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U.S. Department of Energy 

Commercial and Industrial Pumps Negotiated Rulemaking Working Group 

Meeting Summary—Fifth Meeting 

Forrestal Building, Washington, D.C. 

April 29 - 30, 2014 

Members in Attendance (Day 1) 

Lucas Adin U.S. Department of Energy 

Tom Eckman Northwest Power and Conservation Council (ASRAC Member) 

Robert Barbour TACO, Inc. 

Charles Cappelino ITT Industrial Process 

Greg Case Pump Design, Development and Diagnostics (Hydraulic Institute) 

Gary Fernstrom California IOUs 

Mark Handzel Xylem Corporation 

Albert Huber Patterson Pump Company 

Dan Delaney Regal Beloit (alternate for Howard Richardson) 

Joanna Mauer Appliance Standards Awareness Project 

Doug Potts American Water 

Charles Powers Flowserve Corporation, Industrial Pumps 

Louis Starr Northwest Energy Efficiency Alliance 

Greg Towsley Grundfos USA 

Meg Waltner Natural Resources Defense Council 

Doug Brookman Facilitator, Public Solutions, Inc. 

Absent Steve Rosenstock Edison Electric Institute 

Additional Attendees 

Jeff Alascio, Alex Bosenberg, Robert Boteler, Brian Carlson, Daniel Cohen, Katie Coughlin, 

Charles Foster, Jeremiah Freeman, Emily Marchetti, Harry Massie, Jiangang Hu, Elizabeth Kohl, 

Christopher Lau, Brent McManis, Laura Petrillo-Groh, Callie Reis, Arnie Sdano, Brent 

McManis, Steve Thompson, Daniel Weintraub, Sarah Widder and Alison Williams 

Day 1—Working Group Meeting #5, April 29, 2014 

Facilitator Doug Brookman called the Working Group (WG) meeting to order and welcomed all 

present at 9:05AM. The facilitator noted that a few members were running late based, again, on 

inclement weather. 

The WG proceeded with introductions around the room. The facilitator made brief introductory 

remarks, describing the good progress made in the last meeting. He referenced the following 

agenda elements compiled by DOE and the consultant team: 

 Provide an overview of items to cover—the pathway to finalizing the term sheet 
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 An overview on progress to date 

 Compiling an interim report on Progress to Date to ASRAC 

 The process for establishing a test procedure and 

 Scheduling issues and a review of the analyses that need to be completed 

Lucas Adin started by providing an overview, noting that the WG had two in-person meetings 

left after this one and a lot to cover in that time. He noted that the team had performed a lot of 

detailed analysis that would be presented, including: 

 Preliminary estimates of potential energy savings for pump types 

 Metrics 

 Test procedure 

Continuing, he described the engineering analysis, which considers the kinds of technologies 

available, which are then screened in or out for improving the efficiency of a pump and then 

consider costs and how a cost-efficiency curve is utilized to show the cost of an additional 

increment of efficiency improvement (p.16). He stated his intention that the WG provide an 

interim report to ASRAC. One issue to be considered was whether the WG should consider 

expanding the existing authorization (beyond what would be the normal term sheet) to 

consider adding test procedure deliberations to the negotiation. Typically DOE takes the 

initiative to create and publish a test procedure. He referenced raising this issue in the report 

to ASRAC. 

Dan Weintraub started presenting on the general process of how we set efficiency levels, 

providing the following overview: 

 Efficiency levels can be described as a possible standard level 

 These are levels that can be evaluated and analyzed to determine if they're economically 

justified. In a typical rulemaking, DOE establishes and evaluates multiple efficiency 

levels for each equipment class under consideration. 

 In this case the WG may participate in establishing these levels. 

 And the WG will eventually give recommendations on what levels DOE should be 

setting. 

 We will review the economic analysis and the energy savings—that would be the basis 

for the WG’s decisions 

Dan continued, providing an example of setting a baseline, using the EU methodology as an 

starting point (p.27). He clarified that the EU MEI is a market-based index that simply 

represents how well the pump’s efficiency compares to the marketplace as a whole. Continuing, 

“step one of this process, is defining the efficiency surface...due to the size and geometry 

differences, every pump in the marketplace has a different maximum attainable 

efficiency....based on extensive research, the EU concluded that attainable efficiency is a strong 

function of flow and specific speed. The research defined an efficiency surface by the average 

efficiency seen in the EU marketplace for all pumps within the scope. And this was set as a 

function of flow and specific speed because those were the factors that were defined. So all 

pumps falling on this MEI surface are, therefore, of equal, relative efficiency. They're on the 

surface. They all compare similarly in the marketplace. So this allows pumps of varying flows 

and specific speeds to be compared on an even playing field.” 
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Dan continued, “using the surface to define MEI levels, you can translate the efficiency surface 

up and down to create efficiency levels that remove or cut off pumps from the marketplace. So 

you have the surface. You move it up. You cut off more pumps. You move it down. You cut 

off less pumps. The equation that we have right there, that is the equation for minimum 

efficiency. That's the equation of that surface. And on the end, almost covered by the toolbar 

but thankfully not, we have a red C. That's C-value. That just allows you to translate that 

surface up and down. And in the EU, that's what they used.” 

He continued, illustrating in 2-D an example showing speed and flow of a pump, shifting the 

surface up and down, cutting off dots and changing the MEI (p.32). Responding to a question 

Dan clarified, “the shape of the surface is the key. And then the population will sit in relation to 

that surface. The surface is then moved up and down with that C-value so that you're cutting off 

as many pumps as you are targeting to cut off.” Another member added that the shape of the 

curve is fixed—its level on a vertical axis is variable depending upon C-factor. Dan 

summarized, “C-value is a translation factor that allows you to move up and down the y-axis, 

allows that surface to move up and down the y-axis, and determine how many pumps you want 

to cut off at a given efficiency level.” 

