3.2.1 Pre-project study and analysis expenses
3.2.2 Main equipment
3.2.3 Equipment installation
3.2.4 Piping (installed)
3.2.5 Instrumentation and control
3.2.6 Electrical installation
3.2.7 Construction (including services)
3.2.8 Auxiliary services
3.2.9 Land
3.3 Estimate of Fixed Investment
3.3.1 Estimate of the cost of equipment and installations
3.3.2 Methods of estimating fixed investment
3.3.3 Level of accuracy in estimation by factors
3.4 Investment
Costs for Fishing Vessels
3.5
Investment Costs for Fish Containers
3.6 Investment in
Fish Plants
3.7 Working Capital
3.7.1 Stock of raw materials
3.7.2 Products being manufactured
3.7.3 Semi-finished or test products
3.7.4 Finished products
3.7.5 Stock of spare-parts and operational materials-in stores
3.7.6 Cash
3.7.7 Outstanding bills or credit to buyers
3.7.8 Credit from suppliers
3.8 Estimating Working Capital
When analysing a project to build a new fish processing plant, expanding or renovating an old one, or changing an existing process or line, the primary and most important decision regards the various investment possibilities and, eventually, deciding whether or not to invest.
Decisions on investments are based on the profit and sustainability of the technical alternative chosen and on the capital available or borrowed. Variables affecting profit and sustainability are manifold and usually fall into three general interrelated groups: market, investment and costs.
Market analysis will help to establish the probable amount of fishery products to be sold, and this information will help determine the minimum plant capacity. In turn, plant capacity is directly related to investment and this influences the cost of production. As a general principle, all feasibility studies are based on an early market survey which will provide the answers to the following questions:
How much can be sold? (With a minimum of 5 years projection from the anticipated start-up date of industrial activities)
At what price should the product be sold?
The capacity of the project can be determined from the above and studies can then be undertaken which will allow a decision to be made on whether or not to invest. In the case of existing plants, investment analysis is necessary to determine the fixed costs of each product; in turn, knowledge of the capital costs of the main equipment is useful in technical and economic studies of repairs and/or replacements.
The total amount of money necessary to put a project into operation is known as "Capital investment costs". This investment can be made through in-house capital, credit from national and international financing agencies, and from suppliers. The total capital required to complete and operate the project is composed of two parts:
FIXED CAPITAL (IF) which is the amount of money necessary to completely construct a processing plant with auxiliary services, and to bring it to the point of start-up production. It is basically the total value of all the assets of the plant.
Fixed assets can be tangible or intangible. Tangible assets comprise machinery (including the cost of assembly), buildings, auxiliary installations, etc., and the intangible assets include patents, technical knowledge, administration expenses, operation, start-up costs, etc.
WORKING CAPITAL (Iw) which includes the capital resources necessary for the plant to operate at the levels forecasted in the technical and economic studies, once it has been installed and normal operations begin.
The amount of this capital varies within very wide limits, depending on the market for which the products are intended, the characteristics of the process and the conditions established by the source and availability of raw materials.
Fixed capital is usually divided into the following components:
A. Direct Costs | B. Indirect Costs |
|
|
Each of these components can be estimated separately, and its magnitude will vary considerably according to the nature of the project. These components of fixed investment are briefly described below.
A. Direct Costs
Preliminary economic studies are usually performed before deciding on or supporting construction of a project; these include investigative travel, market surveys, laboratory and pilot plant studies, etc. However, the procedure for charging these costs varies from project to project.
In the case of public utility projects, for example, the Government does not usually add these expenditures to the total costs of the project and regards them as unrecoverable promotion costs. All the resources assigned to a project must be considered as part of its cost, including those incurred at the research stage and pre-project costs.
In some cases, the pro-forma invoices of the equipment only include their intrinsic value, and in others, the value of the equipment after installation. Where it includes the value of the installed equipment, components (2) and (3) can be calculated together and include all complementary installations. Where equipment or materials have to be imported, details will be given in terms of FOB (equipment price at port of origin), CIF (price including freight and insurance) and at the utilization site (import expenses, freight, etc.).
The equipment and machinery used during the assembly and which can be used in the production process must also be included. The value can be found by depreciating the goods according to use, incorporating only the resulting residual value (see the concept of depreciation and residual value in Chapter 4).
If this component is dealt with separately, provision must be included for installation of imported equipment. The cost of installation will often include payment of qualified expatriate personnel. This is convenient for the experience that the personnel of the supplier company should have, and because, in many cases, equipment suppliers will only honour their guarantees if the equipment is assembled, adjusted and started-up by their own personnel or by technicians authorized by them.
When no other values are available, 20% of total equipment cost may be used in order to estimate installation cost.
In many estimating methods, this component is calculated separately from the rest of the equipment. In a detailed estimate, calculation of the cost of pipes is made with a diagram of the pipes and their siting. Piping costs can vary greatly in the fishery industry, from low to relatively high values.
Piping in the fishery industry is utilized, for instance, for the purpose of conducting water (fresh and sea water), brine, refrigerants (e.g., ammonia), compressed air, sewage and liquid effluents, hydraulic fish transport, steam, edible oils, sauces and special gases (e.g., CO2 or mixtures for MAP - modified atmosphere packaging).
This component includes all auxiliary equipment and instruments for controlling and recording the different variables at each stage of the process; it will increase with the application of HACCP and HACCP-based methods in the fishery industry.
The costs involved in electrical installations consist mainly of labour and materials necessary for supplying power and lighting to the process, while the costs for illuminating the service buildings are normally included in the cost of auxiliary services.
Cost of construction includes the expenditure on labour, materials, and supplies needed for the construction of all buildings connected to the plant. They include plumbing costs, electrical installation, ventilation, air conditioning, and similar building services. The cost of constructing a fish plant usually varies according to the country and the site of the plant.
Table 3.1 shows international values for the cost of construction according to country and type of process. When no other data are available building requirements can be estimated at 150 m2 per ton of raw material daily processed.
Table 3.1 Cost of Construction of Fish Plants
Type |
US$/m2 |
Country |
References |
Fish Plants | 200-250 |
Argentina |
|
100-150 |
Brazil |
Vaaland & Piyarat, 1982 | |
Building for Freezing |
97.8 |
Tropical Countries |
Street et al., 1980 |
Buildings for fish production first category, with offices, buildings for storage sinks, etc. |
250-350 |
UK |
Myers, 1984 |
Construction with sinks and a few offices |
150-250 |
UK Myers, 1984 |
|
Sheds and other types of open simple buildings |
100-150 |
UK Myers, 1984 |
|
Dry processing, building |
75 |
African Countries |
Waterman, 1977 |
Canning building |
80-100 |
Indonesia |
Bromiley et al., 1973 |
Type, Capacity |
US$ '000 |
Country |
References |
Fish plants | Tropical Countries |
Shaw, 1976 |
|
1-5 t raw material/day |
30-60 |
||
6-20 t raw material/day |
40-90 |
||
21-50 t raw material/day |
65-190 |
||
51-100 t raw material/day |
100-240 |
The accepted definition for auxiliary services for a process are the structures, equipment and services not directly involved in the process. Normally, these include equipment for the supply of steam, water, electricity, compressed air and fuel. Some of these services can be bought from other companies, in which case they are considered part of production costs and are not included in investment calculations. Waste disposal equipment, fire extinguishers, cafeteria, etc., are also usually included in the cost for services.
