Overview
What is Tridiagonal Solutions Pilot Guided Analytics?
Tridiagonal Solutions expands its process consulting services in to Data Science and Data Analytics Solutions. With its large customer-base in Process Industry (Oil & Gas, Specialty Chemicals, Steel, Cement, Pharmaceuticals, Food & Beverages, etc.) worldwide, we are uniquely positioned to…
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What is Tridiagonal Solutions Pilot Guided Analytics?
Tridiagonal Solutions expands its process consulting services in to Data Science and Data Analytics Solutions. With its large customer-base in Process Industry (Oil & Gas, Specialty Chemicals, Steel, Cement, Pharmaceuticals, Food & Beverages, etc.) worldwide, we are uniquely positioned to provide the process data modeling (ML-AI), advanced analytics and deployment solutions . With a Process R&D background, and combination of skill sets (100+ persons - Domain Engg. / SME, Data Scientists, Data Engineers, Application engineers) , they support corporate R&D groups, Process Technologist, Plant and Operations teams with services and solutions.
They leverage advanced modeling, workflow automation and process data analytics techniques to address the customer’s needs. They have delivered 1000+ consulting projects into process understanding, validation, troubleshooting and manufacturing data analytics. Their advanced modeling group has an expertise in building performance-based process models (first principle/ computational and experimental techniques) and data-driven models (using ML/ AI algorithms). They extend the process understanding / data-driven models to manufacturing plant data and perform data analytics (root cause analysis, production effectiveness, Quality variance, predictive maintenance, etc.).
They leverage advanced modeling, workflow automation and process data analytics techniques to address the customer’s needs. They have delivered 1000+ consulting projects into process understanding, validation, troubleshooting and manufacturing data analytics. Their advanced modeling group has an expertise in building performance-based process models (first principle/ computational and experimental techniques) and data-driven models (using ML/ AI algorithms). They extend the process understanding / data-driven models to manufacturing plant data and perform data analytics (root cause analysis, production effectiveness, Quality variance, predictive maintenance, etc.).