Continuing the EU example, “...looking at the EU lot 11 efficiency level results, this is how 

the EU did what we were just explaining....each efficiency level in the EU targeted a constant 

failure rate for each equipment class. So that meant they looked in their analysis. Eventually 

they set levels in their original analysis. Down at the bottom, you see they targeted 5 percent of 

the pumps cut off, 10 percent, 15, and so on. And for each one of those in each equipment class, 

they found the C-value that would cut off the appropriate number of pumps. And that C-value is 

different for each equipment class and each speed because they looked at them as being 

independent and having their own kind of properties as a pump....this is how the EU did it. And 

you can see if we were to mimic our process, I drew in EL-1, EL-2, EL-3 above those. 

That's how it would be done. We would say, we have all of these levels. Now we know 

we're going to determine what the cost is to get there. And then we're going to see whether 

it's economically feasible and so on.” 

A member clarified that DOE is not proposing the use the European MEI method. Dan said not 

at this time. The member asked why. Alison Williams responded that, consistent with earlier 

WG discussions, this metric is trying to cover pumps along with motors and controls. “This 

(MEI) schema only covers pumps, bare pumps.” The same member expressed concerns, from 

the manufacturer’s caucus, about using a single metric for both cases.... “We don't agree with it. 

And we think it's a problem. We think it will be confusing in the marketplace, and we don't 

think it will yield what you are looking for. (p.45)” 

Choosing an Efficiency Level 

Dan Weintraub continued presenting, describing two parts: how you choose an efficiency level 

and how you define that level with a metric. Using what the EU did as a model, he described 

how the WG would be targeting ‘failure rates’ for each equipment class. And based on the 

discussion in the WG’s last meeting, we targeted looking at 10 percent, 25 percent, 40 percent, 

55 percent, 70 percent and 85 percent of pumps failing—our efficiency levels—at each 
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individual equipment class. Next we must determine C-values for each equipment class at each 

efficiency level. This requires utilizing a metric. He showed the PER metric and described the 

‘equation work’ necessary to determine C-values. Utilize equal weighting for 75%, BEP and 

110%. At each load point you have hydraulic power of the pump divided by the pump’s 

efficiency times the motor efficiency, which gets you the input power to the pump. 

Hydraulic power is a function of flow and head. For each pump, there is a hydraulic power that 

is defined because each pump is going to have a different attainable efficiency. Therefore, 

hydraulic power is fixed for each pump. Motor efficiency is also fixed because it is going to be a 

function of what you choose as the minimum motor efficiency allowable in this metric. 

Summarizing: the only variable in the equation, when you are looking to set an efficiency level, 

is the pump efficiency at each level—the pump efficiency at 75%, BEP and 110%. So the 

minimum required pump efficiency equals this function of flow and specific speed minus C—for 

a given pump, flow and specific speed are fixed. C-value is the only thing you can change to 

change the minimum required efficiency—so minimum required pump efficiency is purely a 

function of C. Dan continued, supplying a specific example of how the EU regulation works and 

how the proposed PER is similar (p.53). 

Next, Dan compared C-values developed from U.S. pump data to EU C-values. He concluded, 

“the only effective difference here, for an MEI, your failing C-value is the worst of the three, the 

one that you fail at, because you have to pass independently at 75 percent flow, 100 percent, and 

110 percent. So the worst value you have is the one that fails. With the PER, it's effectively 

right now a weighted average. Three points. Take your weighted average. That's what you're 

going to compare against the metric. So all pumps are then shifted. All pumps are affected the 

same way. But the end effect is that the C-values under a PER are going to show themselves to 

be a little more efficient, a little better-performing, but a little better-performing all across the 

board because you're taking a weighted average, rather than taking the worst performing number 

(p.59).” 

A member asked whether there was a way to translate from PER to MEI, or if it is possible to do 

a ‘cross-walk’ for comparison purposes. Dan stated that there is no mathematical crosswalk 

because under the MEI one bad load point that fails, so even if everything else was good, you 

fail. Under the PER you are averaging to get the score. Another member stated that the MEI 

was designed to reflect real world conditions where a pump may operate anywhere along the 

spectrum from 75 % to 110% and still be required to be efficient. He continued, pointing out 

that whatever the evaluation schema, pump designers will design to meet that level of 

performance. The MEI method assures that you get a ‘higher overall curve’ when operating. 

A member noted that a company selling internationally would have additional administrative 

overhead dealing with two different methods. Another member asked if it is possible to mimic 

the European system. 

Examining the Data (p.74) Determining Efficiency Levels (78) 

Dan started by pointing out that the C-values for end suction closed-couple and end suction 

frame-mounted pumps were all very similar, within their respective of speeds. 
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Dan described a set of analyses to determine the efficiency levels of a given product. Those 

analyses are: 

 average lifecycle cost savings, which includes incremental equipment costs, 

 operational savings, 

 define the lifecycle costs, 

 percent of population with net cost/net benefit/no impact, 

 national energy savings, 

 national net present value, and 

 change in industry net present value (impact on manufacturers) 

After all these analyses are completed, the WG will review the results to propose standard levels. 

He described the methodology—how a manufacturer would determine whether a pump would 

pass or fail at an efficiency level. As follows (handout p.16): 

 You calculate your PER pump according to the methodology described in the test 

procedure. (Right now you have a calculator spreadsheet that you can use). 

 Then use the energy conservation standard formula to determine the PER standard 

specific to the pump models, hydraulic characteristics at a given efficiency level. 