The cost of the land depends on its location and can vary by a 30-50% cost factor between a rural area and a highly industrialized one. The value of land does not decrease with time and is therefore not included in fixed investment when annual cost of depreciation is calculated. Although land does involve capital investment, it is usually preferred to include in fixed capital only those items for which depreciation is allowed by law, thus excluding land. In average, land costs for industrial plants amount to 4-8% of the purchased equipment cost or 1-2% of total capital investment (Peters and, Timmerhaus, 1978).
The part of the investment which is used for land improvement includes the cost of materials for fences, levelling of the land, roads, parking, and other similar costs.
There is a period between formal completion of construction and commencement of normal production, "starting-up", and which can last from a few weeks to several months. Obviously, a series of costs are incurred during this period. They can be divided into two main groups.
Construction costs during starting-up (loss on production lines and equipment, flaws in design to be solved, malfunction of equipment, need for additional equipment, etc.)
Starting-up operational costs (salaries, raw materials, semi-finished or finished products falling outside specifications, etc.)
While the first are always included as fixed capital and as such, depreciate during the plant's useful life, there is no single criterion for the second. Depending on the accounting philosophy of the business, they can also be capitalized, or considered abnormal operational costs and charged to the losses component. Although in this last instance they are not considered in the economic evaluation of the project. However, the general tendency is to reduce starting-up costs as much as possible, by prevention at design stage.
Generally, two situations can be established: a) when the capital required for the development of the project is one's own, or b) when some of the funds come from external sources (bank credit). In the latter instance, the interest is compounded from the moment the credit is received until the completion of construction. This interest will be added to the loan, and the total will make up the investment component.
B. Indirect Costs
These expenses include not only payment for the technical and administrative services required to guide and administer the project during construction, but also all the engineering work and blue prints necessary to prepare final construction plans and specifications in order to bid for or contract various jobs or equipment.
These expenses are necessary for the smooth running of plant construction. They normally include field engineering (inspection, location of equipment, etc.) supplies, construction equipment, and temporary services.
These vary according to the situation and can be nil when the same firm is in charge of construction and setting-up of the project.
This component covers unforeseen incidents. The amount varies and depends on the precision of the estimate.
Estimating the cost of a project can vary from a quick estimate to a carefully prepared detailed calculation using a complete flow chart, with specifications, depending on how much is known about the product and how much time and effort are available for the estimate.
There is a large amount of literature on the cost of equipment and construction of plants. This literature is valuable for the process engineer, but must be used wisely (as in the majority of cases the data on costs are published without any explanation of from where they were derived). Two factors must be taken into consideration:
Equipment Cost Indexes - Time
Cost Factor - Capacity
A problem usually to be faced by whoever does the estimate is that the available information on the cost of similar equipment or plants, is usually out-of-date, and has to be adjusted following changes in economic conditions over time. This updating can be done through the use of the cost indexes.
A cost index is a number showing the ratio between the price of goods at time 't' and the price of the same at time 't base'. If a specific date can be given for a past price, present cost can be determined according to the following formula:
Current cost = Original cost x Current index / Index at time of original cost (3.1)
Cost indexes can be used to make a general estimate, but none takes account of all the factors, such as specific technological advances or local conditions. The most common indices allow for a more precise estimate if the period involved is less than 10 years. Many types of indexes are published regularly. Some can be used for the estimation of costs, others are applied specifically to manpower and specific areas such as construction, materials, etc. For instance, in Argentina, the most accessible indexes are those published by:
INDEC: Instituto Nacional de Estadistíca
y Censos (National Statistics and Census Institute)
Cost of Construction
Consumer Price Index
Non-agricultural Wholesaler Price Index
Cámara Argentina de la Construcción (Argentine Board of Construction)
Fundación Atlántica (Atlantic Foundation): Price Indexes of Inputs for the Fisheries Sector
Redes-Letter (Redes Magazine)
There are also external publications which contain equipment indexes, such as those published periodically in Chemical Engineering for Processing Equipment (Marshall & Stevens Indexes) and materials, now renamed Marshall and Swift Index. A complete description of these indexes can be found in Stevens (1947).
Other indexes are the Engineering-News Record Indexes for construction, the Nelson Index for refinery construction, etc. Similar indexes may be found in most countries. However, one of the current difficulties in developing countries is the scarcity or complete lack of reliable indexes.
Reliable cost indexes give an indication of the degree of development of a country. In most developed countries some indexes are up-dated precisely even daily or at least weekly. However, in others up-dating is done monthly, yearly or not done at all. In extreme situations, usually compounded by lack of statistics (e.g., fish landings), investment, particularly large investment, becomes very cumbersome and risky.
If indexes are not available, it is advisable to take values and indexes from the country where most of the equipment will be imported.
In general, costs do not rise in strict proportion to size. Nevertheless, the costs of a plant or equipment can be estimated when data are available for a similar project, but of different capacity to the one desired, utilizing the following relationship:
I2 = I1 x (Q2 / Q1)x (3.2)
where:
I2 = investment desired for capacity Q2
I1 = known investment for capacity Q1
The exponent x in the equation (3.2) is known as the cost-capacity factor (Chilton, 1950). Its average value tends to be 0.6 and for this reason, the relationship is also known as the six-tenths factor rule. However, 0.6 is an average value and its range varies from values lower than 0.2 to more than 1.0.
Tables giving values of this factor, for chemical plants and equipment, can be found in the literature (Happel, 1958; Bauman, 1964). If the total cost is plotted against capacity on a log-log graph, a straight line will be obtained with a slope equal to cost-capacity factor. However, this does not always happen, and curves might be obtained which show the presence of two or more cost-capacity factors, each covering a certain range and providing better results than an overall average factor.
Regarding the fishery industries some values of coefficient x are listed in Table 3.2, and examples of correlations, related to equipment, are shown in Figures 3.1, 3.2 and 3.3, other equipment costs are listed in Appendix C1 (Zugarramurdi, 1981a).
