Post on 31-Jan-2023
Indirect Costs in Shipbuilding: a proposal for its appropriation
José Augusto Dunham (UGF)
José Haim Benzecry (UGF)
Marco Antônio Almeida (UGF)
Mauro Rezende Filho (UGF/COPPE)
ABSTRACT
This article introduces some concepts of costing methods, details the development of a
settlement for the shipbuilding industry and provides an application example with its
preliminary results. Due to data sources on resources and time employed are limited, in most
cases the input parameters for the cost of building a ship are estimated. Thus a methodology for
estimating the input parameters of the system based on cost uncertainty is proposed. This
methodology incorporates knowledge about the vagueness and uncertainty of data on costing
systems. Finally, to investigate the activity of the constructive system of the ship and its potential
benefits, an analytical model was developed.
Keywords: absorption costing, cost estimation, uncertainty
1. INTRODUCTION
Traditionally, in shipbuilding, overhead and profit of the shipyard are allocated as a proportion
of the sale price proposed. This may provide distorted information costs since the building
systems of a ship are different in size, complexity, material requirements and / or configuration,
and do not allow to know the profitability of each building system.
Aiming to improve the product and the cost of information production process companies
began to plan costing systems (Drury, 2006). These systems can provide valuable information to
decision makers, investigating business activities, resource consumption and cost drivers. The
development of a costing system involves four main steps:
1) Identify the activities / pool systems and assign costs based on cost factors like, for
example, purchasing, receiving and inspection activities can be assigned to a set of
process costs;
2) Determine the cost of these activities, identifying and assigning resource consumption;
3) Select a driver of cost for each system, for example, the tonnage of steel processed can
be a driver for the appropriation of the cost structure and,
4) To determine the rate of consumption for the various cost drivers.
One of the main obstacles encountered during the development of the costing system is the
analysis of the extensive amount of data collected. Two to four steps listed above in the
development process costing system require the collection of three types of data: costs of
activities that are summed to calculate the total costs of the system, the cost drivers and the
rates of consumption of resources by driver. Collecting information to specify the activities and
assign costs of these activities in a costing system is a costly and involves time. Costing systems
using estimated costs for the collection of information to generate product costs is an expensive
process. Cooper and Kaplan argue that "managers can make good decisions based on
information approximate cost (about 10%)." (COOPER & Kaplan, 1998).
As the data in most cases are estimated, and their values have uncertainty, their estimates tend
to be imprecise. As the vessel is constructed as the actual value of each parameter data is not
known with precision, it is important to incorporate some degree of uncertainty in the system.
The incorporation of uncertainty and imprecision around the input parameters for a costing
system provides the user information for many purposes, such as building systems costing,
pricing, quotation and budget development.
System cost is defined as a method of calculating costs. There are several forms of settlement
that can be mutually used each with their advantages and disadvantages, such as absorption
costing, direct costing or variable, and costing activities (ABC).
The absorption costing makes full ownership of all costs (direct, indirect, fixed and variable)
products / services. Therefore, absorption costing is the method which consists in the
appropriation of all production costs to goods produced, ie, all expenses related to the
manufacturing effort are distributed to all products / services (Martins, 2001).
The direct costing or variable makes the separation of variable costs and fixed costs,
appropriating the goods and services costs, with the variation of its volume of production,
whereas fixed costs are expenses of the period. The direct costing is also called variable costing
or marginal costing, since variable costs, most of which are direct.
The ABC (Activity Based Costing) costing method allows better visualization of costs through the
analysis of activities performed within the company and their relations with the cost objects
(Martins, 2001). The ABC costing is suitable for complex organizations, where products consume
resources unevenly. The principle of this method is to make directly the best possible cost
proportional and non-proportional through cost drivers. The benefits of the ABC method are
many, especially the following (Bruesewitz & Talbott, 1997):
1. improvement in management decisions;
2. facilitates the determination of the relevant costs as it reduces the need for cost
allocation "arbitrary";
3. identifies actions in order to reduce the costs of overheads;
4. provides greater accuracy in product costs;
5. determines the cost of services / products to the extent that identifies the cost of each
activity in relation to the total costs of the entity;
6. supports benchmarking;
7. determines the amount of shared services;
8. can be used in various types of businesses.
