Before Seeq, data visualization at Covestro was static and cumbersome. Now, Seeq allows for live data and visualizations during meetings, facilitating more informed and timely decisions.
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At Syensqo, Seeq enabled the team to consolidate industrial data from various sources, making it easier and faster to find insights and perform calculations. Tasks that once took 10-15 minutes are now automated. The Seeq AI Assistant has made the software more accessible to more users across the organization, enabling more efficient analyses.
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INVISTA leverages Seeq to monitor processes and equipment, detect anomalies, and share insights across the organization, enabling timely responses and preventing potential failures. Additionally, the Seeq AI Assistant has been instrumental in quickly onboarding new team members and enabling the team to reduce analysis time significantly. By making data analytics accessible to everyone, Seeq supports INVISTA’s vision for data-driven transformation and decision-making.
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Laura Maesaka, ACC, CPC, ELI-MP, Energy Optimization Manager, TPC Group
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TPC Group – From Friction to Flow: A Practical Approach to Driving Adoption
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Marathon Petroleum – Marathon’s Seeq Champions Maximizing Value to the Business
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Indorama Ventures Empowering Transformation: (The SAR Region)
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Devon Energy – Scaling Smarter: How Devon Leveraged a Strategic Success Plan to Drive Operational Efficiency
Rohan Tuli, Industrial Digital Transformation Engineer, Solvay
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Solvay – PID Health Monitoring
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Kaneka North America – Monitoring Fermentation Plant Batch Cycle Real-Time
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Indorama Ventures Scaling Lean Six Sigma Tools Enterprise
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Dominion Energy – Planning for a New Tomorrow – Forecast-Driven Outage Planning
Cara Blankenbicker, Industrial Data Scientist, Syensqo
In the complex world of manufacturing, a process cannot be run optimally if people do not have access to relevant information when they need it. Information has historically been shared using a tapestry of solutions to generate dashboards for operators, monthly spreadsheets for stakeholders and ad-hoc analyses for engineers to troubleshoot processes. Today this can be streamlined into a coherent SEEQ dashboard solution, the product of an ongoing collaboration between site and corporate resources.
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Syensqo – Enhancing Teamwork: Leveraging Dashboards for More Effective Collaboration
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Solvay – Condition Based Batch Filter Washes and Renewals
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Rio Tinto – Enhancing Aluminum Cable Coiling Quality with Tangle Probability Indicators
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3M – Visualization of an OEE Seeq Analysis using Power BI
Emily Cole, Sr. Scientist, Verdagy
Verdagy developed a scalable monitoring tool for lab- and pilot-scale electrolyzers that automatically identifies and aggregates polarization curve parameters and summarizes other KPIs such as hydrogen production rate and total uptime metrics. Verdagy successfully implemented the tool across their technical teams to enable rapid results-sharing while maintaining uniform data analysis methodologies. The targeted scope of Verdagy’s tool enables widespread adoption and requires no learning curve to use.
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Verdagy – Building a No User Learning Curve Internal Data Analysis Platform
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Nutrien – Enhancing Ammonia Plant Reliability with Seeq
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Kaneka – Enhancing Polymer Reactor Productivity Using Seeq Analytics
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Indorama Ventures – Optimizing Data Science Deployment for Velocity
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Eastman Chemical Company – Machine Learning Analytics: Green is Good
Rohan Tuli, Industrial Digital Transformation Engineer, Solvay
Ziyan Sheriff, Senior Process Data Scientist, Kaneka North America
