Estimating Piping Costs From Process Flow Sheets

CE Cost File

_

Estimating Piping Costs From 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. ~ E. S. SDKULLU, Sun Dil Co.

Basica11y, there are two types of piping-cost estimates: 1. Itemized. These. are detailed estimates made on the basis of finaland complete design; they require piping drawings where the exact amount and specifications of piping can be found. Material and labor costs, as we11 as cost of auxiliaries,can thus be estimated in detail. These details are vital to a contractor, but their estimation is genera11y impractical,at' the process engineering stage. 2. Quick and Approximate. These estimates, which do not rely on the nuts-and-bolts details of a process, are needed to guide the development of a conceptual system where such details do not yet existo They must therefore be based on gross features and major variables. 1 This Cost File will quickly review methods used for the quick approximate estimates, and present a new, more precise method that is based on process flowsheets. The method integrates a11 types of processes into one formula, and for the first time permits the estimation of incremental piping costs in case of 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 are calculated as a percentage of either the total equipmentcosts, or of the subclasses of equipment. Let us start by considering the first general type. Lang's3 results give piping costs as a percentage of the insta11ed cost of process equipment: Solid processing plants: 7.2 to 7.6, averaging 7.4% Solids-fluids plants: 14 to 35, averaging 25 % Fluids processing plants; 21 to 66, averaging 50 % Aries and Newton4 used percentages applied to purThe 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.

148

chased cost of major process equipment; are: Process Material, % Solids 8 Solids-fluids 21 Fluids 49

their results

'-..

Labor, % Pipi~g Total, % 6 lit 15 35\ 37 85\

Chilton5, similarly, gives the fo11o~ng pipirg'costs as a percentage of insta11ed process equipment cost: Solids-fluids Solids Fluids

10 to 30% 7 to 60% 10% 30

\

Haselbarth and Berk6 distinguish between \sma11 and large insta11ations by indicating the fo11oring insta11ed piping costs as a percentage of total plant cost: &~SmaIl (under $10 million) Large (abovc $10 million) SmaIl Large Solids-fluids Fluids Small

\ Range, % Average, \% 2 to 8 4· \ 2 to 9 5

l

9 to 15 8 to 16

10 12

8 to 20

15

\

.

~.

\

\

N elson 7 shows installed piping costs for refinery Large to 25 16 \\ ; plants as a percentage of major 8equipment material 1and labor cost: Catalytic cracking

52%

~

Gas cracking Thermal Ethylene cracking ,

43 31 46

\

Modern refinery 53 to 61 Gasoline plants 39 to 46 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 that would be indicated on a flowsheet, down to and including pumps.) Average Unit Costs of Main Plant !tems:

Under $3,000

High (gases and liquids, petrochemicals), % . 65-105 Average (liquid chemicals), % . 33-65 Liquids and solids, % . 13-33 5-13 Low (solids), % FEBRUARY 10, 1969/CHEMICAL

Over $17,000 25-42 9-25 3-9 0-3

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. (Unit costs are based on 1958 dollars.) The percentages within each category are given as a range, and the precise selection is left to the estimator's judgment.

rosion, process type, ete.) without careful sampling and correct statistical proeedures, might be misleading. 2. We should not forget that the ultimate goal in this area is a simple but precise estimation proeedure taking inta account on1y gross features and major variables rather than speeific details.

The "Percent of Equipment Subclass" Approach Proposed: The Use of Process Flowsheets Moving on to the next category, Stoop9 attempts to improve the accuracy of methods described above by usirig the followirig subclasses of equipment: Piping Cost as % of Equipment Purchased Cost: Material Erection Labor Total Towers 50 40 90 Vessels 60 48 108 Exchangers 40 40 80 Pumps 30 24 54 Compressors 20 16 36 Heaters 15 12 27 Stoop also gives size adjustment factors plotted on log-log paper. Similarly, Hand10 reeommends the percentages as follows: Piping Material Cost as % of..Equipment Fob. Costs Columns (excludingtrays) . 50 Heat exchangers 42 Vessels 45 Pumps 25 Compressors 20 Furnaces 15 InsGruments 32 Finally, Hirsch and Glazierll obtained the following regression formula: logF,,= -0.266-0.014logAo-0.156 (e/A) +0.556 (P/A) Where: F" = Cost factor for piping material A Ao

= = P = e

Fob. of basicofequipment A, in cost thousands dollars in dollars Total heat exchanger costs, in dollars Total pump and driver costs, in dollars

IExisting Methods: Summing Up From the above review, it is apparent that a piping-cost estimate made by one method can differ appreciably from that made by another method. This limited accura~y is due to the approximations on which some of the methods are based. As we have seen, several attempts were made reeently to inerease the aecuracy of such estimates. Miller's approach, arid the methods using pereentages Of subclasses of equipment, are among sueh attempts. These attempts have one eommon purpose: to integrate into the estimation procedure more of the varüibles that are thought to influenee piping ~osts in a proeess. This is a legitimate ¡;)ffort,but this effort should be emphasized on1y up to a point, mainly beeause: 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 and difficult to get. Therefore, a simple breakdown of piping cost percentáges' aeeording to proeess characteristics (sueh as size, pressure, severity of corCHEMICAL ENGINEERING/FEBRUARY 10, 1969

