CE Cost File _

Estimating Piping CostsFrom Process Flowsheets

After reviewing the existing methods for making preliminary piping-cost estimates, the

author introduces a simple, flowsheet-based method that offers major advant~ges.

~

chased cost of major process equipment; their results '-..are:

Process Material, % Labor, % Pipi~g Total, %Solids 8 6 litSolids-fluids 21 15 35\Fluids 49 37 85\

Chilton5, similarly, gives the fo11o~ng pipirg'costsas a percentage of insta11ed process equipment cost:

Solids 7 to 10% \Solids-fluids 10 to 30%Fluids 30 to 60%

Haselbarth and Berk6 distinguish between \sma11and large insta11ations by indicating the fo11oringinsta11ed piping costs as a percentage of total plant

cost: \Range, % Average, \%

&~ \SmaIl (under $10 million) 2 to 8 4·Large (abovc $10 million) 2 to 9 5 l

Solids-fluids \

SmaIl 9 to 15 10Large 8 to 16 12 .

Fluids ~.Small 8 to 20 15 \ \

Large 8 to 25 16 \\N elson 7 shows installed piping costs for refinery

plants as a percentage of major equipment material ;and labor cost: 1-

Catalytic cracking 52% ~

Thermal cracking 31 \Gas cracking 43Ethylene , 46

Gasoline plants 39 to 46 '\Modern refinery 53 to 61

Miller8 lists piping costs as a percentage of main "plant items by classifying the processes as shown \in the tabtrlation below. ("Main plant items" repre­sent a11 the usual major items of equipment thatwould be indicated on a flowsheet, down to andincluding pumps.)

E. S. SDKULLU, Sun Dil Co.

Basica11y, there are two types of piping-cost esti­mates:

1. Itemized. These. are detailed estimates madeon the basis of finaland complete design; they re­quire piping drawings where the exact amount andspecifications of piping can be found. Material andlabor costs, as we11 as cost of auxiliaries,can thusbe estimated in detail. These details are vital to acontractor, but their estimation is genera11y impracti­cal,at' the process engineering stage.

2. Quick and Approximate. These estimates, whichdo not rely on the nuts-and-bolts details of a process,are needed to guide the development of a conceptualsystem where such details do not yet existo They musttherefore be based on gross features and majorvariables. 1

This Cost File will quickly review methods usedfor the quick approximate estimates, and present anew, more precise method that is based on processflowsheets. The method integrates a11 types of proc­esses into one formula, and for the first time permitsthe estimation of incremental piping costs in caseof piping modification to a given process.

The "Percent 01 Total Equipment" Approach

In the two types of quick-estimale methods cur­rently in use in process engineering,2 piping costs arecalculated as a percentage of either the total equip­mentcosts, or of the subclasses of equipment. Letus start by considering the first general type.

Lang's3 results give piping costs as a percentage ofthe insta11ed cost of process equipment:

Solid processing plants: 7.2 to 7.6, averaging 7.4%Solids-fluidsplants: 14 to 35, averaging 25 %Fluids processing plants; 21 to 66, averaging 50 %

Aries and Newton4 used percentages applied to pur-

The work sel forlh in lhis Cosl File was eondueled in parlial fui.fillmenl for lhe requiremenls of an M.S. degree in ehemical engineer­ing al lhe Universily of Wiseonsin, and eheeked again by lhe informa·lion available al Sun Oil Co.

Average Unit Costs ofMain Plant !tems:

High (gases and liquids, petro-chemicals), % .

Average (liquid chemicals), % .Liquids and solids, % .Low (solids), %

Under$3,000

65-10533-6513-335-13

Over$17,000

25-429-253-90-3

148 FEBRUARY 10, 1969/CHEMICAL ENGINEERING

The original reference contains five unit-cost cate­gories between the $3,000 and $17,000 shown here,so that there are seven categories altogether. (Unitcosts are based on 1958 dollars.) The percentageswithin each category are given as a range, and theprecise selection is left to the estimator's judgment.

The "Percent of Equipment Subclass" Approach

Moving on to the next category, Stoop9 attempts toimprove the accuracy of methods described aboveby usirig the followirig subclasses of equipment:

Piping Cost as % ofEquipment Purchased Cost:

Material Erection Labor TotalTowers 50 40 90Vessels 60 48 108Exchangers 40 40 80Pumps 30 24 54Compressors 20 16 36Heaters 15 12 27

Stoop also gives size adjustment factors plotted onlog-log paper.

