-by Mike Judd
Having the right spare parts in the right place at the right time enables us to keep operating and create revenue. On the other hand, holding too many or the wrong spare parts adds unnecessary cost. Many organizations have low quality and poorly structured inventory data, significantly hampering the ability to hold the right spares and only the right spares.Large Language Models combined with Machine Learning and Subject Matter Experts provide practical and cost effective methods for significantly improving data quality and structure. This enables us to effectively model the optimum stock levels using appropriate probability distributions for spare parts demand and supply.Combining these methods and taking action can significantly improve uptime and reduce costs.