Predictive Maintenance of Steam Traps: Combining Demand Side Management and Performance Contracting

Annual testing is standard preventive maintenance for steam traps. When found bad, a trap has been leaking (on average) for six months. Predictive maintenance uses test samples to learn the traps' operating lives. By testing only a fraction of the traps and replacing traps before they leak, predictive maintenance reduces annual average steam trap costs from $43 to $12 per trap. Demand is lowered because 66% of the savings result from reduced steam loss.

District heating systems have inherent advantages applying predictive maintenance for their customers. As steam conditions are the same across the system, test sample results can be applied across the system. This can ease the negotiation of a performance contract, as it is difficult for others to compete. Because 33% of the savings come from economies of scale in trap replacement and reduced steam trap testing, district heating systems can increase profits and service while lowering heating costs

THE PROBLEM

Leaking steam traps are a major source of energy waste in a district heating (DH) system. Steam waste in the DH system before delivery increases the cost of steam supplied to customers. Steam waste in the customers' heating system increases their costs and makes them more likely to change to other heating methods. Additionally, raw steam in condensate return lines may cut their operating lives in half. Annual steam trap testing is generally presented as the solution. This "solution" has several difficulties:

1. Testing steam traps is expensive — averaging $10-25 per trap.
2. It requires conscientious use of test equipment by trained, experienced personnel.
3. Test frequency tends to slip to 2- or 3-years, causing energy losses to triple or hextuple.
4. The basic cost — personnel time — cannot go down, only up.
5. District heating companies have no advantages applying this solution.

District heating companies (DHCs) have two potential advantages in approaching such problems: Economies of scale and breadth of information. The ideal solution will take advantage of both.

THE ANALYTICAL TOOL

The computer program TrapCost™ (an earlier version of Steam$$™) simulates the steam trap-related costs of a steam system. A sample of 2617 steam traps from a district heating system was used to evaluate ways of dealing with them under various assumptions. The program allows changing the number and types of traps in the system so that other systems can be similarly simulated. Based on this analysis, we developed a solution that seems ideal.

OVERALL RESULTS

The largest cost differences are found among steam trap management strategies. The results of eight are shown in Table 1 and discussed below, with steam trap replacement costs based on maximum expected economies of scale.

	Test	Replace	Energy	Total
No trap management	$ .00	$ .00	$166.36	$166.36
3-year test & replace	6.42	5.18	26.16	37.76
2-year test & replace	8.92	5.44	17.44	31.80
1-year test & replace	16.42	5.73	8.72	30.86
Optimum test & replace	8.42	5.66	10.85	24.92
Predictive replacement	2.52	6.09	.81	9.42

"No trap management" ignores the steam traps and allows them to leak. Once a trap begins to leak it deteriorates quickly. However, a steam trap cannot leak more steam than is supplied to it. Most systems limit the steam flow to 20-40% above the expected requirement. This paper assumes 30% maximum losses.

"3-year test & replace", "2-year ..." and "1-year ..." are conventional steam trap management strategies. The steam trap is assumed to go just bad enough to detect with a portable tester (10% leakage above the condensate level) halfway through the test interval. Annual test costs differ because of the frequency of testing. Replacement costs differ because the operating life of the trap is increased by half the test interval. Energy costs differ because the trap deteriorates until it is leaking as badly as the trap design permits. The total shows an improvement over no trap management for the 1- and 2-year test intervals, but no improvement for 3-year intervals.

"Optimum test & replace" minimizes the total of testing cost and energy losses. In effect, this strategy trades slightly higher trap replacement costs for lower testing costs and energy losses, reducing total steam trap costs 26% below annual test & replace.

"Periodic replacement" replaces all traps every 3 years. The replacement interval was chosen so that no traps will be bad when replaced. This is the easiest strategy to manage and provides costs lower than all of the above. However, in many facilities this approach would be too disruptive. This strategy reduces total costs 52% below annual test & replace. The savings come from both testing and energy.

"Adj Periodic replacement" adjusts the trap replacement intervals for the amount of time they are actually working with steam and the relative lives of different trap types. These intervals are still short enough than no traps will have failed by replacement. It provides significant savings for seasonal applications and when traps are downstream from a motorized valve. This strategy reduces total costs 70% below annual test & replace. The savings come from both testing and energy.

