Case Study:
48% improvement in manufacturing quality
Reducing manufacturing rework through data-driven quality control
The Client
A leading manufacturer of renewable energy infrastructure.
The Problem
Our client is a specialist in a specific area of renewables manufacture. It was facing recurring quality issues during final on-site testing, which led to costly rework and delivery delays. It wanted to improve quality control at the manufacturing stage, helping to reduce delivery delays and potential fines.
The QEA solution
After collecting and analysing nearly 700,000 observations, including all the current tolerance levels that were set, we could see that there were some key areas where the business could focus, based on patterns revealed in the data – a correlation matrix – that would ensure better quality control at the manufacturing stage. We identified the ideal tolerance levels for each of these processes, based on intelligent data analysis.
“We always had data—but we didn’t have clarity. Insight Delivered helped us uncover what truly impacts product quality. The AI-powered insights shifted us from reactive fixes to proactive control, driving down rework and improving consistency.”
Director of Manufacturing Quality
The result
Our work with this client shows how it is possible to collect and analyse huge quantities of disparate data, and then apply AI to produce a measurable result. In this project, results included:
