Real-Time Process Intelligence to Raise Your Manufacturing IQ
When your manufacturing process drifts from optimal operating conditions, you need to know about it—before product quality or yield is negatively affected. SIMCA®-online tracks your production processes in real-time for a continuous snapshot of operations. Our proprietary digital twin machine learning technology gives you early warnings of process anomalies that will affect the end product. With this real-time process intelligence, your production team can proactively drive the best possible outcomes. And that means you can ensure consistent product quality, maximize productivity, and prevent costly re-work or scrapping.
Are you confident your process is on track to meet quality targets? Do you wish you could cut down on complexity and decipher process control data more quickly and easily? What if you could visualize and interpret the behavior of all your processes at a glance, with just a few clicks? Find out how SIMCA®-online, part of Umetrics Digital Twin AI Ecosystem, uses digital twins from SIMCA® machine learning multivariate data analysis (MVDA) modeling to eliminate the complexity of traditional process monitoring so you get clear actionable insights—exactly when you need them, no matter where you are.
SIMCA®-online is the First Choice for Real-Time Batch Process Monitoring
- Real-time analysis of vital parameters and their correlation patterns
- Increased process visibility from end-to-end with dedicated charting
- Early fault detection and warning of process deviations
- Interactive visuals for instant insights and guidance on corrective and preventive actions
- Highly accurate end point prediction and forecasting with Control Advisor
- Quick overview of batch-to-batch comparison
- Process intelligence to maximize productivity and improve product quality
SIMCA®-online provides real-time analysis of vital parameters and their correlation patterns. Processes can be monitored remotely, in real-time, from connected servers by using windows or web clients.
Alarms can be set to enable early detection of possible process upsets. Alerts with email notifications makes sure the information quickly reaches all stakeholders.
Multivariate charts summarize your process. For deviating observations use drill-down functionality to visualize how much each variable deviates from normal to guide users to identify the root cause for analysis.
Accurate prediction, forecasting, and validation of the final quality attributes allow for quality control to take place ahead of production completion.
SIMCA®-online use a digital twin model from SIMCA® to anticipate the effect of changes and recommend immediate adjustments to change your process parameters for optimal results.
Benefit From the Unique Power of Digital Twin SIMCA®-online
Save Resources and Time in Production
SIMCA®-online takes advantage of the latest advanced data analytics to track and detect when your process deviates from an ideal state and provides insight into the underlying causes. This means less time and resources spent on root cause analysis and batches that would otherwise be scrapped or require costly re-work.
Proactively Improve Product Quality
With accurate prediction and forecasting of the final quality attributes, quality control can be completed before production is finished. In addition, SIMCA®-online Control Advisor provides AI insights and guidance on how to adjust the process to reach a better end state, so operators can take proactive steps to improve product quality.
Minimize Risk and Ensure Compliance
SIMCA®-online makes it easy to implement best practices for continued and continuous process verification. This helps you safeguard vital processes and ensures compliance with quality standards, regulations and industry guidance for good manufacturing practice and adherence to 21 CFR part 11.
Latest Added Functionality
Integration into the Umetrics® Digital Twin AI Ecosystem allows to explore the variables included in the project directly from your data source. This visualization and ad-hoc contextualization of existing or additional variables allows for quick inspection to increase understanding and preparation for model updates.
Adaptive Process Mode allows dynamic switching between modeling for different processing modes, extending the multi-unit abilities to support to track all continuous, intensified, or hybrid culture processes. The ability to combine dynamic evolution with steady-state data at the batch level also enables an enhanced aggregated analysis of both modes.
Excluded batches from the SIMCA® project, which sometimes are used as verification batches, can now be included in SIMCA®-online as reference batches so they can be compared with current production.
Alerting enhancements include the possibility of distinguishing regions of interest from less critical parts of the process, ensuring that all triggered alarms receive full attention from all stakeholders.
Dynamic alarms for univariate data can be configured in SIMCA®, and support scenarios for highly specific settings also for generated and Python variables, further adding to the flexibility and versatility of the real-time solution.
Elevate To Catalyze Batch Process Modelling Expertise
Discover the secrets of overviewing batch data tables and learn how to build robust predictive models that turn data into decisions. Using our proprietary machine learning methods, participants will learn how to interpret complex data quickly and confidently.
The course is composed of lectures, demonstrations, and computer exercises in SIMCA® software, based on real-life datasets.
Also available: self-paced, on-demand eLearning courses for beginners on MVDA
Downloads
Data Analytics eLearning: Level 1 Basic Training on Design of Experiment (DOE) and Multivariate Data Analysis (MVDA)
PDF | 202.0 KB
Data Analytics eLearning: Level 2 Intermediate Training on Design of Experiment (DOE) and Multivariate Data Analysis (MVDA)
PDF | 203.3 KB
PAT IN-DEPTH FOCUS - Process Analytics Experiences in Biopharmaceutical Manufacturing
PDF | 879.3 KB
PAT IN-DEPTH FOCUS - Correlation Between Powder Rheology Data and Processability in Solid Dosage Form Manufacturing
PDF | 487.9 KB