"Predictive replacement" provides additional savings for some trap types. 4 test samples of 20 traps each determine the actual operating life of 2211 of the 2617 traps. In-line trap test units were installed for the samples so their testing cost is only $5.00 each and the results are more accurate due to lower test sensitivity (4%). The other 406 traps are managed by Adj Periodic replacement. Predictive replacement reduces total costs 73% below annual test & replace. The savings come from both testing and energy.

All strategies but predictive replacement can be used as well by DH customers as by DHCs. However, DHCs have a competitive advantage in using predictive replacement because their test samples can extend across customers. More DHC steam traps are represented by samples and consequently have lower testing costs. Only a DHC can maximize the advantages of predictive replacement.

Economies of Scale

Economies of scale affect the cost (including labor) of replacing steam traps. In Table 2, these vary over 100% from Table 1, representing the difference between a large, competitively-bid contract (Table 1) and smaller-volume trap replacements. The test and energy costs are the same as in Table 1.

	50% Higher	100% Higher
	Replace Total	Replace Total
No trap management	$ .00 $166.36	$ .00 $166.36
3-year test & replace	7.77 40.35	10.36 42.94
2-year test & replace	8.16 34.52	10.88 37.24
1-year test & replace	8.59 33.73	11.45 36.59
Optimum test & replace	8.49 27.75	11.31 30.58
Predictive replacement	9.13 12.45	12.17 15.48

To place Table 2 in perspective, the labor and replacement part for a Thermostatic steam trap from Table 1 might cost $44, in Table 2 it would cost $66 and $88. In 1993 a large industrial facility in the Northeastern U.S. was paying about $100 to replace such a trap while another of the same size was paying $44. Clearly, not everyone uses their potential economies of scale.

DH customers can try the 1- to 3-year test & replace and Periodic replacement strategies in Table 2 to reduce their steam trap costs. The lowest price they can reach is $19.37, versus the DHC lowest price of $11.89 from Table 1 — creating a $7.48 differential. More likely is $46.87 — creating a $34.98 differential. These differentials provide a DHC opportunity to combine demand side management with performance contracting while increasing customer service.

The entire $7.48 margin results from economies of scale realizable by a DHC. Table 3 shows a breakdown of the $34.98 margin. The $21.10 of energy savings, less 40% (lost contribution) plus the test and replace savings, provides $26.55 per trap per year of potential benefit from predictive replacement — plus demand side management savings.

	Test	Replace	Energy	Total
Annual T&R, 50% pricing	$16.42	$8.59	$8.72	$33.73
Less, Predictive replacement, 0%	2.52	6.09	.81	9.42
Annual savings per trap	$13.90	$2.50	$7.91	$24.31

The potential benefit will is some weighted average of the $7.38 and $34.98 benefits. Anywhere in this range is attractive. Next we consider how the DHC can use this and, then, how to effect the transition.

THE DHC OPPORTUNITY

Reducing energy waste from $21.12 to $.02 (a 99.9% reduction) provides a demand side management opportunity. This is a minimum savings of 3.5 million pounds of steam per year for each 1,000 steam traps. If the current steam trap maintenance strategy is to test less frequently, the potential savings are much greater.

Getting an idea where steam is wasted is not difficult. Look for steam from vents, overpressure in the condensate line, and high condensate temperature. If all are found, steam trap losses are high — toward (or even above) the upper limit.

The performance contracting opportunity combines demand side management with economies of scale in trap replacement and management. The $7.48 to $34.98 gaps found above are the savings to apply when calculating the potential benefits. DHCs have choices in how to benefit from this gap. The choices can be constructed from the following opportunities:

1. Contracts for complete steam trap management, potentially including initial trap replacement.
2. Contracted costs for testing and replacement of steam traps.
3. Participation in steam trap maintenance contracts can be linked to long-term steam purchase contracts.

Developing and capitalizing on these opportunities provides a new avenue for DHC marketing efforts. For example, the DHC could manage customers' steam traps in return for a long-term contract with charges for each trap. These charges would support the DHC's trap replacement and a shift to predictive maintenance. This shift would provide lower heating costs and a higher level of service to the customers. The DHC would make a greater profit on the trap replacement and maintenance than its loss of margin on the lower sales, and would have the benefits of demand side management.

IMPLEMENTING PREDICTIVE REPLACEMENT

The proper way to transition from the current trap management strategy to predictive replacement depends on what traps are installed and how they are managed. As shown in Table 4, annual management costs of different types of steam traps and applications differ greatly.