Table 3.2 Cost-capacity Factors for Equipment in Fish Plants
Equipment |
Range |
Cost-capacity Factor |
Basic Size |
Basic Cost (Year) |
Rapid Evaporating |
||||
Condensers |
80 000-320 000 |
0.57 |
140 000 kcal/h |
US$ 5 000 (1989) |
Evaporators |
12 000-24 000 |
0.67 |
12 000 kcal/h |
US$ 3 000 (1989) |
Plate |
|
|
|
|
Freezers |
10-18 t/day |
0.31 |
18 t/day |
US$ 28 000 (1989) |
Liquid |
|
|
|
|
Freezers |
2-8 t/h |
0.869 |
8 t/h |
US$ 702 600 (1984) |
Continuous |
||||
Spiral Freezer |
0.5-1.5 t/h |
0.514 |
1.5 t/h |
US$ 272 220 (1984) |
Single Belt |
||||
Continuous |
||||
Freezer |
0.2-0.6 t/h |
0.583 |
0.6 t/h |
US$ 130 560 (1984) |
Vertical |
|
|
|
|
Freezer |
53-14 t/day |
0.13 |
14 t/day |
US$ 23 250 (1984) |
Blast |
||||
Freezers |
5-20 t/day |
0.31 |
5 t/day |
US$ 10 000 (1989) |
Cold |
||||
Stores |
500-10 000 m3 |
0.628 |
2 000 m3 |
US$60 000 (1984) |
(stowage rate: 10 m3/t) |
||||
Flake Ice |
|
|
|
|
Machines |
20-30 t/day |
0.38 |
20 t/day |
US$18 000 (1989) |
Bone Separator |
||||
Baader |
1 100-3 500 lb/h |
0.65 |
1100 lb/h |
DM 50 000 (1990) |
Bibun |
4 000-5 700 lb/h |
1 |
4000 lb/h |
US$ 16 000 (1977) |
Paoli |
400-2 200 lb/h |
0.69 |
1100 lb/h |
US$14 800 (1977) |
Figure 3.1 Cost vs Capacity for Quick Evaporating Condensers (part of refrigeration equipment)
Figure 3.2 Cost vs Capacity for Evaporators (part of refrigeration equipment)
Figure 3.3 Cost vs Capacity for Fish Bone Separator
The value of the cost-capacity factor for refrigeration equipment, in freezing plants with capacities of 10-100 t/day is 0.795, while that for processing equipment is 0.868. In Argentina, the range is very wide, given that when mechanized plants increase capacity, the amount of equipment increases, while the manual plants increase their refrigeration equipment.
Regarding coefficients for whole plants, cost-capacity factors for different types of fish plants, in both developing and developed countries, are given in Table 3.3.
Evidently, there are substantial differences depending on the location of the plant and the processing technology, but it can be concluded that for fish plants (with the exception of fishmeal plants) a 0.85 factor, such as that proposed for solid processing plants, is adequate (Wilson, 1978), while the cost-capacity factor for fishmeal plants is about 0.6.
Table 3.3 Cost-capacity Factors for Fish Plants
Type of plant |
Range (t/day) |
Capacity factor |
Size (t/day) |
Basic cost |
Country |
Calculated from |
Canneries |
8-35(°) |
0.89 |
11.3 |
1 100 |
Argentina |
(Cerbini & Zugarramurdi, 1981a) |
Freezing |
10-100(°) |
0. 6-0.81* |
20 |
2500 |
" |
(Zugarramurdi & Parin, 1988) |
Average for other |
||||||
Food Freezing Plants(°) |
|
0.875 |
20 |
3 270 |
Several countries |
(Parin et al, 1990) |
Ice Plants |
||||||
Flake |
2-200(°) |
0.895 |
50 |
420 |
UK |
(From Myers, 1984) |
Tube |
10-200(°) |
0.646 |
50 |
460 |
" |
" |
Plate |
2-200(°) |
0.960 |
50 |
400 |
" |
" |
Fishmeal Plants |
||||||
20-100(') |
0.5 |
66.7 |
806 |
Brazil |
(From Vaaland & Piyarat, 1982) |
|
0.459 |
n/a |
n/a |
Canada |
(From Mensinkai, 1967) |
||
2-200(') |
0.5 |
20 |
400 |
Tropical Countries |
(From Shaw, 1976) |
|
without concentration of stickwater | 15-30(') |
0.60 |
25 |
235 |
Europe |
(From Atlas, 1975) |
with concentration of stickwater |
60-250(') |
0.618 |
60 |
455 |
Europe |
" |
FPC, Biological |
50-1000(') |
0.585 |
50 |
1 350 |
USA |
(From Almenas, 1972) |
FPC, Alcohol extraction** |
50-1 000(') |
0.502 |
50 |
1 570 |
USA |
" |
20-68(') |
0.477 |
68 |
1 757 |
Senegal |
(From Vaaland & Piyarat,1982) |
*t product
't raw material
*(0-100% according to the degree of mechanization)
**Isopropyl alcohol
Total fixed capital can be calculated from the current sale price of the product and the annual capacity of the plant (Woods, 1975). Fixed investment is calculated as follows:
I = V × Q / W (3.3)
where:
I = Investment
V = Sale price per unit produced
Q = Annual capacity of the plant, expressed in the same units of production as V
W = Universal Factor
Table 3.4 shows the values for W. For the application of this method, sale prices and range of capacities in the fishery industry are given in Table 3.5.
Table 3.4 Universal Factor Values
General Application |
1.0 |
Processes where main costs are raw materials or manpower |
1.4 |
Range |
0.2- 8.0 |
Table 3.5 Average Values of V and Q in the Fishery Industry
Product |
Sale Price per unit (V) |
Range of Q (1) |
Country |
References |
Fresh sole |
US$ 1 9281/t |
914 t/year |
USA |
(Georgianna & Hopn, 1986) |
Frozen hake |
US$ 1 470/t |
5-20 (t/day) |
Argentina |
(1990) This work |
(Skinned, boneless fillet block) |
||||
Frozen sardines |
US$ 0.46/kg |
30 t/day |
Indonesia |
(Haywood & Curr, 1987) |
Frozen fillet |
US$ 2 874/t |
3 000 t/year |
Senegal |
(Jarrold & Everett, 1978) |
Argentinean sardines in oil, 170 g can |
US$ 0.6-0.7/can |
15- 1 00x 103 cans/day |
Argentina |
(1989) This work |
Canned sardines |
US$ 0.46/kg |
120 t/day |
Indonesia |
(Haywood & Curr, 1987) |
Canned tuna |
US$ 2 704/t |
5 500 t/year |
Senegal |
(Jarrold & Everett, 1978) |
Salted anchovy |
(t/season) |
|||
drums x 200 kg |
US$ 1.3-2.0/ka |
40-4000 |
Argentina |
(1989) This work |
Fishmeal |
US$ 0.1/kg |
1 200 t fish/year |
Indonesia |
(Haywood & Curr, 1987) |
Fishmeal |
US$ 312/t |
25 000 t/year |
Senegal |
(Jarrold & Everett, 1978) |
Note: (1) In the same units as V
The value of this method is its simplicity. This advantage is lost if the analyst tries to find in the list of values for W that which corresponds to the particular case in mind. Thus, the term 'Universal Factor' is used since the W factor is supposed to be applicable to any process. In its favour is the little time it takes to make the estimate (5 minutes) but there is a very wide uncertainty range in the result (between -70% and +200%).
This technique is frequently used to estimate the order of magnitude of investment. It establishes that the costs of an industrial plant can be obtained by multiplying the costs of the basic equipment by a factor (Jelen and Black, 1983). Two factors are used: one to estimate fixed investment and the other to estimate total investment. Average values of these factors can also be found in the literature. Application is very simple:
Estimated investment = fL x (Cost of basic equipment)
This method is used when little or no information is available on design. It is a preliminary approximation (±20-30%). The method was first applied in the chemical industry and the general factors for this type of industry are presented in Table 3.6.
