Krissy Key, Transformation Data Engineer, Indorama Ventures

Laura Maesaka, ACC, CPC, ELI-MP, Energy Optimization Manager, TPC Group

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.

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. ​

Sherri Goodwin, Data Science Engineer, Indorama Ventures

Outlining Indorama’s structured approach to maximizing data science impact with limited resources. Through a phased deployment of data scientists (Alpha and Beta Release Candidates) and initiatives like the SeeqAThon, we drive rapid value delivery, collaboration, and solution adoption. We highlight key strategies, including asset scaling, linear programming, Generative AI integration, and enhanced Seeq functionalities with Lean Six Sigma add-on tools. A case study will showcase how these methods translate into real-world efficiency and innovation.

Dr. Nethika Suraweera PhD, Senior AI/Data Scientist, Nutrien

Adeyinka Opadeyi, Ammonia Process SME, Nutrien

Nutrien’s Real Time Operation Center (NROC) oversees operational efficiency of 10 Nitrogen Production Sites. NROC has utilized rapid data navigation and modeling during both the data exploration and analysis phases, enabling timely detection of failures and proactive interventions. We will review a few use cases illustrating the transformative impact of data monitoring and analytics in Nitrogen production, demonstrating how we leverage Seeq to ensure operational excellence.

Prabhu Ramachandran, Sr. Manager Digital Transformation, Kaneka

Chiru Botre, Process Data Scientist Digital Transformation, Kaneka

Kaneka will highlight how data analytics tools were used to analyze batch cycle times, reactor phases and grades. They used the tools to provide enhanced data visualization enabling real time actions and uncovering key insights to streamline real-time reporting. This resulted in an overall reduction of reactor batch cycle times.

Jack Puryear, Digital Manufacturing Engineer, Eastman Chemical Company

Peyton Piesco, Digital Manufacturing Engineer, Eastman Chemical Company

Eastman Chemical Company is bringing Machine Learning online in manufacturing through joint Data Science, Manufacturing, and Advanced Controls efforts. This session covers the team’s journey to validate and monitor the ML models on live chemical processes using Seeq.

Kyle Denzler, Manufacturing Intelligence Leader, Owens Corning

Faced with limited resources, Owens Corning established a remote monitoring team and empowered the group with technical leadership and  integrated digital tools, including Seeq.  This presentation investigates the effectiveness of this team in saving engineers’ time, enabling insights from data and simplifying the task of data retrieval.