 

Example: “in this equation, end suction closed-couple, 1,800 rpm with standard set at EL-3. EL3, off of the table that we had before, has a C-value is 126.86. So in this equation, PER standard 

equals, this big bracket right here is one over BEP pump, required BEP pump efficiency. And 

that can be pulled out because we knew that that was the only variable. You multiply that times 

all of these factors, which are static and determined by the pump itself, your hydraulic power, the 

factor of .947 or .985, and the motor efficiencies, which would be pulled off a table, as we have 

discussed thus far. You calculate that out, and you find out what the standard is for your pump. 

And then you compare what you have calculated for your pump itself versus the standard, and 

you see whether you pass or fail.” 

 

Summarizing, “In the end, it's a spreadsheet calculation, even fairly simpler than the PER 

calculator, because there is only one equation that varies. So each pump, you can look at 

efficiency level 1, 2, 3, 4, 5, 6 and see where you pass and see where you fail for every pump.” 

Returning from the mid-morning break, Dan Weintraub began by presenting an overview on the 

Engineering Analysis process, referring to a large flow chart (handout p.3, transcript p.83). The 

sequence is: 

 Navigant and LBNL perform analysis, conducting manufacturer interviews and doing 

independent industry research. 

 Next the analysis considers design options, which is market and technology screening 

analysis. 

 Then the analysis considers two separate factors: available efficiency improvement and 

the cost of applying those available efficiency improvements (also called design options) 

and determine how the design options would be used in the marketplace. 

 Then determine the average incremental manufacturer’s production cost (MPC), per unit 

sold 

 And also at this stage, find the aggregate conversion cost to industry 

 On a parallel path, the analysis models MPC and baseline markups. 
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 Taking these analyses, you model industry market pricing and economics 

 That enables you to find the average incremental manufacturer’s selling price—an 

estimate of how much the price of a product would go up to the first purchaser at a given 

efficiency level 

A member commented that each company’s markups and other factors will be different. Dan 

indicated that the analysis tries to account for this, by including, for example, both small and 

large manufacturers. 

Market and Technology Assessment (handout p.4, p.89) 

Dan went through a list of potential technology options to improve efficiency, followed by a 

more detailed description, including: 

 Improved surface finish 

 Improved hydraulic design 

 Reduced running clearances 

 Reduced mechanical friction in seals 

 Reduced volumetric loses (removal of thrust balance holes) 

Screening analysis is employed to evaluate the technology options based on the following 

criteria: 

 Technological feasibility 

 Practicability to manufacture, install and service on a commercial scale 

 Impacts on product utility or availability 

 Impacts on health and safety. 

This analysis resulted in the following technologies being screened out: 

 Reduced running clearances 

 Reduced mechanical friction in seals 

 Reduced volumetric losses 

 Surface coating or plating 

After generally confirmatory remarks, members commented that there are other factors that 

matter such as sustainability of efficiency gains, effective containment and overall safety. 

After the analysis, the following design options were ‘screened in’. These will be subject to 

further, more detailed analysis: 

 Hydraulic redesign as a base 

 Hydraulic redesigns with a change to advanced casting techniques-including changes to 

investment, die or lost-foam casting and surface finish improvement options—surface 

polishing of the impeller and/or volute. 

 Impeller and/or volute geometry redesigned for higher efficiency. 

 Hydraulic redesign to advanced casting techniques—the impeller could also be cast using 

advanced techniques, which would give it an improved surface finish. 

 Cast bronze and stainless steel impellers can be investment or die cast 

 Surface finish improvement options: surface polishing of impellers or volute 
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Engineering Analysis (p.101) 

The purpose of the engineering analysis is to determine the incremental changes in manufacturer 

selling price at each proposed efficiency level. This cost-efficiency relationship is a key input 

for the following downstream analyses: 

 Life-cycle cost and payback period analysis 

 Manufacturer impact analysis 

 Employment impact analysis 

Dan continued to present on potential efficiency improvement areas, with a detailed description 

of hydraulic redesign options, leading to a description of costs for hydraulic redesign up to 

MEI/PER 40 (handout p.18, p.108). Continuing, Dan referenced a Hydraulics Institute study 

showing costs of redesign for 1 HP, 50HP and 200HP pumps. He stated that the analysis team 

has a data base that now includes 50 percent of all pumps shipped, including the performance of 

those pumps. Utilizing these data, the team came up with estimates of the average unit cost for 

the redesign of different pump types. 

Some of his conclusions: 

Hydraulic redesigns are not expected to impact manufacturers’ production cost (MPC). 

Designs beyond the MEI-40 level will cost manufacturers more (design and test labor costs) to 

complete. For example, EU Lot 11 manufacturers’ data indicated it would cost 1.6X more to 

design a pump model to MEI-80 versus MEI-50. Considering small manufacturers as well, the 

analysts arrived at 1.8X as the increased cost number for the U.S. marketplace. He continued 

that the U.S. has many small manufacturers, and they would have a heavier cost burden than 

their large manufacturer counterparts. (p.116). Responding to a question, he explained that the 

cost of designing higher efficiency pumps is higher because the design effort is essentially an 

iterative process with design-test, and repeat design-test iterations, until the final efficient design. 

A member confirmed what Dan was saying and contributed that as the efficiency gets higher the 

pathway to achieving it gets “less and less clear.” 

Based on research and manufacturer interviews, the analysts determined that advanced casting 

(pattern and tooling) costs 2.4X more, on average, than sand casting tooling, and advanced 

casting methods currently make up 60 % of the market. Using the data from HI, and applying 

the anticipated cost increases, the team made estimates of the costs of advanced casting and 

tooling for 1, 50, and 200 HP pumps (handout p. 21). 

Members questioned the cost estimates: 

 Wouldn’t the labor costs be lower with advanced castings? Answer: a manufacturer pays 

a lot more up front for these technologies, but once you have made that investment the 

costs per piece are the same. 

