Smart Use of Data Improves Diagnostics, Optimizes Performance
Summary
Chronic operating issues and costly technical support was plaguing a southern paper mill. There had to be a better way. By analyzing data and using modeling to generate insights into performance-based maintenance and operational strategies, Neundorfer engineers were able to identify effective resolutions without leaving the office.
"Neundorfer was able to monitor performance and equipment operations, analyze the data to find correlations, and create focused actions for troubleshooting and optimization."
Integrated Paper Mill
Full Story
A large integrated paper mill with electrostatic precipitators (ESP) installed on the mill’s recovery and power boilers was experiencing chronic operating issues. While the mill marginally met all of its environmental objectives, the costs for doing so were becoming excessive. At that time, most technical support was provided via on-site troubleshooting visits to the mill which had high travel costs and limited time to analyze the plethora of operating data, or via phone which provides its own unique difficulties. The mill was looking for a better way to improve performance and reliability of these units, to eliminate reoccurring issues, and to reduce maintenance costs in the process. Neundorfer provided the mill an integrated solution that allowed consultants to remotely analyze operating data, troubleshoot, and support on-site efforts. This approach allowed Neundorfer to gather large amounts of data and use the data to provide insights into performance-based maintenance and operational strategies.
As with any integrated process, there are many primary and ancillary systems that must work together to help the mill with its day-to-day operations, and all of these systems are gathering large amounts of operating data. Although it is all brought back to a central system, there was no easy way to analyze it, identify potential sources of upsets or issues, and create strategies to resolve issues.
Neundorfer implemented an approach that allowed us to centralize and remotely connect to the available data, monitor performance and equipment operations in real time, analyze the data to find the known and unknown correlations, and create focused actions around troubleshooting and optimization. These actions were communicated back to the plant by Neundorfer engineers. The data consists of boiler data, precipitator operating data and key emissions data from the environmental monitoring equipment. This information was put through proprietary modeling and processes and then reviewed by Neundorfer engineers. It also allowed for real-time troubleshooting with Neundorfer engineers talking with the mill while looking at live data.
The result was quick and informed responses to the mill’s request for assistance, while eliminating travel time and costs. Analysis of the data and an understanding of maintenance activities resulted in the elimination of unnecessary and costly equipment repairs. The approach also lead to increased knowledge and capabilities of the operations personnel, enabling them to create and direct maintenance tasks more effectively. For example, during an issue with suboptimal performance, the analysis of the data allowed Neundorfer to direct on site personnel to inspect specific parts of the precipitator during an unscheduled shutdown to address the issues. Through all of this, tuning of the equipment allowed for performance optimization that further reduced emissions.
This is an example of how “big data” can be used to benefit every day operation, lead to increased knowledge and capabilities at the plant, and support performance-based maintenance and operation practice that improve performance and save money.