Steam has underpinned manufacturing since the Industrial Revolution and remains critical to many businesses today. Production and distribution have evolved considerably since that time, though safety and cost-efficiency are of far greater concern than they once were, not least due to considerations around sustainability.
Still, steam remains an expensive utility, responsible for a significant proportion of energy use, capital overhead and maintenance costs. Its ubiquity and relative simplicity, however, often see it overlooked by time-poor plant managers. This makes it an ideal candidate for closer attention from process engineers, in part because faulty equipment or leaking pipework is hardly uncommon.
It’s this situation that led the Growth Hub team, IMI’s innovation engine, to develop a novel steam trap monitoring solution, which is already delivering some impressive results.
Problems and preventatives
Modern facilities are designed and built to consume as little energy as possible so, in theory, it should be rare to find something as valuable as steam escaping from pipes and valves. Without regular maintenance, however, the number of leaks and volume of lost steam will inevitably increase.
Leakages from valves and steam traps can be categorised in two ways. The first is external, such as those from gland packing; the second is internal, where steam exits through the valve seat and into the outlet.
Detection is relatively simple when using existing process measurements. But it’s much more difficult to identify faults on valve packing and traps because they don’t usually have sensors installed. While deleterious and potentially serious, these faults are not mission-critical, so a control room will rarely pick up on them, leaving plant managers oblivious to a problem that could quickly lead to long periods of downtime and significant losses.
In steam systems that haven’t been maintained for three to five years, around 15%-30% of installed steam traps are expected to fail. If a steam distribution system includes more than 500 traps, this can equate to more than £384,000 of lost steam each year. Clearly then, it makes good sense to get this issue under control with regular inspections. The question is, how often?
Testing and inspection frequency varies depending on the size and pressure across the steam trap. Below is a general guideline for recommended inspection intervals:
High pressure (10 BarG and above): weekly to monthly
Mid pressure (2-10 BarG): monthly to quarterly
Low pressure (below 2 BarG): annually
The cost of leakage through a steam trap varies depending on how the condensate is recovered, how critical the process is and what product is being manufactured.
A novel solution for steam trap monitoring
Managing this workload for non-critical devices can be time-consuming, so a smarter, more efficient approach was sought by the Growth Hub team. This would allow engineers to diagnose leaks more effectively, but it would also free up time for them to focus on other, more critical maintenance tasks.
The result of these efforts was the Asset Monitoring application and STM-10 Sensor, an automated continual measurement solution that can communicate important KPIs, including leakages, blow through, blockages and hammering. This data can then be used to demonstrate plant efficiency and CO2 savings when compared with earlier yearly inspections.
Its compact design is easily installed to expose pipe on either side of the steam trap. The associated Asset Monitoring cloud-based dashboard gives operators and maintenance staff the ability to instantly diagnose steam trap failures, allowing corrective actions to be initiated before problems begin to harm production yields.
The STM-10 Sensor uses wireless long-range communications and thermal energy harvesting, making it a self-contained solution that can be installed by any member of the plant maintenance team. This combination of hardware and software components is not about collecting plant data for the sake of it, but rather so staff have a relevant dashboard of insights that can be used to make more competitive decisions.