What makes the differenee in the proportion of piping costs between two given proeesses, A and B? Although process Howsheets have never been used to answer sueh a question, is it not obvious, by looking to the Howsheets on Fig. 1, that proeess A will have a higher proportion of piping cost than proeess B? 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 of piping in a proeess. The Piping lndex-An attempt is made here to define a variable that will show, on the' basis of Howsheets, how much piping relative to its major process equipment a given proeess has. Let us sal' that

L¡ = Number of lines carrying fiuids between major

process equipment. (Lines for solids should only be considered if the solids wiil actuaily be carried by 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 A 1" = 5/3 for process B. Mter defining the piping index, the next step is to relate this variable to the proportion of piping cost 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 for first process and 1.7 for second-Fig. 1

149

COST FILE .

capacity (piping costs as a percentage oí major equipment decreases with increasing plant capacity8), the user can adjust the results given by the formula. Moreove1~,although there is generally no relationship between the physical layout of a plant and its Howsheet, sometimes it is possible to pinpoint on a Howsheet the lines representing a, pipe longer 01' shorter than the average. In such cases, longer pipes should be given a somewhat heavier weight in the determination of Ip: for instance, one can count as 1 a pipe of average length, as 1.3 a long pipe, and as 0.6 a pipe unusually short. The same kind of adjustment can also be made in the determination of M by giving heavier weights to more expensive majar equipment items.

p% p=1I

x

(1p}I.6

100

lIIustrative Example

PIPING COSTS

show this relationshipto ,index-F,ig. 2

costs (labor and material), as a percent of the purchased cost of major process equipment, versus the piping index, based on a sample of 24 prpcesses. The coefficien,Jof correlation obtained from the scatter diagram in Fig. 2 is r = 0.5. In simplined language, this means that 50% of the variation of in percentage piping cost among the 24 processes in our sample can be explained by the variation in piping in'dex Ip• Compared to other methods reviewed previously, most of which have a éoefficient of correlation around 0.3 to 0.4, 01' wide ranges on p, this correlation can be considered relatively high. Firially, a fun~tion of general form p% = k (Ip)n is ntted to this scatter diagram by least-squares method,12 The coefficients of this function, resulting from the ntting, give the following equation: P%

=

11 X

(Ip)1.6

(2)

Where: P = Total piping costs (material and labor) as a percent of purchased cost of major process equipment (excluding instruments and electri cal items) .

1p = Piping index as defined in Eq. (1) This formula is a useful tool for quick estimation of piping costs in the early phases of process designo As indicated earlier it is the nrst that integrates all categories of processes (such as solid-solid, solidfluid, etc.) into one formula, and it constitutes a unique tool for estimating incremental piping costs when fluid-flow modifications to any given process are being considered.

Engineer Jones propases a new variant of a process under considerationby the company.The new variant would save $15,000 in operating costs. The main changes in process are several récycIes that will require some additional piping. Jones' supervisor asks him to quickly estimate the cost of this additional piping in order to justify the .changes. Since the new variant falls in the same category as the basic process (such as solid-Huid, large pla~t), Jones cannot quickly estimate the cost of additional ~ piping with previously used methods. But the use of 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 be increased by 0.123 X 100,000 = $12,300. So, Jones can indicate to his supervisor that an additional in" vestment of $12,300 in piping is more than justified to save $15,000 ayear. ' References 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12.

Rudd, D. F., 'and Watson, C. C., Strategy in Process Engineering," Prelimina,ry Edition. CE Oost File-93, Gl'em. Eng., Sept. 14, 1964, p. 228. Lang, R., Chem. Eng., Oct. 1947', p. 117. Aries, R S., and Newton, RD., "Chemioal Engineering Cost Estimation," McGraw-Rill, New York, 1955, p. 78. Chilton, C., Chem. Eng., June 1949, p. 106.. Hasel'harth, J. E.,' Berk, J. M., Chem. Eng., May 16, 1960, p. 158. . Nelson, W. L., Gil &; Gas J., Nov. 5, 1956, p. 127. Miller, C. A., Chem. Eng., C'E Cost FHe-l05. Sept. 1965. Sto'Op, M. L., Ind. Eng. Chem., J,an. 1960, p. 303A. Rand, W. E., Cost Engineer's Notebook, Amer. Assn. 'Oost Engrs. Jan. 1964. Rirsch, J. :a., and Glazier, E. M., Chem. Eng. Progr., Dec. 1964, p, 37. . Hoel, G. P., "Inwoduction to Mathematical statistics," Wiley, New York, 1965.

Fur~her Refinements In practice, an experienced engineer can obtain better results from this formula than is suggested above by the computed coefficient of correlation. With the help of additional information such as process pressure, se~erity of corrosion, and plant 150

Meet the Author ENGINS. SOKULLUis employed in the Technical Economics Div. of Sun Oil CO. (1608 Walnut St., Philadelphia, Pa. 19103), where his assignments

involve economic

evalu~tion,

planning,

optimiza-

tion 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 earlier education was obtained in France and Turkéy. FEBRUARY 10, 1969jCHEMICAL

ENGINEERING