How UPM Wisaforest uses condition monitoring for improved asset management.
This article explores the use of condition monitoring at the UPM-Kymmene's Wisaforest pulp and paper mill in Finland. Production capacity is 800,000 air dried tons per annum (ADt/a) of pulp and 180,000 ADt/a of kraft and sack papers.
The WISA 800 REC (RECovery) project entailed a single line to replace the mill's two previous recovery lines. A new sawdust cooking line was added, providing more flexibility in the raw material base by allowing the use of sawdust as feedstock for selected pulp qualities. This delivered both environmental advantages (fewer emissions) and process advantages by allowing the mill to draw from a larger pool of locally available sources for pulp feedstock.
The project scope was extensive. The main equipment suppliers for the recovery island were Andritz Corporation (process equipment), Siemens AG (main turbo-generator) and Metso Automation (process control system). GE Energy was chosen to supply a condition monitoring solution.
The Condition Monitoring System
Employees working with the WISA 800 REC project defined the scope of the CM system based on machinery criticality (see Table 1 ).
Large, high-speed turbomachinery generally warrants a conventional rack-based continuous monitoring system, and the plant chose proximity probes coupled with a machinery protection system. With exception of the lime kiln, all other machinery used rolling element bearings and was more appropriately addressed by a monitoring system using a scanning architecture. Both hardware solutions were linked to monitoring software to allow a common, connected platform.
Project Execution
One of the first items that needed to be defined was the total number of measurement points, which would be used to determine the number of dynamic scanning modules (DSMs) required. Ten DSMs were needed, reflecting the appropriate balance of wiring costs, hardware costs and scanning times. The locations for these DSMs were identified based on wiring topology, availability of power and network connections, and other factors.
The machines in the facility vary drastically from one another, including operating speed (1 to 3,000 rpm), drive mechanism (direct, belt and gear), and operating mode (constant speed, variable speed, constant load and variable load). Suppliers and plant personnel needed to cooperate to determine and document the correct values for all settings, and then enter these values into the software's configuration screens.
Taking the New Recovery Unit into Operation
One of the most crucial times for the CM system is when machines are tested and brought online for the first time. Problems that may not have been apparent at the factory may surface, or the installation of the machine may have introduced problems. Consequently, an important aspect of the project was to ensure that the CM system was configured and ready as each machine was started.
Through careful advance planning and schedule coordination, the CM system was ready to begin monitoring. As other machines were subsequently brought online, the system's configuration and commissioning were coordinated to coincide with their start-up dates.
When the new recovery unit officially began full-time operation, all measurement points had been collecting data for several weeks. The team turned its attention to fine tuning alarm levels and other system configuration settings. During these adjustments, no machine failures could be allowed and faulty operating conditions needed to remain visible. The company and supplier worked collaboratively to successfully accomplish these objectives in a timely fashion.
During the start-up phase, the CM system identified a number of machinery problems, which allowed proactive intervention and remedy before the entire plant went live. This early payback of the system and its usefulness during start-up activities had been a high priority for the Wisaforest project team and was part of the justification for installing the system. After full-time operation commenced, the system continued to deliver value by logging many other machinery saves.
Case Histories
Case History #1
Problem: Bearing Lubrication
Machine: Secondary Air Fan
Unit: Recovery Boiler
The secondary air fan is a 600 kW direct-driven overhung fan that is critical for the recovery boiler operation. Shortly after start-up, abnormal changes in trends of the high frequency data from the inboard bearing accelerometer were noted. Figure 1 is taken directly from the CM software, showing a two month trend of high frequency data from the accelerometers on the inboard and outboard bearings.
The elevated levels on the inboard bearing (blue) compared to the outboard bearing (orange) are readily apparent.
Spectral analysis suggested that the bearing's outer ring was wearing prematurely, and the root cause was ultimately traced to problems with the bearing lubrication system. The prominent dips in the trend plot correspond to intermittent operation of the lubrication system, showing a marked decrease in vibration for the inboard bearing when lubrication was flowing properly.
Even though the root cause was identified, implementing the changes to the lubrication system was a lengthy process, and the machine was required to operate in the interim. Although the bearing had to be replaced twice during the first six months, the CM system proved useful in scheduling these replacements, allowing the plant to monitor bearing degradation closely and intervene at the right times before catastrophic bearing failure and collateral machine damage occurred. Outages could be planned, allowing the bearing change-outs to be performed when impact to production was minimized.
Case History #2
Problem: Resonance
Machine: Lime Kiln Driver
Unit: Lime Kiln
The lime kiln is a large machine with slow rotational speeds (as low as 5 rpm). Two drivers provide rotational power. Depending on production conditions, the kiln must run at different operating speeds. When the kiln ran at higher speeds, higher vibration levels were noted, occurring predominately at 2X. This led plant personnel to initially conclude it was an alignment problem, but realignment of the drivers did not correct the situation. The data was re-examined, this time by looking at phase and rpm levels in addition to amplitude and frequency ( Figure 2 and Table 1 ).
Table
