CHALLENGE

Quality level prediction to improve efficiency while contributing to sustainability

SOLUTION

An intelligent, quality level prediction algorithm with real-time dashboards

BENEFITS

Enhanced operational efficiency
Heightened productivity
Empowered operators
Savings in infrastructure costs
Reduction in negative environmental impact

Data-driven results

Identifying quality issues before the completion of the production process was particularly important to this manufacturer. We addressed this issue by applying the potential of AI, deploying a machine-learning model capable of predicting the quality of ball bearings up to an hour before the end of the production cycle. The model allows operators to make real-time adjustments, significantly reducing the rate of defective products and minimizing the amount of scrap generated during production. The benefits are felt both in cost savings and improved sustainability.

Actionable insights

The effectiveness of the AI system was further enhanced with the introduction of real-time dashboards to give operators continuous, up-to-the-minute insights into production parameters, machine health, and product quality. The dashboards offer clear, actionable data, enabling quick decision-making in response to any deviations in the production process, before they escalate into more significant problems. This empowers operators to maintain a streamlined, efficient workflow, improving productivity and quality control.

The results of the AI-driven solution were immediately apparent, including a 2% reduction in product scrap. Additionally, the transition to AI-powered predictive maintenance optimized the life of the machinery and lowered energy consumption, contributing to measurable sustainability benefits.

Futureproofing

Using cloud-based Microsoft Azure services, we ensured a scalable solution that allows the client to future-proof their operations and reduce the need for heavy on-site infrastructure investments. Clear cause-and-effect analysis makes it possible to pinpoint the root causes of quality deviations, enabling continuous refinement of processes and enhancing productivity. Azure Machine Learning, Data Factory, and other cloud services provide a seamless, low-cost platform for ongoing machine learning operations (MLOps), making the solution accessible and easy to maintain.