Despite the benefits, the ABC method may present some disadvantages to the company, such
as:
1. High expenditure for implementation;
2. high level of internal controls to be implemented and evaluated;
3. need for constant review;
4. difficulty of involvement and commitment of the employees of the company;
5. difficulty in integrating information between departments;
2. CONCEPTS OF COSTS
One of the objectives of a business is to be profitable. As the partners or shareholders of
a company expect profits, managers have a responsibility to use resources wisely and to
generate revenues that exceed the costs of operation of the business, investment and
financing.
Costs can be classified and used in several ways depending on the purpose of analysis (Crosson
& Needles, 2011). The classification will allow managers to:
1. Control costs, determining which are traceable to a particular cost object, such as a
service or product.
2. Calculate the number of units that must be sold to achieve a certain level of profit (cost
behavior).
3. Identify the costs of activities that add value or not a product or service.
4. Classify the costs for the preparation of financial statements.
The costs may be classified as follows:
• Direct costs are those costs that can be conveniently and economically allocated to a
product and / or service. For example, the wages of workers who make cereal bars can
be assigned to a particular batch because their hours worked in manufacturing are
known. Similarly, materials such as cocoa butter, sugar, milk, etc..
• Indirect costs are costs that can not be conveniently and economically allocated to a
product and / or service. For example, quality control, equipment maintenance,
supervision spending, etc.. As a matter of accuracy, however, this overhead should be
included in the cost of a product or service.
May also present the following characteristics:
• Variable cost is a cost that changes in direct proportion with the quantity produced (or
some other measure of volume).
• Fixed cost is a cost which is constant within a defined range of activity or time period.
Table 1 shows examples of these concepts to the production of the cereal bar.
Table 1 – Examples of Costs
Item Classification Behavior Attribute Value Type
Sugar Direct Variable Add value Direct material
Labor Direct Variable Add value Direct labor
Supervision Indirect Fixed Does not add Overhead
Depreciation Indirect Fixed Add value Overhead
Sales commission Expense Variable Add value Expense
Administration Expense Fixed Does not add Expense
3. DEVELOPMENT OF THE SYSTEM
A costing system for building a vessel is of high complexity. Should consider the subdivision of
the vessel on specific systems, each having specialized subsystems performing specific tasks and
processing data sometimes imprecise or vague. A hypothetical application is shown based
costing used as the procedure for generating input parameters. The figures are illustrative. The
system was developed for the calculation of expenses and perform the analysis of profit / loss.
This analysis example of a costing system was chosen because it is an application most often
used in the analysis of costs and allows monitoring and understanding, especially in shipping,
once the price is set by the shipyard with the shipowner.
3.1. DESCRIPTION OF THE PROBLEM
The costing system shown has five different systems, shown in Table 2.
Table 2 – Direct Costs of the Building Systems
System Parameter Qty Value
Structure Direct labor 56.700 844.263,00
Material / Equipment 256.000 28.225.024,00
Machines Direct labor 24.100 343.666,00
Material / Equipment - 14.457.414,00
Accessories Direct labor 18.600 274.350,00
Material / Equipment - 4.561.250,00
Nets and Pipes Direct labor 26.100 437.958,00
Material / Equipment - 1.854.365,00
Treatment and Painting Direct labor 32.500 859.625,00
Material / Equipment - 4.784.651,00
Total Direct Costs Direct labor 158.000 2.759.862,00
Material / Equipment - 53.882.704,00
Grand Total of Direct Costs 56.642.566,00
Table 3 presents the indirect costs to be allocated as well as their drivers.