Table 3.6 fL Factors to Estimate IF and IT for Chemical Plants (after Arnold and Chilton, 1963)
Type of Plant |
fL for IF |
fL for IT |
Solid processing |
3.9 |
4.6 |
Solid-liquid processing |
4.1 |
4.9 |
Liquid processing |
4.8 |
5.7 |
For fish processing plants, 1. and IT factors calculated from published data are given in Table 3.7 for artisanal fish processing and in Table 3.8 for industrial fish processing.
Table 3.7 Average fL Factor to Estimate IF for Artisanal Fish Processing
Type of Process |
Average Factor |
Canning |
2.485 |
Freezing |
2.6 |
Dry and dry salting |
2.43 |
Fishmeal and biological fish silage |
2.265 |
A marked difference is observed in Tables 3.6, 3.7 and 3.8 between the factors used for fish plants and chemical plants. This is probably due to a larger auxiliary infrastructure in chemical plants, not often existing in food factories.
On the other hand, mechanized plants in industrialized countries, with a high proportion of equipment costs, show a factor which is substantially lower for the same type of process. It is also noted that this difference is not compensated for by lower construction costs in developing countries (see Table 3. 1).
Table 3.8 fL Factors to Estimate IF and IT for Fish Processing Plants
Type of Plant |
Fish Plants |
Country |
Data calculated |
|
fL for IF |
fL for IT |
|||
Canning, Manual |
2.5 |
3.1 |
Argentina |
|
" |
2.47 |
2.97 |
Indonesia |
(From Haywood & Curr, 1987) |
Mechanical |
2.05 |
Norway |
(From Myrseth, 1985) |
|
Freezing |
2.6 |
3.3 |
Argentina |
(Parin et al, 1990) |
Manual |
2.29 |
Tropical Countries |
(From Street et al., 1980) |
|
Manual, shrimp |
2.93 |
UK |
(From Graham, 1984) |
|
Mechanical, shrimp |
2.11 |
USA |
(From Bartholomai, 1987) |
|
Mechanical, catfish |
2.31 |
USA |
" |
|
Dry Salting |
2.2 |
Brazil |
(From Vaaland & Piyarat, 1982) |
|
2.67 |
African Countries |
(From Waternian, 1977) |
||
FPC |
1.64 |
Senegal |
(From Vaaland & Piyarat, 1982) |
|
1.59 |
USA |
(From Almenas, 1972) | ||
2.89 |
Brazil |
(From Vaaland & Piyarat, 1982) |
Using this method, it is possible to extrapolate the cost of a complete system from the cost of the main equipment of the process (Chilton, 1949); and to produce an estimate of the total fixed investment within an error of 10-15% of actual value, if appropriate factors are used. It is advisable to adjust the experimental factors pooling results from different and successive cases.
The data for this method can be used in developing cost equations in order to optimize stages of a particular process. The starting point of this method is the estimation of the investment of main equipment of the process, which will be called IE. It can be observed that the costs of other essential items needed to complete the system can be correlated with investment in main equipment and that total investment can be estimated by applying experimental factors to the basic investment IE.
The equation (3.4) is thus obtained, in which the experimental factors f, are obtained from a study of various similar processes.
where:
IF = Fixed investment for the entire system
IE = Costs of main equipment once installed
fi = Multiplication factors for estimation of direct costs, such as piping, instrumentation, buildings, etc.
fIi Multiplication factors for estimating indirect costs, such as engineering fees, contractors, contingencies, etc.
Table 3.9 presents typical data compiled from analysis of existing chemical processes (Rudd and Watson, 1968), along with calculated values for fish plants. It is interesting to observe that investment in main equipment can be as low as a half, a third or sometimes a quarter of total investment, depending on the nature of the process. When the auxiliary services have a general and continuous use in other processes within an industrial complex, an internal price based on the quantities to be consumed is generally charged to the project.
When this quantity cannot be accurately measured, a factor is included, usually an annual fee, proportional to IF. At the other extreme is the case of the plant totally isolated from any industrial complex ("grassroots") which must provide all its auxiliary services and whose investment is included in IF.
It is emphasized that, due to the enormous costs involved in supplying auxiliary services, linking up with state terminals, loading and unloading terminals, transport and other necessary services in a completely undeveloped site, the total fixed investment necessary for a new plant located in a remote area, can be almost 100% greater than that of a plant built near to an already existing one.
Figure 3.4 shows the relationship between the fixed investment for chemical and petrochemical plants compared with food processing plants (Parin and Zugarrainurdi, 1994). Clearly, for a particular capacity of production, there is a difference in the order of magnitude between both types of plants.
Table 3.9 Factors Required to Estimate Total Investment in Fish Plants
Cost of Installed Processing Equipment |
||
Experimental Factors as a percentage of IE |
fi |
Data calculated from |
1 Piping for the process |
||
Chemical plants (solid process) |
0.07-0.10 |
(Rudd & Watson, 1968) |
Canning, Argentina |
0.03 |
|
Freezing, Argentina |
0.05 |
(Parin et al., 1990) |
Shrimp, USA |
0.056 |
(Bartholomai, 1987) |
Catfish, USA |
0.023 |
" |
Salting and Dry-salting, Argentina |
0.01 |
|
Fishmeal, Argentina |
0.05 |
|
2. Instrumentation |
||
Chemical plants (little automation) |
0.02-0.05 |
(Rudd & Watson, 1968) |
Canning, Argentina |
0.01 |
|
Freezing, Argentina |
0.03 |
(Parin et al., 1990) |
Salting and Dry-salting, Argentina |
0 |
|
Fishmeal, Argentina |
0.01 |
|
3. Structures, Buildings |
||
Chemical Plants (open structure) |
0.05-0.2 |
(Rudd & Watson, 1968) |
(half open structure) |
0.2-0.6 |
" |
(closed structure) |
0.6-1.0 |
" |
Canning, Argentina |
0.6 |
|
Norway |
0.63 |
(Myrseth, 1985) |
Tuna, Indonesia |
0.607 |
(Bromiley et al., 1973) |
Tropical Countries |
0.43 | (Edwards et al., 1981) |
Freezing, Argentina |
0.6 |
(Parin et al., 1990) |
Tropical Countries |
0.43 |
(Street et al., 1980) |
Shrimp, USA |
0.88 |
(Bartholomai, 1987) |
Catfish, USA |
0.76 |
|
UK |
0.49 |
(Graham, 1984) |
Salting, Argentina |
0.6 |
|
Drying, African Countries |
0.71 |
(Waterman, 1977) |
Brazil |
0.4 |
(Vaaland & Piyarat, 1982) |
Fishmeal, Argentina |
0.5 |
|
FPC, USA |
0.1 |
(Almenas, 1972) |
Senegal |
0.44 |
(Vaaland & Piyarat, 1982) |
Brazil |
0.4 |
|
Total Physical Cost |
||
Average direct cost factors for, |
||
Canning |
1.61 |
|
Salting and Dry-salting |
1.57 |
|
Fishmeal |
1.51 |
|
Freezing |
1.69 |
|
(*) see section 3.2.3 |
||
Engineering and Construction |
||
Chemical plants |
0.2-0.35 |
|
Fish plants, Argentina |
0.1 |
|
Tropical Countries |
0.1 |
(Edwards et al., 1981) |
Size Factor |
||
Small commercial unit, chemical plants |
0.05-0.15 |
|
Fish plants, canning, Argentina |
0.1 |
|
freezing, Argentina |
0.1 |
|
Contingencies |
||
Chemical plants |
0.1-0.2 |
|
Fish plants, Argentina |
0.1 |
|
Tropical countries |
0.1 |
(Edwards et al., 1981) |
Indirect Cost Factors |
||
Average indirect cost factor |
1.3 |
|
Total Fixed Investment |
||
Total experimental factors |
fT | |
Canning |
2.51 |
|
Freezing |
2.63 |
|
Salting and Dry-salting |
2.45 |
|
Fishmeal |
2.36 |
Figure 3.4 Investment for Chemical and Food Plants
Ref.: 1. Sardines, canned (Norway); 2. Lemons, packaging (CA, USA); 3. Sardines, canned (Argentina); 4. Green peas, canned (CA, USA); 5. Lima beans, canned (CA, USA); 6. Pears, production (CA,USA); 7. Green peas, frozen (CA, USA); 8. Lima beans, frozen (CA,USA); 9. Frozen spinach (CA, USA); 10 Polyethylene (USA); 11. Alkylation (USA); 12. Acetic acid (USA); 13. Ammonia (USA); 14.Methanol (USA); 15. Reforming (USA); 16 Nitric acid (USA); 17. Cracking (USA); 18. Ammonium Nitrate (USA); 19. Polymerization (USA).
