Large-scale pumping systems are all about the numbers. In applications where individual pumps require power inputs that are measured in megawatts, even the smallest improvement in efficiency and productivity can yield major benefits. One of the latest developments uses advanced data analytics to provide a real-time view of operations and highlight opportunities to improve the performance and efficiency of multiple assets at system level.
There are several challenges operators of pumping systems might face. The cost of asset availability, increasing energy bills and restrictions in performance are three that usually appear at the top of the list. The key to addressing these, and a few others, is better interpretation of system data—using it to reduce costs, to make better decisions more quickly and to improve overall profitability.
Large-scale pumping installations are usually equipped with sensors and data gathering devices to monitor performance. From vibration and flow rate measurement to system pressure and energy consumption, information is often collected and analyzed as part of the daily routine.
The interpretation of data and putting it to work to benefit the operation is the greatest challenge. In many cases, there is a considerable opportunity to improve both the analytical process and the speed at which changes are implemented to optimize performance. Using modern communications and procedures enabled by the Internet of Things (IoT), it is possible to use near real-time data to drive actions in the field that will improve productivity.
Ideal Operating Conditions
Accurate interpretation of pump system data enables operators to fine-tune performance and identify under-performing assets. Ideally, all pumps would be designed and manufactured to precisely match their applications, which would enable them to operate continuously at the best efficiency point (BEP) on the pump performance curve.
However, in practice, it is necessary to closely monitor pump performance and establish underlying trends. These, along with associated flow rates, can be used to highlight periods when pumps are over-exerted and prone to excessive wear. Combined with historical data and new data analysis, it is possible to evaluate individual asset performance and optimize efficiency and reliability.
Security of Data
Each pumping station should be connected to a supervisory control and data acquisition (SCADA) system, but this is not always the case. Some installations rely on local programmable logic controllers (PLCs) or process historians, but the important point is that the pumping process data is captured.
One data gathering solution uses a secure access point to analyze the ongoing stream of data and deliver a tailored analysis and visualization of the information in a dashboard layout. At the same time, the software highlights potential issues with system assets to enable focused maintenance action.
The whole predictive analytics package is designed to be flexible so that it can be easily integrated with existing information technology (IT) platforms and deliver valuable insights into the performance of the pumping installation.
Each pumping location should be able to supply operational data for pressure, flow, power, density and viscosity. Each location should also have available information for the maintenance department, which would include vibration and temperature readings. The format and accessibility of this data will largely dictate the speed at which it can be processed and interpreted, which will, in turn, affect the speed of response to any performance concerns. However, the actual analysis of the data and the quality of the proposed actions are dependent on the expertise used to create the machine learning algorithms within the software.
One data solution offers a secure connection to multiple data sources and provides a visualization of all aspects of pumping performance. Combining performance data with information from vibration and temperature sensors on each asset helps to create an accurate picture of expected reliability and performance. This empowers operators to identify potential issues and implement preventative actions and planned maintenance schedules that minimize downtime and enhance productivity.
Once any underperforming assets have been identified, it is important to schedule the remedial work at the earliest opportunity to enable the pumping system to return to full capacity. This requires expertise and experience as well as considerable service facilities and logistics capabilities to ensure the fastest response as well as a high-quality refurbishment. Aging assets still hold enormous value and should be considered for life extension projects wherever possible.
Legacy assets may not have original designs available, or the original equipment manufacturer (OEM) may no longer offer support. In such cases, an expert maintenance provider can offer a valuable service. Long-term experienced companies can provide retrofit services that replace worn components and fine-tune designs to ensure optimum performance and efficiency for a specific application.
Capturing the Benefits
For businesses that operate on such an expansive scale, using near real-time data analysis to identify bad actors and losses in efficiency is a major step forward. By reducing reaction and planning time, it is possible to minimize downtime and promote productivity.
In situations where more substantial upgrades or repairs are required, the assets can be closely monitored to pinpoint the optimum time for the maintenance work to be completed. This also enables the budgets and resources to be in place before the work is due to start, minimizing lead times and ensuring an efficient repair process.
Ultimately, the implementation of a flexible and structured data analysis system offers a host of benefits to the operator, not least to improve efficiency and reduce operating costs. The ability to quickly identify underperforming assets and schedule refurbishments that can restore, or even improve performance, is vital to minimizing downtime.