Flavio Romero | Sulzer

U.S. manufacturing activity hit its highest point in four years in May 2026, and the initial agreement to end the conflict in the Persian Gulf could ease some supply chain tensions. While the industry will take any good news it can, manufacturers are still visibly weary of ongoing pricing volatility, snarled supply chains and tariffs.1 The importance of pump system optimization has never been greater as manufacturers seek cost management advantages from every possible angle.

However, procurement managers cannot be tethered to short-term thinking in these uncertain times. When it comes to procuring fluid engineering pumps, there is a truism that should not be ignored: the cheapest pump is almost never the least expensive over its lifetime. Too many costs accumulate throughout the life cycle of the pump system. This is why manufacturers can derive outsized long-term value by adopting life cycle cost (LCC) thinking, executed through data analytics, innovative service strategies and asset optimization.

Life Cycle Cost Thinking Curbs the Total Ownership Cost of Pump Systems

The worst costs are the hidden costs that lower-priced pumps can accrue over their life cycle. Lower-priced pumps often incur a substantial trade-off between lower capital expenditure (capex) and higher operating expenses (opex), driven by factors like material selection, less rigorous research and development and suboptimal startup and commissioning. Cost trajectories span decades, built up by maintenance and repair activities, energy consumption, unplanned downtime and performance degradation. Taking a broader view of a pump system’s life cycle—going beyond the immediate fix—helps protect long-term equipment performance and energy efficiency. Studies have revealed that the investment costs of a pump are only 10%-20% of the total ownership cost for repairable systems.2

LCC is the philosophy that companies can save significant amounts of money because of sound reliability management.3 With LCC in mind, pump system optimization starts on day one.

Protecting Long-Term Value at Installation

A 600 horsepower (hp) motor might cost $40,000 at inception, but operating continuously at an electricity rate of $0.10 per kilowatt-hour (kWh) can cost over $400,000 annually to operate.4 Any and all efficiencies to trim that annual cost will pay off massively over 30 or 40 years. Manufacturers can get a head start on optimizing life cycle cost by using digital simulation and system modeling to validate performance before installation. Installation should include meticulous reliability and performance testing, including a thorough examination of pipe stress measurement and precise alignment, as well as under-the-radar forces that degrade reliability. A thorough commissioning process ensures proper startup and establishes baseline performance data that feeds future monitoring and diagnostics. The LCC idea is to optimize fit-for-purpose performance over decades for long-term cost control, not to simply minimize capital cost.

Predictive Maintenance as an Optimization Tool

The Institute for Supply Management projected a 4.9% increase in capital expenditures and a 14% increase in prices paid for raw materials for the year-end 2026.5 Regular maintenance is the baseline, but proactive predictive maintenance is essential, starting with continuous monitoring to detect deviations early, continuously optimize energy consumption and operate at optimal conditions. This is where cloud, data-driven analytics and industrial Internet of Things (IoT) come in. Ironically, for industrial manufacturing, the next industrial revolution is coming from digitalization. A 2025 Deloitte survey report found that manufacturing executives largely view smart manufacturing as the primary driver of competitiveness over the next three years.6

Wireless IoT condition monitoring and sensors now enable continuous monitoring of vibration, flow and temperature in pump systems to identify failure patterns early, plan interventions proactively, minimize downtime and extend asset life. This LCC paradigm shift reduces uncertainty and the costs associated with it.