Note: bbl (US barrel) = 0.119 m3
Errors in these methods are mainly due to: factors of scale, the extension to cases different from those from which the factors used were estimated, and variation of the relationship between equipment and plant costs according to equipment maker and equipment quality. Precautions must be taken with respect to errors introduced in the use of factor methods.
These errors include that of trying to correlate costs using a single independent variable (a correlation error), that of presenting the data by a simple exponential relationship (linear correlation error), that of not considering technological or learning behaviour in the correlations, and that of special circumstances. Each will be analysed separately.
A compromise between simplicity and accuracy is sought. In general, the independent variable which may minimize the error is selected. However, this simplification can introduce significant errors.
In Figure 3.3, cost data for bone separators are presented as the most significant independent variable which, in this case, is processing capacity per hour. The difference between the curves shows the difficulty of presenting costs by a simple correlation and the error involved in such simplification. This difficulty is aggravated when comparing data from various manufacturers and for a greater number than used in the example.
The second type of error is due to the attempt to correlate the data in a simple exponential form, such as in equation (3.3), and in the approximation done by the freezing plants in Figures 3.5 (Zugarramurdi and Parin, 1988) and 3.6 (Cerbini and Zugarramurdi, 1981b).
Figure 3.5 Investment vs Plant Capacity for Frozen Fish Plants with Different Levels of Mechanization
Figure 3.6 Relationship between Investment and Capacity for Mechanical Fish Filleting and Freezing Plants
"Tails" or extremes of production capacity are not usually correlated. They are taken as the maximum and minimum sizes of equipment or plants for usual production techniques. In this case, the "tails" are replaced by size restrictions. An increase in capacity over this maximum is obtained by duplicating the plant or equipment.
For equipment smaller than the minimum size, only the minimum size is obtained subject to appropriate modifications. In Figure 3.7, for canning plants, it is observed that the investment values for the smallest plants deviate from the estimate line, indicating that sizes smaller than the minimum cannot be extrapolated without introducing significant errors (Parin and Zugarramurdi, 1987).
Figure 3.7 Fixed Investment vs Canning Plant Capacity
The third type of error concerns technological advances. When new methods of manufacturing or constructing equipment are developed, the "old" correlations are usually discarded. Given that many correlations are updated by inflation indices, care must be taken that the correlation refers to current manufacturing techniques. The error of special circumstances occurs since correlations can be based on a manufacturer's price list, on a company's actual purchase price, or a mixture of the two.
The actual sale price depends on these factors (on a supply and demand basis), i.e., how anxious the manufacturer is to sell the equipment and the previous business relationship between manufacturer and buyer. In the fishery industry there is also the possibility of purchasing suitable second-hand equipment (adjusted and/or refitted) which allows for a reduced investment; however, estimations in such cases, based on factors presented in Tables 3.7 and 3.91, will yield investment overestimates. The error will depend on the quantity of second-hand equipment utilized. Exchange rates, industry promotion policies and type of technology may also distort the correlations.
Some equipment (e.g., ice plants) may be cheaper if produced in a developing country (e.g., Argentina, Brazil, China, India). This cannot be generalized as the situation will change with time (and the same equipment becomes more expensive). The best advice is to use the methods presented here as starting points and refine the estimate according to local conditions.
A fishery is a system composed of different activities such as capture, processing and marketing of fish, which operates within certain socio-economic and political contexts and which interacts with other sectors of the economy. In accordance with the characteristics discussed in the Introduction, two major economic groups are considered: small-scale artisanal fisheries and large-scale industrial fisheries. Table 3. 10 gives cost values for fishing vessels in artisanal as well as industrial fisheries. The values in Table 3. 10 were plotted on the graph in Figure 3.8, and a cost-capacity factor of 0.65 was obtained for vessels.
Figure 3.8 Investment Costs for Fishing Vessels
Table 3.10 Investment Costs for Fishing Vessels
Type |
Size |
Cost |
Country |
References |
||
Length(m) |
HP |
t |
(US$ 1000) |
|||
Coastal boats |
18.5-21 |
380 |
40 |
200-250 |
Argentina |
(Parin et al., 1990) |
Trawler |
33 |
500 |
182 |
500 |
Argentina |
(Otrera et al., 1986) |
Canoe (without motor) |
10 |
- |
0.075 |
1.9 |
Senegal |
(Jarrold & Everett, 1978) |
Canoe (without motor) |
4-5 |
- |
0.020 |
0.163-0.285 |
Paraguay |
(FAO, 1991) |
Canoe (with motor) |
14 |
20 |
3 |
19.15 |
Senegal |
(Jarrold & Everett, 1978) |
Purse Seiners |
20 |
300 |
15 |
355.2 |
" |
" |
Trawler |
40 |
1 000 |
50 |
2220 |
" |
" |
Factory Ships |
50 |
1 700 |
540 |
4400 |
" |
" |
Tuna Purse Seiners |
55 |
1 800 |
175 |
6216 |
" |
" |
Catamaran, |
||||||
for sardine |
3-4 |
- |
0.009 |
0.230 |
India |
(Kurien & Willmann, 1982) |
for shrimp |
3-4 |
- |
0.008 |
0.210 |
" |
" |
for anchovy |
5-6 |
- |
0.009 |
0.230 |
" |
" |
Canoe |
7-15 |
- |
0.173 |
0.972 |
India |
" |
Boats |
12 |
100-125 |
- |
23 |
Bangladesh |
(Eddie & Nathan, 1980) |
12 |
22 |
- |
5 |
" |
" |
|
Large trawlers |
- |
- |
100-600 |
120-595 |
Peru |
(Engstrom et al., 1974) |
Purse Seiners |
13 |
20 |
- |
35.65 |
Indonesia |
(Haywood & Curr, 1987) |
13.72 |
102 |
34.1 |
108 |
India |
" |
|
20.5 |
220 |
12.6 |
111 |
Thailand |
" |
|
22 |
300 |
8.1 |
194.3 |
Morocco |
" |
|
Schooner (standard) |
- |
37 |
1.1 |
33 |
Seychelles |
(Parker, 1989) |
Schooner(special) |
- |
56 |
2 |
67 |
" |
" |
Schooner (new design) |
11.6 |
70 |
2 |
72 |
Seychelles |
" |
Boats/RSW* |
13.26 |
15-20 |
- |
76.2 |
India |
(Nordheine & Teutscher, 1980) |
- |
35 |
- |
267 |
India |
" |
*Refrigerated Sea Water
Small-scale artisanal fisheries generally operates in coastal marine waters in developing countries, the majority of which are located in tropical latitudes (Stevenson et al., 1982). Small-scale fisheries are characterized by a variety of fishing gear and vessels. The fishing techniques are usually labour-intensive and the types of gear used are diverse and relatively economical to operate.
