Predict variances and optimize plant performance
Harness the expertise of your most skilled operators
IBM Production Optimization learns from the actions of expert operators by correlating the actions with outcomes for any situation. The knowledge gathered is then used to calculate the right set points for various operating conditions and guide everyday operators on the right actions that will maximize throughput, optimize quality and minimize energy.
Unlock insights hidden in your plant floor data
Production Optimization uses advanced machine learning techniques to bring insights out of plant floor data collected. Process engineers can compare process efficiencies across several plants and baseline performance to derive process improvement steps.
Monitors a variety of KPIs and process variables
The solution is configurable so you can choose specific KPIs for optimization. In the case of cement, the fineness is an important criteria and has to be optimized at a narrow tolerance even if it takes more energy. Or vice versa, the energy consumption has to be minimized even if fineness has higher variance.
Supports on-premises vs as-a-service deployment flexibility
Production Optimization offers a number of deployment scenarios depending on requirements. Clients seeking to accelerate time to value and avoid upfront infrastructure costs can deploy the solution as a service. The solution can also be deployed on-premises for clients with unique security requirements, disconnected operations, or specific performance needs from near-edge processing.
Fast deployment with pre-built analytic models and templates
Production Optimization has pre-built advanced analytical pipeline for early anomaly detection, anomaly scoring, regression/prediction, auto classification and optimization optimized for various use case and processes in discrete manufacturing plants. This reduces upfront data scientist’s effort and accelerates time to value.
Two way integration with EAM system is possible including strong integration with Maximo EAM. Plant Maintenance Supervisors are able to send EAM tickets after evaluating predictive maintenance alerts. They are able to monitor the status of the maintenance ticket throughout the maintenance workflow. The dashboard also gives consolidated metrics on the maintenance ticket status of all the work orders sent.
How customers use it
There are no specific hardware requirements for IBM Production Optimization
There are no specific software requirements for IBM Production Optimization