Case Study: a leading manufacturing company reduces downtime with i-Verve's AI-powered predictive maintenance solution

a leading manufacturing company cuts unplanned downtime by 40% with i-Verve

A major manufacturing company faced challenges with unplanned equipment downtime and high maintenance costs due to its reactive maintenance approach. It engaged i-Verve to develop an AI-powered predictive maintenance system to address these issues.

i-Verve implemented a solution using machine learning models built with Python and a cloud platform on Microsoft Azure, integrating IoT data and the client's ERP system. This predictive system reduced unplanned downtime by 40%, cut maintenance labor costs by 30%, and achieved 25% overall savings in maintenance expenses for the client.