Assembly Line

HAYAT HOLDING uses Amazon SageMaker to increase product quality and optimize manufacturing output, saving $300,000 annually

đź“… Date:

✍️ Author: Neslihan Erdogan

đź”– Topics: Machine Learning, Cloud Computing, Edge Computing

🏢 Organizations: HAYAT HOLDING, AWS, Deloitte

In this post, we share how HAYAT HOLDING—a global player with 41 companies operating in different industries, including HAYAT, the world’s fourth-largest branded diaper manufacturer, and KEAS, the world’s fifth-largest wood-based panel manufacturer—collaborated with AWS to build a solution that uses Amazon SageMaker Model Training, Amazon SageMaker Automatic Model Tuning, and Amazon SageMaker Model Deployment to continuously improve operational performance, increase product quality, and optimize manufacturing output of medium-density fiberboard (MDF) wood panels.

Quality prediction using ML is powerful but requires effort and skill to design, integrate with the manufacturing process, and maintain. With the support of AWS Prototyping specialists, and AWS Partner Deloitte, HAYAT HOLDING built an end-to-end pipeline. Product quality prediction and adhesive consumption recommendation results can be observed by field experts through dashboards in near-real time, resulting in a faster feedback loop. Laboratory results indicate a significant impact equating to savings of $300,000 annually, reducing their carbon footprint in production by preventing unnecessary chemical waste.

Read more at AWS Blog