The greatest determining factor for costs is the combination of boat/gear used. The magnitude of the different costs for any of these fishing combinations depends on duration of trip, distance to the fishing area, etc. Small-scale fisheries exploit many species, using a variety of boats, gear and manpower. These different fishing units or types of business have different effects on the resources, just as in their economic operation. The effective effort that each exercises on a particular species is different, as is the average size of fish that each catches.
This analysis does not assume to exhaust the subject of investment on fishing vessels which would merit a separate manual (like aquaculture and mariculture), but merely indicates that the techniques of economic engineering can also be applied to fishing vessels and gears.
The authors are also aware that in practice,
within a company, separation of fishing and processing operations
may not be as sharp as when the same subjects are analysed from
an academic or administrative point of view. Fish technologists
must also be aware of this.
Containers are used to handle and transport fish and other fish resources from the time of catch, storage and processing, to their consumption. In many countries, the handling of fish without adequate containers causes deterioration of 20-30% of the fish. Fresh fish loses its quality easily, and thus appropriate containers are needed to prevent contamination, physical damage and spoilage.
There is a great variety of sizes, design and construction of fish containers used throughout the world. Construction materials depend on fishing technique, vessel size, level of organization in the industry, value of catch, and very often, local tradition. Table 3. 11 shows data on investment costs for fish containers for both artisanal and industrial fisheries.
Table 3.11 Investment Costs for Fish Containers
Type |
Capacity (kg) |
Cost (US$) |
Useful (years) |
Country |
References |
Basket |
25 |
0.94 |
1-2 |
Ghana |
(Essuman & West, 1990) |
Fresh fish: |
|||||
Palm baskets |
20-25 |
0.94 |
6-12 months |
" |
" |
Receptacles carried on the head |
|||||
aluminum |
20-25 |
8.3 |
5-10 |
" |
" |
plastic |
20-25 |
3 |
3-5 |
" |
" |
Dry anchovy: |
|||||
Jute bags |
45-50 |
1.9 |
3-4 |
" |
" |
Polypropylene bag |
20-25 |
0.57 |
3-5 |
" |
" |
Wooden boxes |
16 |
4.2 |
n/a |
Norway |
(Brox et al., 1984) |
30 |
5.3 |
n/a |
" |
" |
|
Aluminum boxes |
12 |
7 |
n/a |
" |
" |
33 |
25.5 |
n/a |
" |
" |
|
Plastic boxes |
12 |
5.5 |
n/a |
" |
" |
33 |
15.2 |
n/a |
Australia |
||
Insulated containers |
|||||
Insulated container (Metal box 70) |
70 litre |
90 |
n/a |
Denmark |
|
Metallic container (Artisanal) |
144 |
76 |
n/a |
Paraguay |
(FAO, 1991) |
Expanded polystyrene container with wood frame and painted (Artisanal) |
50 litre |
25 |
n/a |
" |
" |
Expanded polystyrene container |
37 litre |
14 |
n/a |
" |
" |
Using the methods described above, it is possible to estimate, with a certain degree of accuracy, the investment necessary for a fish plant, a process line or just a process modification. In fact, the relevant literature contains no detailed calculations, but only descriptions of the main equipment and their costs, construction costs, and data on total investment, from which a global cost for other items can be estimated.
Table 3.12 compiles investment costs for fisheries plants in developing and developed. countries. An interpretation of these values will allow conclusions to be drawn.
Table 3.12 Investment Costs for Fish Plants
The values of Table 3.12 are plotted in Figure 3.9. In this graph, it is seen that even when some of the existing plants in developing countries are artisanal, and generally smaller than those in industrialized countries, the relationship between costs and capacities proposed earlier, still applies.
Figure 3.9 Investment Costs of Fish Plants (FP : finished products)
In the case of canning plants, the graphical correlation shows a cost-capacity factor of 0.868 (r = 0.9998), while freezing plants have a factor of 0.825 (r = 0.921). It results that industrial plants of varying sizes operating in different countries (conditions) show a clear correlation between investment and installed capacity, provided the same technology is used. If technology varies, there are two possible situations: when the technology is partly modified (change of one or a few stages of the process); or when the technology used to obtain the same product varies substantially. The former can be seen in Figure 3.5 where data for freezing plants are shown according to mechanical or manual processing. The same data are shown for canning plants in Figure 3.7. The second case is illustrated in Figure 3.9, at point ( ),. using the production of fishmeal at the industrial and artisanal levels.
In practice, there is a minimum limit for industrial production capacity. This limit is set by the minimum capacity of key equipment on the market. It is obvious from Figure 3.9 that the minimum scale of production requires an investment which also correlates with the maximum scales of production. Besides, these results show that minimum sized plants in developing countries, with partially modified technology, are not comparatively less expensive than large capacity plants in developed countries.
The concept of minimum size can be compared to the results of Figure 3.7 and the experience of pilot plants of institutes, in the sense that investment for minimum size plants or plants below minimum size is even greater than that which would correspond to the correlation shown in Figure 3.9. In general, this is due to the need to incorporate one or more oversized (or exceeding minimum scale) pieces of equipment. All these aspects must also be integrated into costs, as will be examined in Chapters 4 and 5.
Working Capital is mainly made up of:
Inventory (raw material, semi-finished products, stock of spare-parts, operational materials)
Cash
Credit to buyers, outstanding bills
Credit from suppliers (when considering this section, bear in mind that its value must be deducted form the rest of the Working Capital).
Logically, the quantity of raw materials that must always be kept in stock depends on many factors, but mainly on:
Its origin, national or imported
Availability, number of suppliers, etc.
In the case of national raw materials, an average value equivalent to 15-30 days production, at factory price, can be included in the working capital. In the case of imported raw materials, an average of 90-120 days production can be included in the working capital. The value for the raw materials will include costs for importation and transport to the factory. The current tendency is to reduce as much as possible the stock of raw materials, final products, package material, spare-parts, etc., since storage increases costs and immobilizes capital. The management technique used in this case is called "just in time".
This component includes the value of raw materials, services, direct manpower needed for factory production. Its magnitude depends basically on the process (continuous or batch).
