Case Study: Mecánicas Aparicio improves production forecasting and efficiency with Bravent's XGBoost predictive model and analytics chatbot

Mecánicas Aparicio reduces unplanned production hours by 40% with Bravent

Mecánicas Aparicio, a company specializing in laser cutting and machining, faced significant production challenges due to manual part analysis, which caused delays, resource misallocation, and quality errors. They sought a solution from vendor Bravent to automate analysis and improve data-driven planning and decision-making.

Bravent implemented a predictive model using XGBoost to forecast production times and an analytical LLM-based chatbot for natural language queries. The solution delivered an 80% improvement in cutting time predictions and a 66% improvement in bending predictions. This resulted in a measurable ROI, including a 40% reduction in unplanned production hours, reduced costs, and improved inventory efficiency for Mecánicas Aparicio.

Mecánicas Aparicio