 Another member reflected that the cost per pound or cost per the same casting would be 

higher for investment casting than sand in all cases. The analysts reflected that 

manufacturer surveys indicated “it was a wash” between different casting methods. A 

member contributed that considering both the casing and the impeller, and looking at 

factors like labor, scrap rate, etc., “that when you combine those two, it’s almost a wash.” 
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 Continuing Dan stated that the team concluded that the cost of advanced casting tooling 

is 130 percent of what was quoted in the HI survey. 

Costs: Hydraulic Redesign (HRD) with Change to Advanced Casting (handout p.22, p.134) 

Members asked for clarification on the cost data and Dan described how the figures were 

derived. Continuing, Dan concluded that the average HRD cost for an end suction pump is 

$223,000 and the average cost for an inline pump is $221, 000—both reflecting a 7% cost 

increase. 

Surface Polishing (handout p.23, p.137) 

Surface polishing was determined to cost approximately 45% of the finished impeller cost for 

End Suction and Inline pumps. Dan confirmed that those were the average costs to redesign an 

average pump to MEI-40. Continuing, he restated that 60% of the market currently employs 

advanced casting techniques. An online contributor asked if the analysts considered that 

advanced casting tends to be labor intensive and only cost-effective if sourced from low-cost 

countries. Dan replied that the research showed a majority of investment casting is done onshore 

“because the quality offshore is not there yet”, but confirmed that it is labor intensive. 

Looking at costs, on average the shipment-weighted cost of the average pump out the door was 

estimated to be an increase in impeller cost of $46 for end suction pumps and $50 for inline 

pumps. The costs were based on survey data, reflecting what manufacturers reported they would 

do. 

Summary of Engineering Costs (handout p.24, p.149) 

Dan displayed a chart which showed the model-weighted average cost to move End Suction and 

Inline pumps from MEI-40 to MEI-70, with specifics about hydraulic redesign cost and 

hydraulic redesign with investment casting. 

Modeling Industry-wide Implementation of Design Options at Each Efficiency Level (handout 

p.26, p.153) 

Dan described how the industry is arrayed and how these design options could be applied and 

what the cost of the design options would be across the industry. He described the following 

methodology: 

 The engineering analysis will attempt to model the redesign choices that will be made by 

the industry when faced with various efficiency levels. 

 A cost model will start with the total number of pumps failing at a given level. 

 Assign design options to each failure based on market data and direct industry research. 

 Choose an efficiency level and analyze, one at a time—at each efficiency level, you have 

pumps that are failing and pumps that are passing. 

 Your output is an estimate of the number of models that are going to be dropped and not 

redesigned, the number of models that would be hydraulically redesigned, the number 

that would be hydraulically redesigned and changed to investment casting, the number of 

models that would be polished. 

Dan described the primary assumptions which guided the redesign options chosen (p.156). A 

manufacturer questioned the methodology, based mostly on market realities, costs and 
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customer/manufacturer’s needs. Another manufacturer agreed, cautioning especially about over 

reliance on polishing as a means to meet the efficiency target. Another member agreed that 

polishing might be a short term answer while waiting for a redesign. 

Dan continued, a primary assumption is that not every pump will be redesigned. This would be 

due to existing low sales volume, overlapping performance and multiple brands. Some pumps 

will be substituted for others. Dan described the assumed failure rate: at PER-10, 60 % of the 

failing models would be dropped and not redesigned; at MEI (PER)-40, an average of 40% of 

those pumps would not be redesigned—and that level of failure was consistent moving up 

toward the MEI-70 level. Dan clarified that he was looking at the industry as a whole. 

Manufacturers commented that the numbers seemed “extremely high.” Manufacturers described 

the role of pumps that are loss leaders and the practical need to maintain a complete catalog of 

pump types. 

A member asked what percent of total sales was represented by the 60% of failing models. Dan 

responded that at PER-10, it is below 7% of sales—the failing models are not a large percentage 

of sales and not a large percentage of models overall. A member contributed that “if Europe 

went to (MEI-)40 percent of the market standard, that a fair fraction of the existing market would 

fail...we’re trying to cut 40% of the least efficient...” 

Dan presented a summary of the estimated results (handout p.33, p.182). The total number of 

ESCC/ESFM models currently is 2,050. At PER-10, 250 of those fail by definition. It's 250 

models over those 2 equipment classes. If we're saying 60 percent of the models are dropped, 

that's 123 dropped. Eighty-two models will require redesign. A manufacturer described the 

chart as “scary”, raising the possibility of some companies that might be concentrated in models 

that are failing and also the prospect of having products move offshore. Dan clarified the 

results model the industry as a whole. Lucas Adin added that the jobs impact is a part of a 

different analysis. 

As a summary comment, a manufacturer said he and his industry counterparts had significant 

reservations about the estimates, “that 60 percent of the product would not be redesigned is kind 

of mindboggling to this group.” Another manufacturer agreed, stating that the estimate was 

counterintuitive because the industry today “is always trying to reduce inventory, reduce the 

number of model lines.” The discussion turned to ways of gathering more data, improving the 

data, interpreting the data and the timing of it all. Members complimented Dan on a very high 

quality presentation. Several members closed out the morning session with their views of the 

potential impacts to the pump industry, especially for small manufacturers. The WG broke for 

lunch. 

Summary of Inputs for ESCC/ESFM and IL (handout p.32, p.211) 

Dan Weintraub provided the following overview: 

 We have 2,050 models for end suction closed-couple and end suction frame-mounted 

(survey data). 

 We looked at total shipments 

 We scaled up our models by the same scale as our total shipments. 
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 If we had approximately 100,000 shipments, that's approximately 2 times more shipments 

than what our data represented. 