These are products which still have to go through other production processes, before being placed on the market, or which are still awaiting laboratory approval. Cost can be high in industries where approval of products takes a long time.
Many factors can determine the quantity of a finished product that is kept in storage. Storage of finished products in a freezing factory which only produces fillet blocks will be very different to that of a canning factory which makes a great variety of products. Similarly, there are some products which are consumed in greater quantities during particular periods of the year (for example Easter in Christian countries) while others are consumed regularly throughout the year. In the case of salted fish, the storage of salted products which must pass through a curing process (for example, anchovy), and remain stored for a long period (usually 4-6 months until shipping) are a considerable strain on the working capital, 'which at times, is of the same importance as fixed investment costs. When not dealing with a specific case and when no other data are available, 30 production days are usually taken as average storage time for finished products. As seen in section 3.7.1 the current tendency in the food and fishery industry is to reduce stocks as much as possible following the policy "just in time". The appropriate application of this policy allows for reduction in the stocks of finished material (immobilized capital), reduction in storage room capacity and hence in investment and operation costs (e.g., electricity).
The value of the spare-parts can vary within a very high price range, especially if at the start of operations, a plant could have imported equipment from abroad, which is usually provided with spare-parts for several years' operation. From the point of view of the project, the value of the spare-parts is generally estimated as the equivalent of 1 to 3 months operation, bearing in mind the total yearly amount that has been taken. to calculate the cost of sales. A similar criterion is followed for operational materials, assigning the equivalent of a month's expenditure to working capital, which will be kept permanently in storage.
Cash is the amount of money in hand that must be kept available to ensure plant operation, payment for raw materials, salaries, services, etc. Usually the cash for a project is equivalent to 30 days of the total production costs minus depreciation.
This is usually one of the most important components of working capital. Several factors exercise an influence on the calculation of its volume, but the most important is the credit conditions fixed by the market. Each business has its own policy, which can vary from 30 to 60 to 365 days. On the domestic market, it is usual to provide credit to supermarkets for fishery products; for instance, 30 days are given for canned fish in Argentina.
All the previous components constitute gross working capital. It is advisable not to take into account the possible credit that might be obtained from suppliers. However, it should be considered in financial analyses of the project in order to correct the value. In the case of inputs for fish plants in Argentina, this credit is granted by fish suppliers, with a limit of 15 days for national raw material and 30-90 days for imported raw material.
Various methods can be used to estimate working capital, among which:
Take it as 10-20% of fixed investment. Generally, 10% is used as an acceptable approximate estimate for fish industries when data are lacking.
Take it as 10% of annual sales. Table 3.13 shows average percentages of annual sales for each component, the fraction of the year (decimal) during which working capital is needed, and finally, the average costs of each component as a percentage of the annual sales. It can be observed that the average working capital is approximately 10% of annual sales (Bauman, 1964).
Calculate the inventory costs for one month's capacity of raw material, plus two months' capacity of finished products. Add the accounts receivable calculated on one month's sales (Woods, 1975).
Table 3.13 Calculation of Working Capital
% Annual Sales |
Average Time |
Average Costs as % of annual sales |
|
Current Assets |
|||
Raw Material |
30 |
0.04 |
1.2 |
Finished Product |
60 |
0.08 |
4.8 |
Outstanding Bills |
100 |
0.10 |
10.0 |
Cash in Hand |
1-5 |
1.00 |
2.5 |
Total 18.5 |
|||
Current Liabilities |
|||
Taxes |
8 |
0.60 |
4.80 |
Salaries |
14 |
0.03 |
0.42 |
Services |
4 |
0.10 |
0.40 |
Freight |
2 |
0.01 |
0.02 |
Raw material |
30 |
0.10 |
3.00 |
Total 8.64 |
|||
WORKING CAPITAL: ASSETS - LIABILITIES = 9.86 |
Example 3.1 Calculation of Total Investment for a Frozen Fish Plant
The purpose of examples 3.1 and 3.2 is to explain and give procedures for the practical calculations of capital investment. The described methods can be applied to such different technologies as freezing, canning and fishmeal plants or to plants singly at an already industrialized site, or to such different sizes as pilot plant and high-capacity units, whenever the reader should follow, understand and use the information properly. The indications of price, both for equipment and for materials, are only estimates, and a supplier whose working conditions are established will be the best source of information on this point. The reader should adapt the approach to the specific problem. Cost data vary with the date, equipment size, plant location, manufacturers' design, materials of construction, the process involved and other factors.
Appendix C1 is intended only as a guide for estimates and represent values for the sizes listed in the year indicated in the source. The six-tenths factor may be employed for general approximations at other capacities, but the user is warned that these may lead to considerable possible error. Experience and judgment can reduce the error, but accurate costs can only be obtained from manufacturers. The methods applied in the examples are not the only ones to be found in the bibliography, and the reader might be interested in looking further into other more accurate and therefore more sophisticated models. Some cases may require more detailed models. In connection with the use of published cost data, it should be emphasized that they are satisfactory only for approximate cost estimations. Where a more accurate figure is- desired, it is necessary to obtain quotations from manufacturers for the specific piece of equipment required.
1) Calculate the fixed investment for the frozen hake plant in Example 2.1 by the following methods:
Lang method
Multiple-factor method
Cost-capacity factor for complete plant
2) Estimate working capital
3) Calculate total investment, excluding land
Answers:
1) Table 3.14 shows the main equipment (From Example 2. 1) and their delivered costs. The purchased cost of each piece of equipment (quotations from suppliers, 1991) is used to calculate fixed investment (refrigeration system not included at this stage). The term purchased equipment or delivered equipment refers to the cost of the non installed equipment delivered to the construction site. The 1. value can be compared with the estimate made through the correlation proposed by Zugarrainurdi and Parin (1988):
Major Equipment Investment in Manual Plants (Without refrigeration system) = US$ 59 485 x Q0.51 = US$ 84 709
Table 3.14 Cost of Primary Equipment
Equipment Item |
Quantity |
Delivered Cost (US$) |
Whole fish weighing machine |
2000 |
|
Whole fish Washer |
13000 |
|
Sorting Table (*) |
2 |
400 |
Filleting Table (*)(**) |
16 |
3200 |
Inspection and Trimming Table (*) |
5 |
3000 |
Fillet Packing Table (*) (w/conveyor belt) |
3 |
2700 |
Fish Block Weighing Table w/scale |
1 |
3600 |
Tray remover |
1200 |
|
Final Packing Table (*) |
3250 |
|
Strapping Machine |
5800 |
|
Conveyor Belts |
2500 |
|
Tray Washer |
14000 |
|
Box Washer |
20000 |
|
Plastic boxes, 35 kg fish each |
40 |
4000 |
Freezing Trays |
200 |
6400 |
Fork-lift truck |
6000 |
|
Total delivered cost of major equipment items IE |
91050 |
(*) Stainless steel
(**) The number of filleting posts calculated in Example 2.13 is 15. However, filleting tables have an even number of posts, therefore 16 posts instead of 15 is used.
The difference between the two estimates is due to changes in the prices of equipment and inaccuracies since the plant capacity deviates from the valid range (10-100 t of finished product per day). From the requirements given in Example 2. L, the freezing requirements must be calculated. Table 3.2 gives the data for applying Equation 3.2 to estimate the plate freezer and the cold store.
