Modern pumping applications are driven predominantly by operating costs and among these, the budgets for energy and maintenance head the field. Coupled with the energy requirements are the associated carbon footprint, which in some situations will add further expense due to local taxation policies. Reducing these costs is now becoming easier with the use of advanced data analytics, predictive maintenance solutions, and retrofit parts that improve the efficiency and reliability of legacy equipment.
By Dr. Marc Heggemann, Head of Digital Solutions, Sulzer & Manish Talwar, Head of Retrofits Americas, Sulzer.
Pumps of all sizes are used throughout industry to transport fluids and create the necessary pressure for processes such as reverse osmosis or steam generation. In total, pumping systems account for around 20% of the world’s electrical energy demand, which gives pump manufacturers an opportunity to help reduce the global energy demand. However, determining any wear rates or loss of efficiency requires data analysis and comparisons with performance curves from the original equipment manufacturer (OEM).
Identifying Potential Issues
It is easy to overlook an issue that is not clear or highlighted by existing instrumentation and systems. In many cases, operators only react when bearings or seals begin to fail, but at this point, the pump may have already been operating well below par for some time. Carrying out equipment health checks is
the first step in taking control of running costs; implementing pre-emptive actions to restore as-new performance is the best way to avoid unplanned downtime that will only increase costs further.
This has already been demonstrated in numerous real-world applications, for example, a solar plant in the U.S., could be equipped with six boiler feed pumps that are powered by a combination of variable speed and direct drive, high-voltage motors. In this case, feedwater recirculation is regulated by automatic recirculation (ARC) valves.
Additionally, as using existing sensor data from the pumps, makes it possible to use a round-the-clock monitoring set up for the equipment. Such as the innovative BLUEBOX™ solution, to apply advanced analytics which identifies potential issues. An initial assessment determined that two of the ARC valves had failed and would benefit from an immediate repair. Two other valves were leaking and would need to be repaired in the near future.
Examining Existing Data
The analysis of data over a five-month period highlighted several issues with the boiler feed pumps. The most significant were increased wear in the pumps, illustrated by reduced efficiency, and the fact that the electric motors were exceeding their rated outputs trying to achieve the required performance.
The raw data for flow and head were plotted against the OEM pump curve to establish the starting point for the project. The graph representation of the data also illustrated the vast range of flows the pumps were operating over, with the majority away from the best efficiency point (BEP). The data clearly showed the equipment was consistently delivering below the expected head, indicating the pumps were worn. Moreover, the results of the analysis revealed a variety of lost profit opportunities (LPOs) with some variability depending on the demand from the solar plant.
When the efficiency versus flow chart was plotted, it was clear to see there was significant room for improvement compared to the OEM efficiency curve. After reviewing all the information available, it was possible to set out a maintenance proposal, based on the risk of equipment failure, that could be delivered by the OEM-X Line Service.
Attention was drawn to one set of pumps due to the high expectation of increased vibration, seal failures, and bearing failures if prompt action was not taken. Overlooking this advice could result in pump rotor or casing damage, which has the potential to reduce output from the plant, incurring further costs.
Calculating The Cost of Inefficiency
Based on the knowledge of the maintenance company’s engineering teams combined with the delivered analysis, a comparison of equipment performance and opportunities for improvement was developed. In this case, it was believed the pump would operate at full load for 12 hours each day and that the energy price was USD $0.10 /kWh. Using the measured head and efficiency figures of 5,000 feet and 64% respectively, the annual energy bill for one pump in its current condition could be estimated at USD $1,260,840.
However, refurbishing the worn pump to as-new specifications would return the head to 5,300 feet with an efficiency of 78%. This would reduce the annual energy bill by over USD $250,000.
During the period of data collection, the pump was delivering a head of 4,925 feet and the plant remained fully operational. Therefore, it was concluded there was no reason to produce 5,300 feet of head as per the as-new specification of the pump. This offers the opportunity to rerate the pump with a reduced head, retaining the 78% efficiency figure. This rework would further reduce the energy costs by USD $71,650.
Investing For the Future
Working on the basis that both pumps would require similar levels of refurbishment and that the retrofit solution would work equally well in both situations, the plant has an opportunity to make considerable savings. From the current energy costs of over USD $2.5 million, the combined annual savings for the rerated pumps would equate to USD $643,440.
These figures are very significant and by using the estimated refurbishment costs, it is possible to offer a payback period of approximately 16 months, which would be an excellent opportunity. In fact, the same calculation provides a projected profit of USD$ 2.7 million over five years, having paid for the pump upgrades.
Ultimately, pump operators need to use their data more productively. Working with a partner that has the expertise and experience to deliver clear, actionable insights, as well as the retrofit engineering solutions to support these obstacles can drastically improve performance. This approach not only optimizes running costs, but also reduces the operator’s carbon footprint, and maintenance costs while helping to identify pre-failure conditions and allowing for targeted maintenance projects.
About the Author
Manish Talwar, currently serving as the Head of Retrofits Americas for Sulzer, has over a decade’s experience in delivering customized retrofit solutions for centrifugal pumping systems. Starting as a Graduate Mechanical Engineer in Leeds, UK, he progressed through the roles of Retrofit Specialist in the UK and Asia Pacific, to his recent leadership positions. Manish’s expertise spans technical optimization of equipment, implementing growth strategies, and leading global product lines. His current role involves driving growth in the Americas and ensuring timely delivery of high-quality retrofit projects.
About the Author
Dr. Marc Heggemann is Head of Digital Solutions with Sulzer. Marc works across the Flow Equipment and Services divisions to drive the use of data driven customer solutions in new and existing pump applications. With thousands of pump evaluations completed, Marc is highly aware of the demands pump operators are under and how the correct use of data analytics and insights helps them make informed decisions to minimize the ‘make or break’ situations engineering teams experience.