 Then we scaled up the number of models in our database by two (This number will 

change based on the new data that we're getting from HI) 

Then he reviewed the data categories: % Models dropped at PER10, % Models dropped at 

PER40, % of Casting Investment/Die Cast, % of Castings Sand Cast, % of Castings switched to 

Investment/Die Cast, % of Models Fabricated Stainless Steel, % of Pumps Eligible to be 

Polished, % of Eligible Pumps Polished. Describing the results for ESCC and ESFM Pumps, he 

noted that very few models are polished at PER10 or even PER25 through PER70. The bulk of 

the redesign activity to meet new efficiency levels will be hydraulic redesign only and limited 

number of additional models utilizing hydraulic redesign with changes to advanced casting. He 

continued, describing Inline pumps with similar results: very few models are polished; the bulk 

of them are hydraulically redesigned. 

Next he reviewed shipments-weighted results for ESCC/ESFM at each of the different efficiency 

levels, starting with projected number of shipments failing, then percentage of total shipments 

failing, the percentage of failing shipments polished and the total number of shipments polished. 

A few results: at PER10, 7 percent of total shipments fail. Ten percent of the bottom models 

represent seven percent of shipments. For Inline pumps, 3.2 percent of the models are polished. 

Average Incremental MPC Per Unit Sold (handout p.37, p.220) 

Dan continued, the incremental MPC per unit sold is, effectively, what the change of cost is due 

to polishing across the industry. The methodology is, for each equipment class and efficiency 

level, the industry shipments-weighted average cost to polish an impeller is multiplied by the 

number of shipments that will feature a polished impeller. This creates the total aggregate 

incremental cost for the industry. Divide that by the total number of failing shipments which 

results in the average incremental MPC per unit sold. 

Earlier the analysts described this cost as about $45 with about 400 to 600 units that would need 

polishing. Multiply the cost per unit times total units, take the result and divide it by the number 

of failing shipments. The result is, on average, less than $2. If you are looking at an industryweighted average, it ends up being an average increase of less than one-half of one percent—.2 

or .3 percent. The conclusion: this is a small cost to the industry as a whole because there are 

very few units being polished. 

Aggregate Industry Conversion Cost (handout p.41, p.221) 

For each equipment class and efficiency level, the adjusted industry average redesign costs are 

multiplied by the number of models requiring each redesign. This creates an aggregate 

conversion cost for the industry—the costs per model to hydraulically redesign. Multiply that 

times the number of models that are going to be hydraulically redesigned and the result is the 

aggregate cost for the industry—a bottom-up approach to ascertain how much it is going to cost 

the industry as a whole to meet an efficiency level. 

Accounting for Redesign Cost Sharing Between Shared Model Platforms (handout p.42, p.223) 
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Because ESCC/ESFM and 2/4-Pole pump models share significant hydraulics and hardware, the 

team did not expect every model in the database to incur the cost of a full hydraulic redesign. To 

account for these shared costs we quantified: 

 Statistics on shared platforms—number of hydraulically identical ESCC/ESFM pump 

models and number of 2-and 4-pole pumps sharing the same model name 

 Allocation of shared redesign costs 

Utilizing the database, and looking at hydraulic performance, the team differentiated those 

pumps with ‘unique’ hydraulic characteristics and those that were ‘duplicates’ of other pumps. 

To determine the allocation of shared redesign costs we assumed that ‘unique’ pumps were 

always going to bear the full cost of redesign. Accordingly, we assumed that ‘duplicate’ pumps 

would incur some percentage of the redesign costs of the ‘unique’ pumps, not the full cost. 

Next we took the principal cost categories in a redesign—redesign, prototype & initial test; 

pattern, tooling; testing; and, marketing—and estimated what share of the full cost would be born 

for ‘duplicate’ pumps for each principal cost category (handout p.43). The result: the total 

percent of original redesign cost attributed to the ‘duplicate’ model for ESCC/ESFM was 59 

percent (weighted average by cost category); for 2/4 pole speed pumps the weighted average was 

68%. Members questioned some of the cost assumptions/allocations, asserting that the testing 

effort would be greater. 

Determining the Per-Model Cost Adjustment: ESCC/ESFM (handout p.44, p.230) 

This methodology is to address the overlap between pumps that are end suction closed-coupled, 

two-pole and four-pole. Starting with the number of failing models at each efficiency level, you 

can separate unique models and duplicate models. Then determine the percentage of unique 

models that have a unique 2/4 pole design versus those with a duplicate 2/4 pole design. 

Multiply those percentages to obtain the population having the cost of a unique closedcouple/frame mounted design and a unique speed design. Dan described a similar calculation for 

duplicate models. 

Continuing, he showed the population of pumps that fall into each category. And there is cost 

sharing among the categories. Dan continued, “your first bucket is unique model costs, unique 

models, 100 percent. So they get 100 percent of the cost. Your next bucket is models that have 

duplicate speed only. That's 68 percent of the cost. The next one is duplicate type only. It's 59 

percent of the cost. And then you get to the pumps that are double duplicates. And here I simply 

multiplied 68 percent by 59 percent to get 40 percent and applied those to a small percentage that 

are representing duplicates on both speed and type. You take the sum of the product, so multiply 

this and multiply this and multiply this. You add them up. You get a weighted average. And 

right now it's 75 percent. That will go up a little bit with the adjustments. But what that 75 

percent means is that you can say that of all the models that are going to be redesigned, you 

apply 75 percent of the cost that we had discussed earlier or you could take 75 percent of the 

models times a full cost. It will get you the same thing. But it's to account for the sharing in 

costs between similar architectures (p.232).” Dan presented a similar methodology for Inline 

pumps (handout p.45). 
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A member mentioned that a manufacturer might to do a redesign for reasons other than 

efficiency gain. Continuing, he indicated that all this content was a lot to process; and, the 

presentation format made it seem like ‘one-way’ communication. He wanted some assurance 

that manufacturers would have the opportunity to provide feedback. Lucas Adin indicated that 

was exactly what the analysis team hoped to achieve. 

