Deeper manufacturing analysis to optimize process planning and maintenance to streamline the production process
Client’s existing data platform (SAP HANA) cannot ingest new types of data i.e. unstructured data – social media, IoT, streaming data, etc., making it difficult to scale.
Require experienced engineers to control the Kiln Rotary machine, and rely solely on human knowledge and know-how.
Develop a centralised Data Lake platform to reduce time consuming manual data gathering working tasks and increase data analytics capabilities
Develop a machine learning model that can predict 1 hour before breakdown resulting in huge cost savings
Centralized, streamlined, and ingest real-time sensor data from manufacturing plants allows other operating entities to perform data science and other analytics use cases in the future
On-site engineers know early before the machine breakdown, so they can plan the maintenance process beforehand and support cost savings in the future
Optimize manufacturing costs by tracking all processes and identifying bottlenecks
Predict manufacturing process breakdowns early so engineers can plan maintenance beforehand
Improve production planning efficiency and flexibility by using automated optimization algorithms
Collect and personalize data in one platform to monitor business performance and support management decisions