Similarly, Hand10 reeommends the percentages asfollows:

Piping Material Cost as %of..Equipment Fob. Costs

Columns (excludingtrays) . 50Heat exchangers 42Vessels 45Pumps 25Compressors 20Furnaces 15InsGruments 32Finally, Hirsch and Glazierll obtained the follow­

ing regression formula:logF,,= -0.266-0.014logAo-0.156 (e/A) +0.556 (P/A)

Where: F" = Cost factor for piping material

A = Fob. cost of basic equipment in dollarsAo = A, in thousands of dollarse = Total heat exchanger costs, in dollars

P = Total pump and driver costs, in dollars

IExisting Methods: Summing Up

From the above review, it is apparent that apiping-cost estimate made by one method can differappreciably from that made by another method.This limited accura~y is due to the approximationson which some of the methods are based. As wehave seen, several attempts were made reeentlyto inerease the aecuracy of such estimates. Miller'sapproach, arid the methods using pereentages Ofsubclasses of equipment, are among sueh attempts.

These attempts have one eommon purpose: tointegrate into the estimation procedure more of thevarüibles that are thought to influenee piping ~ostsin a proeess. This is a legitimate ¡;)ffort,but this effortshould be emphasized on1y up to a point, mainlybeeause:

1. Cost relationships among different pro e­esses are of a statistical nature. As sueh, they re­quire eorreet statistioal sampling and testing. Further­more, data in this area are too heterogeneous anddifficult to get. Therefore, a simple breakdown ofpiping cost percentáges' aeeording to proeess char­acteristics (sueh as size, pressure, severity of cor-

CHEMICAL ENGINEERING/FEBRUARY 10, 1969

rosion, process type, ete.) without careful samplingand correct statistical proeedures, might be mislead­ing.

2. We should not forget that the ultimate goalin this area is a simple but precise estimation pro­eedure taking inta account on1y gross features andmajor variables rather than speeific details.

Proposed: The Use of Process Flowsheets

What makes the differenee in the proportion ofpiping costs between two given proeesses, A and B?Although process Howsheets have never been usedto answer sueh a question, is it not obvious, by look­ing to the Howsheets on Fig. 1, that proeess A willhave a higher proportion of piping cost than proeessB? This commonsense observation is quite accurate,as we will see later; it shows very clearly that How­sheets are a valuable information source: they mal'determine the amount and, therefore, the eost ofpiping in a proeess.

The Piping lndex-An attempt is made here todefine a variable that will show, on the' basis ofHowsheets, how much piping relative to its majorprocess equipment a given proeess has. Let us sal'that

L¡ = Number of lines carrying fiuids between majorprocess equipment. (Lines for solids should onlybe considered if the solids wiil actuaily be carriedby pipes).

M = Number of major process equipment items (exclud­ing instruments and electrical items).

Then, we define our piping index as:1" = L¡/M (1)

For example, based on Fig. 1, we have:1" = 9/3 for process A1" = 5/3 for process B.

Mter defining the piping index, the next stepis to relate this variable to the proportion of pipingcost in a proeess. Fig. 2 giv'es a plot of total piping

Process B: JP=~

-1 ~8tHiJ-(not vio piping)

l.n~

PIPING INDEX, as obtained from flowsl1eet, is 3.0 forfirst process and 1.7 for second-Fig. 1

149

COST FILE .

p%

p=1I x (1p}I.6100

PIPING COSTS show this relationshipto ,index-F,ig. 2

costs (labor and material), as a percent of thepurchased cost of major process equipment, versus thepiping index, based on a sample of 24 prpcesses.

The coefficien,Jof correlation obtained from thescatter diagram in Fig. 2 is r = 0.5. In simplinedlanguage, this means that 50% of the variation ofin percentage piping cost among the 24 processes inour sample can be explained by the variation in pipingin'dex Ip• Compared to other methods reviewed previ­ously, most of which have a éoefficient of correlationaround 0.3 to 0.4, 01' wide ranges on p, this correlationcan be considered relatively high.