Aggregate Industry Conversion Cost (handout p.46, p.246) 

Dan provided an overview: we determined the cost per model to hydraulically redesign. Then 

we came up with cost-sharing factors, that will give us the adjusted costs. The results: for end 

suction, its 75 percent of the original cost. For Inline, its 94 percent. We determined the number 

of models that are hydraulically redesigned. You multiply those out to obtain the aggregate 

conversion costs to the industry as a whole. 

Dan presented two charts (handout p.47), one of which showed total conversion costs to the 

industry by pump type and efficiency level; another showed the total conversion costs as a 

percentage of revenue by efficiency level. 

Summary of Preceding Slide Presentation (handout p.48, p.252) 

Dan concluded this segment with a summary: 

 The proceeding analysis clearly indicated that the conversion costs significantly outweigh 

any of those costs associated with polishing pumps 

 As such, those polishing costs are not going to impact the analysis as it stands. 

 Only hydraulic redesign costs will be passed on to the LCC and downstream analysis. 

Market-Based Approach to Modeling the Base Case MPC, MSP and Cost-Efficiency 

Relationship (handout p.50, p.254) 

Presenting, Dan continued, that the approach is to use market-based data to model the base case. 

He clarified that the analysis team was using source data obtained directly from the 

manufacturers and described the data elements (handout p.51). Key points: 

 In order to model the MSP over the full range of products offered by all manufacturers, a 

scaling parameter must be chosen. 

 The efficiency relationship has already been determined to be a factor of flow and 

specific speed, so it makes sense to work with these parameters 

 To reduce complexity, normalizing factors were chosen: specific speed/ flow (Ns/Q) and 

motor speed base RPM of 1800. 

 Taking the log of this factor and shifting it by one unit on the X-axis allows for easy 

power series regression (log[(Ns/Q x (n/1800] + 1) (handout p.52). 

You model the pump cost without the motor, as follows (handout p.55): 

 Calculate the per-unit manufacturer selling price for each model and divide total revenues 

by total units. Then estimate the actual motor cost for each model in the data base. The 

analysts use manufacturer-specific cost curves for each to estimate the actual motor cost. 

This is compared to the data we collected in the manufacturer interviews. 

 To create an adjusted motor cost we consider account markup and the percent of pumps 

not sold with motors. Multiply baseline motor cost by manufacturer-specific markup. 
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Multiply marked-up motor cost by manufacturer-specific percent of shipments sold with 

motors, to account for some pumps not being sold with motors. 

 Find the pump-only MSP by subtracting the adjusted motor cost from the per-unit MSP. 

Average the pump-only over discrete ranges of the scaling parameter. 

 Regress on these average pump-only MSP in each range 

Dan continued describing the results of the modeled pump costs without the motor. “Inline MSP 

model results, two and four-pole were evaluated together in one population because we needed 

to keep the population of data points larger. They should be fairly similar in their costs. And the 

scaling factor corrects to represent physical size....and the population average for all pumps was 

$1,383 (referring to handout p.58). Pump-only MSP, average cost per model, vertical inline. 

Here you have your scaling factor, your secondary axis, .5 horsepower, 2.2 horsepower, 13 

horsepower, 75 horsepower, 180 horsepower. This 75 horsepower is about $2,000 before a 

motor. This 2.2 is about $900 before a motor. You can see the curve. You can fit regression to 

it pretty strongly.” 

Evaluating the Effectiveness of the Model: Inline Results Pump without Motor (handout p.59) 

We can evaluate the performance of the MSP model by seeing how well the model predicts 

MSP, on average, for all 287 models that had shipments. The results show an average percent 

error for all models was .5% and the average actual cost error was $12. Dan clarified that the 

team had 287 models in the cost model—pumps with shipments. The model, using a scatterplot, then visually re-created the sample manufacturer per-unit MSP data. 

Dan then described the same methodology applied to end-suction pumps (handout p.62). 

One additional conclusion from the data was that the manufacturer’s production cost really does 

not change appreciably with efficiency. A member, offering an additional interpretation said, 

“given the current state of the market,... [the market] may not value a difference between an 82 

percent pump and an 84 percent pump in certain applications.” 

Baseline Cost-Efficiency Relationship (handout p.65) 

Based on industry research, the analysis team has found: 

 MPC does not change appreciably with efficiency; hydraulic design is the prime factor in 

determining a pump’s efficiency; hydraulic design does not appreciably affect the 

material and labor cost 

 For individual manufacturers, MSP does not change with efficiency—they do not carry 

tiered product lines or target higher markups for specific higher efficiency models 

 Many other design factors significantly influence MPC and MSP—durability, reliability, 

etc. 

 A cost-efficiency relationship may exist in the overall market if a manufacturer’s pricing 

correlates to their relative efficiency in the market 

Finding and Applying the Baseline Cost-Efficiency Relationship (handout p.66). 

The cost model developed on the previous slides represented the average per-model MSP of a 

pump at a given log. We can evaluate each pump to see how much more or less than the average 

it costs. We can then look to see if there is a relationship between an MSP premium and 
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efficiency. Efficiency is represented by a pump’s failing PER C-value. As a result, we can 

group shipments by C-value ranges (efficiency) and see how the price premium varies. 

