(s) are about to fail. To take advantage of these predictions, it is essential that the parts, personnel and time frame are made available in a timely fashion to keep the operation going uninterrupted. Usually, the level of parts maintained in a part warehouse is determined using static thresholding where quantities of each part is determined and is fixed for a given part. In literature, such methods are known as static thresholding. While work has been done to accommodate unpredictability of parts usage in supply chain, there is lack of attention that has been paid to consider the demand of parts in future due to prediction of impending failure. To address this, this paper introduces a noble method and system, entitled dynamic thresholding, to ensure the part inventory adapts to predicted usage while maintaining minimum inventory management cost. The feasibility of the concept and system is demonstrated using simulated datasets.