Barry Callebaut: Boosting Factory Efficiency

Industry: Industrial Engineering
Solution: ML-based Anomaly Detection & Production Optimisation
Impact: Increased production line efficiency, improved press cycle monitoring, and actionable insights from sensor data

Overview
Barry Callebaut, the world’s leading chocolate manufacturer, has long been at the forefront of innovation. With a global push toward smarter manufacturing, the company partnered with Ishango to enhance efficiency at one of its production facilities.

The Challenge
The goal was clear: improve production performance by analysing sensor data from the factory floor. Barry Callebaut needed help identifying bottlenecks and detecting anomalies in the press cycles—one of the key stages in chocolate production.

The Ishango Approach
Our team developed a machine learning solution using Python on the Databricks platform. We worked closely with stakeholders to explore the factory’s sensor data, uncover inefficiencies, and flag unusual press cycle behaviors in real-time.

The Result
The solution quickly delivered value. Multiple anomalies in press cycles were identified and addressed, resulting in smoother operations and reduced downtime. Factory operators gained visibility into issues they hadn’t previously detected.