Dan displayed two graphs showing the results for Inline Pumps (handout p.68). The graphs 

displayed a cost premium ranging from 10 percent to -30 percent. The conclusions: 

 For the really inefficient pumps, their cost was much lower than the median 

 Moving to a mid-range of efficiencies, the prices flatten out 

 There was not much of price premium at higher efficiencies (p.276) 

 General conclusion, there is a very weak cost-efficiency relationship 

Several members commented on the conclusions: 

 these are very competitive markets and the market does not value efficiency—even 

though there has been industry consolidation 

 “getting pricing in this market is extremely difficult;” 

 conversion costs can be high and industry needs some way to recoup those conversion 

costs in a timely way. 

A member reminded the WG that these results were the reason to do standards, “we have learned 

that customers probably won't pay extra and aren't interested in a few additional points of 

efficiency. Manufacturers, because of the investment required, probably aren't going to 

voluntarily change their product lines to get a few additional points of efficiency. Yet, there's a 

public good associated with the energy savings that would result from that improvement. Yes, 

recovering the cost of this conversion is subject to competitive forces, but if everybody in the 

industry has to incur those costs, then it seems reasonable that competition would support the 

commensurate increase because everyone is faced with the same circumstance.” 

 

ESCC/ECFM Costs Versus Efficiency (handout p.71) 

Dan stated that End Suction available data were not suitable for the previous cost-efficiency 

analysis. The Inline pump cost-efficiency results were mapped to the end suction population—

they are similar in construction and market & pricing dynamics should be similar. Expecting 

that the curve shapes would be the same, the team found through C-value comparisons that end 

suction pumps on average are more efficient. Summarizing (handout p.74): 

 The bottom 20-30% of models show a strong MSP versus efficiency relationship, with 

less efficient models costing less 

 Beyond this, the cost-efficiency relationship is flat, with more efficient pumps costing no 

more than less efficient pumps 

 MPC is independent of efficiency: in the standards case, the new markups will be applied 

to an MPC model that is identical to the baseline model that was just derived—this 

creates the cost-efficiency relationship for the standards case. 

 Because the standards case will rely on changes in markups rather than changes in MPC, 

the markups in the base case will be different from the markups in the standards case. 

This differs from the usual rulemaking process, but is necessary given the structure of the 

pump industry. 

Pricing and Markups (handout p.76, p.297) 
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Returning from its afternoon break, the WG began on pricing and markups. Chris Lau presented 

the standards case’s basic premise: that it is likely that after standards go into place, MSPs will 

change—and that will depend on manufacturer’s conversion costs and manufacturer’s ability to 

pass on costs through their sales chains. He clarified that MSP is MPC times the manufacturer 

markup. The analysis will determine manufacturer markup scenarios that reflect the industry’s 

ability to pass on the conversion costs. Markup is MSP divided by MPC. 

The process is to establish two scenarios, a lower bound and an upper bound. For the lower 

bound it would be something that is a minimal cost recovery. It will reflect a manufacturer's 

inability to raise prices due to market factors. And it would result in sort of minimal change in 

end user pricing. At the upper bound, what we would like to see is something that actually 

represents higher cost recovery, reflects an increasing ability for manufacturers to pass on costs 

and increase their selling price. And it would likely be whatever represents the highest change in 

end-user pricing. 

 

We might call the lower bound minimum cost recovery or flat markup. In other words, -- and 

this is very low -- it would be whatever you are selling it today, that's what you sell at after the 

standard. That indicates you have no ability to pass on costs to your customers. At the upper 

bound, we don't know where we're going to go yet. We have heard two possible options to date. 

One is that manufacturers when they upgrade equipment, when they upgrade designs, when they 

do these redesigns, they spread out the costs over all of their existing models so that no single 

model increases dramatically in price. We don't know if that is realistic. We would love to hear 

feedback on it. The other option is the conversion costs recovered over just the redesigned units. 

So if you have 20 models out of 50 that get redesigned, then those 20 models would see some 

sort of increase in markup and a resultant increase in selling price. 

 

A manufacturer commented that “the marketplace is not going to let you do that. I mean, if you 

try to recover all that cost on that model, then you won't sell any because your competitor is just 

not going to let you do that.” He continued, “we’re going to be lucky to hit your lower bound.” 

Another manufacturer described several features that make the pumps marketplace extremely 

competitive. 

Chris continued, the key drivers are MPC, conversion costs, baseline markups and baseline MSP. 

We consider the total conversion costs, the annual payment and the additional revenue the 

industry will have to make to recover that conversion cost. We treat this as annuity payments. 

We figure out what that annual amount is. We divide that by annual shipments to figure out how 

much they're going to have to increase the cost per unit per year. And we add that additional 

cost to the base case MSP. So baseline MSP plus the increased cost divided by MPC is your 

revised markup. These are to say, how much more are you going to have to charge your 

customers to make your conversion costs back? 

He described the estimated industry average baseline markup (handout p.82) and upper bound 

scenarios (handout p.83), noting that standards markup increases as the PER increases because 

conversion costs are going up. The chart also showed the new projected MSP and percent 

increase. Responding to a question, Chris said the time period in the analysis to recover the 

conversion costs for the industry as a whole was 30 years. 
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A manufacturer remarked that he had been in the business 40 years and had never seen a 12 

percent price increase in the span of that 40 years. Another manufacturer inquired about the 

practicalities when, for example, the investment in new tooling would only last 10 years. 

Another manufacturer questioned the overall expense/conversion costs when most companies are 

looking for a two-year payback on investments. There was a lengthy back and forth exchange 

among several members related to the limits on pricing and cost recovery. 

Life Cycle Cost Analysis (LCC) (handout p.85, p.321) 

Alison Williams began by referencing a specific LCC scenario to illustrate some early results, as 

follows: 

 Industry recovered 100% of the required conversion cost over 30 years with a discount 

rate of 10.15% 

 This results in the annual value of additional revenue that must be brought in. This value 

is distributed across shipments of pumps that failed to meet the standard 

 A percentage increase is applied to the base MSP for each shipment of failed model. 

