(314e) Analytics Framework and Infrastructure - Integrating Big-Data Cloud Technologies with First-Principle Modeling
This paper presents the analytics framework and infrastructure built to integrate big-data cloud technologies with traditional process system engineering tools such as first-principle modeling, deterministic optimization techniques for scheduling, and process control. The engines include
- Proprietary model identification system which identifies the basic first-principles behaviors such as mass and energy balances, along with time-depended performance metrics such as fouling and physical performance degradation
- Scheduling platform developed for production scheduling of continuous processes with special emphasis on utility systems along with interactive interfaces for visual construction of optimization problems
We also present the deployment strategies for such engines which range from in-chassis deployment tightly coupled with the controller to deployment as cloud services for extreme scalability. The use of cloud facilities such as high throughput, multi-source data ingestion, stream processing of data, and elastic web applications is demonstrated through case-studies.