A leading CPG- food and beverage company wanted a framework that measured, monitored, and improved the overall equipment effectiveness (OEE) across their manufacturing plants in the USA. The existing methodology wasn’t sophisticated and the learning system was difficult to scale and improve over time.
Sigmoid built an AI solution that evaluated the production line data and identified inefficiencies and recommended corrective action to improve OEE of machines. Modern ML techniques were used to generate and test multiple combinations of patterns for identifying trends and anomalies. This helped to continuously churn data, produce insights, and flag different areas of concern.
The solution resulted in a 2.5% improvement in OEE apart from enabling real-time alerting for machine downtime, failure, and line losses.