Maximizing Efficiency and Transparency with INOSIM Foresight

Abstract

• Complex behavior of modern batch plants
• Intuitive predictive graphical dashboards support plant personnel
• INOSIM Foresight being deployed at CSL Behring, Germany

The complexity of modern industrial batch plants makes it nearly impossible for plant personnel and production managers to predict their future behavior accurately over longer periods of time. This contribution presents the INOSIM Foresight system for predictive decision support that employs highly accurate dynamic material flow simulation to create a transparency and situational awareness that allows the plant operators and management to operate and plan more efficiently, productively, and safely, which can lead to savings in the millions. Intuitive predictive graphical dashboards support plant personnel in a variety of ways. For example, they provide concise guidance to improve production (e.g., by counteracting negative events before they occur and by predicting key KPIs days or even weeks ahead), and they enable the staff to create production, personnel, and in-process maintenance plans that are efficient and non-conservative. The system is currently being deployed at a new, innovative pharma batch plant of CSL Behring GmbH in Marburg, Germany.

Challenges

• Many parallel activities
• Complex interdependencies
• External and internal constraints

Use Cases

• Predictive Operator Task Board
• Predictive In-Process Maintenance
• Predictive Process Supervision

Conclusions and Outlook