I plate freezer = US$ 28 000 x (2/18)0.31 = US$ 14 200
I cold store = US$ 60 000 x (60/200)0.62 = US$ 28 500
I blast freezer = US$ 10 000
Appendix C1 provides cost data for a given capacity; when no cost-capacity factor is available, the six-tenth rule can be applied.
I chill room = US$ 10 000 x (20/10)0.6 = US$ 15 200
Plate Freezer, 500 kg/load 14 200 Chill Room, 0°C, capacity: 20t 15 200 Cold Store -30°C, capacity:60 t 28 500 Blast Freezer, capacity: 5 t 10 000 Refrigeration equipment (compressors, evaporators, etc.) for production of 2 t of frozen fish blocks/day (from supplier) 70 000 US$
137 900
Investment in Major Equipment = US$ 91 050 + US$ 137 900 = US$ 228 950
Using the appropriate Lang factor (From
Table 3.7),
Fixed Investment = US$ 228 950 x 2.6 = US$ 595 270
With the multiple-factor method, each
factor has a range of values and the professional must
rely on pastexperience to decide, in each case, whether
to use a high, average, or low figure. Table 3.15 shows
this calculation.
Results obtained using this procedure have shown high
correlation with fixed-capital investment estimates that
have been obtained with more detailed techniques.
Properly used, these factoring method can yield quick
fixed-capital investment requirements with accuracies
sufficient for most economic-evaluationpurposes.
According to Table 3.3 and Equation (3.2):
IF =US$ 2 500 000 x (2/20)0.6 = US$
627 970
This value is relatively larger than the other estimates,
because 2 t fall outside the valid capacity range for the
cost-capacity factor given in Table 3.3. It will be
considered that fixed investment amounts US$ 600 000,
excluding land.
Iw = 10% IF (From
Section 3.8 a)
Iw = 0. 1 x US$ 600 000 = US$ 60 000
IT = IF + Iw
IT = 600 000 + 60 000 = US$ 660 000
Table 3.15 Use of Factors from Table 3.9 for Capital Cost Estimation (Frozen Fish)
Item |
Multiplying factor |
Cost of item (US$) |
Delivered equipment cost |
1.00 |
228950 |
Installed equipment cost |
0.20 |
45790 |
IE |
274740 |
|
Experimental Factors as a percentage of IE |
fi |
|
Process piping |
0.05 |
13740 |
Instrumentation |
0.03 |
8240 |
Buildings |
0.60 |
164840 |
0.68 |
186820 |
|
Total Physical Cost, |
|
461560 |
Experimental Factors as Percentage of Total Physical Cost |
fIi |
|
Engineering |
0.10 |
46 160 |
Size Facto |
0.10 |
46 160 |
Contingencies |
0.10 |
46 160 |
Total Indirect Cost, |
0.30 |
138480 |
Total Fixed Investment, |
600040 |
Example 3.2 Calculation of Total Investment for a Fish Canning Plant
1) Calculate the fixed investment for the canned tuna plant in Example 2.2 using the following methods:
Lang method
Multiple-factor method
Compare with values for canning plants in Table 3.12
By cost-capacity factor in Table 3.3
2) Estimate working capital
3) Calculate total investment
Answers:
1) The first step is to calculate the cost of the primary equipment. Table 3.16 shows the development of the estimate; the main equipment (from Example 2.2) and their delivered costs. The purchased cost of each piece of equipment were estimated from other similar plants in Cape Verde.
Table 3.16 Cost of Primary Equipment
Equipment Item |
Quantity |
Delivered Cost (US$) |
Reception, crane |
1 |
2000 |
Weighing, 0.5 t scale |
1 |
1700 |
Washing, 2 000 1 tank |
1 |
300 |
Heading and gutting, large table with saw |
1 |
4500 |
Washing, tank |
1 |
300 |
Cutting, large table with saw |
1 |
4500 |
Washing, tank |
1 |
300 |
Placing on trays, large table |
1 |
200 |
Tray capacity, 40 kg each |
20 |
200 |
Crane and two tray carriers |
1 |
1900 |
Cooking, insulated container |
1 |
1128 |
Cleaning of cooked fish, large table for two workers |
400 |
|
Packaging, large table |
1 |
200 |
Filling with oil and seal, seamer: 10 cans/min |
1 |
6900 |
Sterilization, retort: 700 cans/load |
1 |
16000 |
Labelling, large table |
1 |
100 |
Boiler, 250 kg steam/h |
1 |
8900 |
Total delivered cost of major equipment items |
I equipment |
49528 |
Using the appropriate Lang Factor (From
Table 3.8)
Fixed Investment = US$ 50 000 x 2.485 = US$ 124 250
Using the multiple-factor method, each factor has a range of values and the professional must rely on pastexperience to decide, in each case, whether to use a high, average, or low figure. Table 3.17 shows the development of the estimate.
From the data given in Table 3.12, fixed capital investment for a manual canning plant to elaborate 1.25 tfinished product/day located in tropical countries, is US$ 170 000. This value is about 30% higher than the total fixed investment calculated previously.
Data from Table 3.12 should be used only in absence of more specific information.
Table 3.17 Use of Factors from Table 3.9 for Capital Cost Estimation (Canned Fish)
Item |
Multiplying factor |
Cost of item (US$) |
Delivered equipment cost |
1.00 |
50000 |
Installed equipment cost |
0.20 |
10000 |
IE |
60000 |
|
Experimental Factors as a percentage of IE |
fi |
|
Process piping |
0.03 |
1800 |
Instrumentation |
0.01 |
600 |
Buildings |
0.60 |
36000 |
0.64 |
38400 |
|
Total Physical Cost, |
98400 |
|
Total Direct Cost |
100000 |
|
Experimental Factors as Percentage of Total Physical Cost |
fIi |
|
Engineering |
0.10 |
10000 |
Size Facto |
0.10 |
10000 |
Contingencies |
0.10 |
10000 |
Total Indirect Cost, |
0.30 |
30000 |
Total Fixed Investment, |
130000 |
(*) The cost of buildings can also be estimated according to Myrseth (1985), taking into account that: 20 t of raw material require 4 000 m2 and the construction cost is US$ 200/m2. In this case,. for 1 t of raw material 200 m2 will be required and the cost will be US$ 40 000. This value is comparable with the US$ 36 000 obtained in Table 3.17. This means that the two total estimates will be US$ 98 400 and US$ 102 400. It will be considered an average of US$ 100 000 for direct costs.
It should be noted that the capacity
interval for the application of the cost-capacity factor,
is 8-35 t/day.
However, this estimate can be used to obtain the order of
magnitude of the investment required.
According to Table 3.3 and Equation (3.2):
IF = US$ 1 100 000 x (1/11.3)0.89 =
US$ 127 000
It will be considered that fixed investment amounts US$
130 000, excluding land.
Iw 10% IF (from
Section 3.8 a)
Iw = 0. 1 x US$ 130 000 = US$ 13 000
IT = IF + Iw
IT = 130 000 + 13 000 = US$ 143 000