Trap Type	APP	# Traps	# S	No Mgt	50% 3-Year T & R	50% 2-Year T & R	50% 1-Year T & R	0% Predict Replace
F & T	Drip	541	3	$243.83	$78.01	$59.59	$51.62	$17.38
F & T	Working	62	1	80.77	33.63	28.89	33.21	19.61
F&T-HI CAP	Working	11	0	1228.04	259.09	183.91	127.47	85.30
I B	Drip	24	0	206.78	74.94	57.58	50.44	37.47
I B	Working	45	1	69.83	26.98	23.93	28.94	11.83
T	Drip	291	2	316.32	64.49	48.63	39.79	9.22
T	Working	1546	3	107.32	24.00	21.17	24.80	4.45
TD	Drip	13	0	362.50	135.60	99.85	77.24	57.40
TD-L	Drip	23	1	173.32	84.39	65.42	58.91	32.04
TD-LC	Drip	1	0	60.62	52.75	44.64	49.26	32.15
BI-METAL	Drip	1	0	309.27	74.06	56.18	47.77	38.46
Overall Average		2588	11	$166.36	$42.94	$34.52	$33.73	$9.42

The average annual costs in Table 4 decline from left to right as trap management improves and replacement costs decline. This was expected from Tables 1 & 2. Cost differences among both trap types and applications moving vertically in the table is new information. Trap types' annual costs differ because their designs and costs differ. Drip traps have higher costs than Working traps because they have lower condensate loads, allowing greater losses when the trap leaks. And, while not represented in the numbers, Drip traps tend to wear out more quickly than Working traps because of the lower condensate loads.

Table 5 combines the trap costs from Table 4 with the replacement costs and operating life. The return on investment (ROI) for changing to predictive replacement by immediately replacing all traps of a trap type/application combination is calculated from the DHC's point of view.

Trap Type	APP	Op Life	Replace Cost	No Mgt	50% 3-Year T & R	50% 2-Year T & R	50% 1-Year T & R
F & T	Drip	7.37	$94.65	149.6%	54.3%	40.6%	39.0%
F & T	Working	10.80	98.45	37.3%	14.6%	10.1%	17.9%
F&T-HI CAP	Working	9.29	291.64	234.2%	41.4%	22.4%	8.7%
I B	Drip	6.55	81.54	120.8%	31.7%	14.2%	12.8%
I B	Working	12.20	83.27	43.8%	19.8%	17.0%	25.7%
T	Drip	9.50	43.65	424.2%	91.2%	69.8%	64.7%
T	Working	13.29	42.58	148.3%	41.7%	38.7%	51.3%
TD	Drip	5.63	112.00	160.0%	47.1%	22.0%	9.9%
TD-L	Drip	5.43	99.39	87.9%	44.0%	29.5%	29.4%
TD-LC	Drip	5.00	96.00	-3.1%	22.3%	13.5%	23.1%
BI-METAL	Drip	9.31	95.00	165.6%	23.4%	7.6%	4.8%
Overall Average		11.33	$58.13	175.0%	48.9%	41.1%	48.0%

Not surprisingly, we find that poor past steam trap management and the effective use of test samples provide the highest ROIs for changing to periodic replacement. The DHC can capture part of these ROIs through performance contracting.

Remember that replacing all of the steam traps of a trap type/application combination provided the returns in Table 5. Trap type/application combinations without test samples and orphan traps within a combination are managed with Adj Predictive replacement in the simulation. Only if there were 80 or more traps of a single size, trap type and application were they managed by predictive replacement.

The high overall average returns in Table 5 suggest replacing all steam traps at once. While some trap type/application combinations might not be replaced due to funds limitations, these are likely to have little affect on the overall return. This is particularly true if high volumes from wholesale replacement reduces cost and/or the number of different traps in the system.

To use the predictive replacement strategy, trap lives must be determined. If all traps of a pipe size/trap type/application are replaced at once, the test sample for determining the trap lives is chosen from easy-to-test traps in intensive use. These traps will fail first, determining the trap life for the other traps.

CONCLUSION

District heating companies have substantial competitive advantages in dealing with steam traps. These result from their access to system-wide information and economies of scale. By capitalizing on these advantages, many different combinations of cost reduction, increased service, demand side management, and performance contracting can be supported. The optimum combination of these depends on the competitive choices of the DHC.