Manufacturers collect extremely large volumes of data from production lines, sensors, individual equipment performance, and other quality control information. Proper use of this complex information can lead to improved operations management, a streamlined supply chain, and real-time adjustments to quality control, which ultimately improves the bottom line.
The abundance of available data creates a massive opportunity to drive supply chain efficiencies for manufacturers who have broad operations across multiple sites and globally. The Ayasdi Platform provides a new approach to manufacturers to detect anomalies in the supply chain, such as inventory build-ups, site-specific failures, or assembly line inefficiencies.
Improving process yield and decreasing product defects lead to increased profit and happy customers. This includes quickly finding root causes to failures and immediately implementing corrective action. By mining data from the manufacturing process to determine a subset of the most influential predictors, manufacturers can optimize processes to yield higher revenues.
Today’s modern supply chain activities creates petabytes of data which can be used for building a competitive infrastructure, leveraging worldwide logistics, synchronizing supply with demand, and measuring performance globally. Utilizing data across all systems, all factories and even third party partners can help manufacturers drive an efficient supply chain operation.