Building Data Analytics Workflows | An Equipment Health Monitoring Use Case
Join us for an insightful webinar where we explore the integration of classical chemometrics tools from the Umetrics® Suite with Scikit-learn elements to create powerful, cloud-deployable workflows using the Umetrics® Studio Scibox environment. This session is designed for data scientists eager to expand their data analytical capabilities through the development of custom applications. We will guide you through the process of constructing effective workflows, leveraging the robust functionalities of Umetrics® Studio and Scikit-learn to enhance your data analytics projects.
Webinar Highlights:
- Workflow Construction: Learn how to build sophisticated applications using building blocks, simplifying the development and deployment of complex analytical solutions.
- Tooling and Methodology: Explore the tools designed to streamline I/O processes and lower the barrier for data scientists to create applications using SIMCA-based methodologies, empowered by utilizing the same Python package used when scripting in SIMCA®.
- Reproducibility and Automation: Discover how to design applications with a focus on reproducibility and automation, enhancing deviation detection and updating classifications to include previously unclassified deviations.
- Common Framework: Understand how a unified framework for SIMCA® and Studio facilitates seamless project creation and interoperability between these tools.
The webinar will feature a compelling use case from Amgen, showcasing the monitoring of equipment health using real-world data. Despite the surge in data availability and analytics, biomanufacturing plants often face challenges in improving business outcomes, such as reducing the cycle time from anomaly detection to remediation. We will demonstrate how Umetrics® Studio can significantly cut this cycle time through advanced failure mode classification and prescriptive analytics, offering a glimpse into the software's potential to address a wide range of use cases.
What You Will Learn:
- Master the art of building modular and reusable workflows for enhanced analytical efficiency
- Gain insights into integrating classical chemometrics with machine learning for robust data analysis
- Learn strategies for improving reproducibility and automation in data-driven applications
- Explore the benefits of a common framework for seamless tool interoperability