 Results: both Inline and End Suction showed percentage increases from PER-10 through 

PER-85 ranging from 12% to 33% 

Katie Coughlin began presenting on LCC with markups on MSP (p.324). The baseline markup is 

the markup on the baseline unit full price. And the incremental markup is the markup on the 

change in price that is due to the standard. The analysis tries to identify the distribution 

channels, figure out how the various parties make their profit in that business, and assemble that 

incremental markup. She described four distribution channels:  

 From the OEM to the distributor and then to the end user, which is the bulk of the 

shipments 

 OEM to OEM to end user, with an intermediary manufacturing step where the pump goes 

into something that someone sells 

 Direct to end user, only a couple of percent 

 OEM to contractors, also a relatively small part of the market.

Responding to a request for information, a manufacturer added that a contractor is frequently 

hired to do installation. A member suggested it might be productive to consider differences or a 

potential split between the new pumps and the replacement market. 

Continuing, Katie described the team’s preliminary figures for baseline markups as 1.5 and 

incremental markups as 1.24. 

Energy Use Calculation (p.335) 

The energy use calculation is an attempt to understand the way products are used in the field—to 

try to get a good estimate of what the actual value of the energy savings might be to the pump 

user. This means trying to characterize the operating conditions and represent the actual energy 

use, in a somewhat simplified manner, so that we can come up with a reasonable estimate of the 

benefit side of an efficiency standard. The actual calculation is to take the pump shaft power, 

theoretically at each hour, and just calculate the energy input—multiply by hours per year, and 

then that gives you annual energy consumption. We are including motor losses in the energy 
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calculation, because this is to be consistent with the consumer perspective. They're paying 

electricity for the whole setup. And we're using in this calculation the methodology outlined in 

the test procedure. And in general, as the test procedure evolves, the energy use calculation is 

very likely to continue to try to be consistent with the test procedure. 

Continuing, we have very limited information on load profiles. As a result, we have created a 

kind of average annual load profile based on percentiles—the fraction of time while the unit is 

running that expands at a given load point. And we're only using 4 load points currently: 50 

percent, 75 percent, 100 percent, and 110 percent of the nominal duty point. So we have an 

hours per year figure at each load point. The power is the pump power at that load point. And 

then we are adding in the motor losses into the overall energy consumption. At this point we're 

not considering that variable loads would be met with a variable speed drive. We're just looking 

at throttling. So everything is calculated on the pump curve. And we will do a subgroup 

analysis for those consumers that are using variable speed drives to see if that would severely 

impact their energy savings. 

A member asked about accounting for mis-sized pumps. Katie described how a ‘BEP offset’ 

calculation accounts for this (p.338). She also mentioned that, for now, the analysts were 

ignoring impeller trimming. A member commented that around one-half of pumps have their 

impellers trimmed, so some adjustment is necessary. Another member contributed that the 

analysis should find a way to consider power factor. Katie noted the need to describe the actual 

distribution of pump duty points and cited the team’s data sources. The team uses manufacturer 

shipment data to determine the actual distribution of pump sizes to compensate for deficiencies 

in two of the data sources. 

Katie also described the scenario-type methodology used to compensate for the lack of load 

profiles (p.350). A member commented that the load profiles should reflect the different rate 

schedules and use profiles as seen in different uses between the commercial and industrial 

sectors. Regarding operating hours, Katie described a consultant report which provides a 

distribution of operating hours by application. Summarizing, the energy use segment she said 

“once you've got operating hours, you have got a duty point, you have got a pump curve, and you 

have got this offset that tells you how far away you are from BEP, you just plug in this equation 

for energy use for the pump....flow times head divided by efficiency. And that gives you the 

annual energy consumption.” 

A member commented that “...as far as where the equipment tends to operate relative to duty 

point, I think it's fairly well-known that pumps generally operate to the left of the BEP point, the 

duty point, as opposed to beyond the BEP point...or duty point.” 

At the close of Day 1, the WG raised issues to be discussed on Day 2. Regarding metrics, Lucas 

Adin referenced criteria, presented previously, that DOE uses to assess whether a particular 

metric is appropriate. Sarah Widder, summarizing, said “I think there are two main issues. Do 

we capture the performance of motors and controls or do we just stick to the pump, bare shaft 

pump, and do we weight the load points or do we analyze them and compare them individually 

against some standard? Al Huber stated that his caucus needed to understand if “you have to 

have one metric?” Continuing, he stated “what we had in mind is one metric for the pump, 
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which is basically the MEI/PER, whatever you what to call it. I mean, we're very close on that, 

whether you average the three or whether you do the other....they call that fixed load.” He 

proposed additional refinements for both the numerator and the denominator, reiterated their 

desire for two metrics and keeping the same as the European construct. 

Lucas and the analysis team described topics for Day 2, including the LCC analysis and 

continuing to zero-in on the metric. The facilitator raised the issue of the outstanding workload 

compared to time scheduled to complete the work and queued that for discussion on Day 2. On 

the subject of making progress, a member stated that “once the LCC analysis results are laid side 

by side with the manufacturer impact, then it's time for us to get together and talk because no 

amount of analysis is going to figure out what the actual forecast of either of those is going to be 

long-term.” Alison stated that the analysis team hoped, in addition to having revised LCC 

analysis, to have the shipments national impact analysis and manufacturer impact analysis (MIA) 

done by the WG’s May meeting. 

Al Huber added that the manufacturers caucus “totally disagreed” with some the assumptions 

presented in the engineering analysis. He wanted to go back through and discuss them. Lucas 

agreed that was a very high priority. Day 1 recessed at 5PM.