Firially, a fun~tion of general form p% = k (Ip)n

is ntted to this scatter diagram by least-squaresmethod,12 The coefficients of this function, resultingfrom the ntting, give the following equation:

P% = 11 X (Ip)1.6 (2)

Where: P = Total piping costs (material and labor) as apercent of purchased cost of major processequipment (excluding instruments and elec­tri cal items) .

1p = Piping index as defined in Eq. (1)

This formula is a useful tool for quick estimationof piping costs in the early phases of process designoAs indicated earlier it is the nrst that integratesall categories of processes (such as solid-solid, solid­fluid, etc.) into one formula, and it constitutes aunique tool for estimating incremental piping costswhen fluid-flow modifications to any given processare being considered.

Fur~herRefinements

In practice, an experienced engineer can obtainbetter results from this formula than is suggestedabove by the computed coefficient of correlation.With the help of additional information such asprocess pressure, se~erity of corrosion, and plant

150

capacity (piping costs as a percentage oí major equip­ment decreases with increasing plant capacity8), theuser can adjust the results given by the formula.

Moreove1~,although there is generally no relation­ship between the physical layout of a plant and itsHowsheet, sometimes it is possible to pinpoint on aHowsheet the lines representing a, pipe longer 01'

shorter than the average. In such cases, longer pipesshould be given a somewhat heavier weight in thedetermination of Ip: for instance, one can count as1 a pipe of average length, as 1.3 a long pipe, andas 0.6 a pipe unusually short. The same kind ofadjustment can also be made in the determination ofM by giving heavier weights to more expensive majarequipment items.

lIIustrative Example

Engineer Jones propases a new variant of a processunder considerationby the company.The new vari­ant would save $15,000 in operating costs. The mainchanges in process are several récycIes that willrequire some additional piping.

Jones' supervisor asks him to quickly estimate thecost of this additional piping in order to justify the.changes.

Since the new variant falls in the same category asthe basic process (such as solid-Huid, large pla~t),Jones cannot quickly estimate the cost of additional ~piping with previously used methods. But the useof piping index can show him that this index is in­creased from 2.3 to 2.7 in the new variant. He can,thus, estimate the incremental cost of additional pip­ing by the use of our new formula:

!'J.p = 11 X (2.7)1.6 - 11 X (2.3)1.6 = 12.3%

If the cost of majar process equipment is $100,GOO,then the piping costs in the new variant will beincreased by 0.123 X 100,000 = $12,300. So, Jonescan indicate to his supervisor that an additional in"vestment of $12,300 in piping is more than justifiedto save $15,000 ayear. '

References

1. Rudd, D. F., 'and Watson, C. C., Strategy in ProcessEngineering," Prelimina,ry Edition.

2. CE Oost File-93, Gl'em. Eng., Sept. 14, 1964, p. 228.3. Lang, R., Chem. Eng., Oct. 1947', p. 117.4. Aries, R S., and Newton, RD., "Chemioal Engineering

Cost Estimation," McGraw-Rill, New York, 1955, p. 78.5. Chilton, C., Chem. Eng., June 1949, p. 106..6. Hasel'harth, J. E.,' Berk, J. M., Chem. Eng., May 16,

1960, p. 158. .7. Nelson, W. L., Gil &; Gas J., Nov. 5, 1956, p. 127.8. Miller, C. A., Chem. Eng., C'E Cost FHe-l05. Sept.

1965.9. Sto'Op, M. L., Ind. Eng. Chem., J,an. 1960, p. 303A.

10. Rand, W. E., Cost Engineer's Notebook, Amer. Assn.'Oost Engrs. Jan. 1964.

11. Rirsch, J. :a., and Glazier, E. M., Chem. Eng. Progr.,Dec. 1964, p, 37. .

12. Hoel, G. P., "Inwoduction to Mathematical statistics,"Wiley, New York, 1965.

Meet the Author

ENGINS. SOKULLUis employed in the Technical Economics Div.of Sun Oil CO.(1608 Walnut St., Philadelphia, Pa. 19103), wherehis assignments involve economic evalu~tion, planning, optimiza­tion and operation analysis via techniques such as linear pro­gramming and' computer simulation. He has M.B.A. and M.S.'Ch.E. degrees from the University of Wisconsin; his earliereducation was obtained in France and Turkéy.

FEBRUARY 10, 1969jCHEMICAL ENGINEERING