Case Study
Mativ
Learn how Mativ used dataPARC’s predictive modeling to open a new product line, eliminate data silos, and implement systematic loss-time tracking.
Mativ’s Challenges
Mativ depended on Excel for data analysis, creating silos that prevented real-time insights. Reporting lagged by days, and there was no systematic way to track and analyze loss-time reasons across operations.
The dataPARC Solution
dataPARC eliminated Mativ’s dependency on Excel and integrated all data sources, enabling real-time analysis and swift trend identification. This reduced reporting lag from days to hours and provided a comprehensive plant-wide view. Predictive PLS modeling and soft sensors for color control opened a new product line. The alarm system empowers operators to assign reasons and comments systematically, with Pareto chart visualization for loss analysis.
Mativ’s Challenges
Mativ depended on Excel for data analysis, creating silos that prevented real-time insights. Reporting lagged by days, and there was no systematic way to track and analyze loss-time reasons across operations.
The dataPARC Solution
dataPARC eliminated Mativ’s dependency on Excel and integrated all data sources, enabling real-time analysis and swift trend identification. This reduced reporting lag from days to hours and provided a comprehensive plant-wide view. Predictive PLS modeling and soft sensors for color control opened a new product line. The alarm system empowers operators to assign reasons and comments systematically, with Pareto chart visualization for loss analysis.
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