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Machine Learning for Process Industries Machine Learning for Process Industries
The Challenge

The Challenge

Industrial processes have become increasingly advanced as innovation continues to shape the modern world. Complex modern processes utilize thousands of industrial sensors, sophisticated process control systems, and a myriad of other industrial data systems in the safe and efficient operation of these facilities.

Much of this operational data remains isolated within systems or departments, limiting its potential value. Machine learning can help organizations analyze large volumes of information to support predictive maintenance initiatives, improve process optimization efforts, and identify opportunities for operational improvement. These capabilities can help support operational excellence across the organization.
The Solution

The Solution

Technologies such as cloud computing, industrial data platforms, artificial intelligence, and machine learning are helping manufacturers gain greater value from operational data. Puffer-Sweiven helps organizations evaluate and apply these technologies to improve equipment reliability, process performance, and operational efficiency.

We develop and provide advanced data driven solutions for industrial soft sensors and predictive modelling, predictive maintenance applications, optimal and self-learning adaptive control, and energy and emissions management.