Table 3 – Indirect Costs
Type of Cost Parameter Value
Equipment hours
Total cost 1.650.000,00
Driver: machine hours 24.000,00
Rate 68,75
Procurement
Total cost 265.000,00
Driver: number of orders 2.100,00
Rate 126,19
Planning
Total cost 1.080.000,00
Driver: number of manufacturing orders 22.500,00
Rate 48,00
Quality control
Total cost 1.350.000,00
Driver: hours 8.400,00
Rate 160,71
Administration
Total cost 2.800.000,00
Driver: direct labor 158.000,00
Rate 17,72
Classifier
Total cost 245.800,00
Driver: hours 1.300,00
Rate 189,08
Profit to be appropriated will be equivalent to 10% of direct costs plus indirect, ie, $
6,378,866.00, then forming the sales price of the vessel at $ 70,167,732.00. Table 3 shows the
distribution of the drivers use of the systems:
Table 3 – Use of the Drivers
Item Structure Machines Accessories Nets Painting Total
Driver: machine hours 15.360 3.360 1.920 1.680 1.680 24.000
Direcionador: número de pedidos 504 252 462 546 336 2.100
Driver: number of manufacturing orders 14.400 900 2.700 4.050 450 22.500
Driver: hours 5.376 1.176 672 588 588 8.400
Driver: direct labor 56.700 24.100 18.600 26.100 32.500 158.000
Driver: hours 832 182 104 65 117 1.300
3.2. DEVELOPMENT OF PARAMETERS
In developing this system cost input parameters were estimated using triangular numbers. This
required the estimation of possible lower values (SP), the most probable (MP), and lower (LP) for
each input parameter. By developing a real system, these estimates are developed from a survey
of shipyard experience and analysis of historical data. After a thorough review of all available
data, the parameters are extracted for all input parameters estimated in the light of experience.
The triangular function for each parameter can be achieved by asking three questions: 1) What is
the most promising parameter value, 2) What is the parameter value most likely? and 3) What is
the largest possible value of the parameter?
This process will result in triangular parameters for all input parameters of the estimate. If the
estimator know the true value of a parameter, estimates of SP, MP and LP are equal. If there is
much uncertainty about the true value of the parameter, the parameter of cost will have a wide
triangular membership function, represented by larger ranges of values between the estimates
of the SP, MP and LP. If there is any uncertainty about the true value of the parameter, there will
be narrow lanes between the estimates of the SP, MP and LP. The triangular membership
functions are not necessarily symmetrical and can be tilted to the right or left, depending on the
judgment of the estimator.
In this analytical model, the following steps will be used to generate estimates for each
triangular input parameter in the system example, assuming the hypothesis that it is not
possible to develop these estimates by extrapolation or analysis of historical data (Harrison and
Sullivan, 1996). Thus, we have:
1) In the traditional system costs, the value is assigned as the average of its data set and
this is the most likely value which represents the number triangular this parameter in the
system.
2) It is assumed that a good estimator is able to provide estimated values which remain in
the range of plus or minus 10% of the actual value of the parameter data in constructing
the system. (Cooper and Kaplan, 1988)
3) It is assumed that the data set for each parameter has a normal distribution frequency.
This assumption enables the use of empirical rule approximation to the sample standard
deviation for each parameter. The states of empirical rule implies that almost all
measurements in the data set lying within three standard deviations averaged. Therefore,
10% of the value of the parameter can be equated to three times the standard deviation
of the sample. This will be used to calculate the sample standard deviation, sd, for each
parameter.
4) It is assumed that each parameter is a normal distribution with mean equal to the sample
value of the system parameter and the sample standard deviation is equal to 10% *
(parameter value) / 3.
5) Five hundred random numbers were generated from the resulting distribution. The result
of random numbers is ordered from smallest to largest. The lowest and highest possible
parameters are defined as the same as random numbers lowest and highest, respectively.
An example showing the values, smaller, more likely larger of the total cost of the account
"Hours of equipment," respectively Csi, Cmi, and Cli, for the first group of costs is shown below.
1) Total Cost = sample mean estimate = promising = $ 1,650,000
2) 10% * (Total Cost) = $ 165,000
Desired accuracy range = [$ 1,485,000, $ 1,815,000]
3) 3sd = 10% (Total Cost)
3sd = $ 165,000
sd = $ 55,000
4) Total Cost - parameter distribution = N ($ 1,650,000, $ 55,000)
5) The lowest and highest random numbers are 1466590 and 1792479 respectively.
Minor estimate = $ 1,466,590
Greater estimate = $ 1,792,479
The parameter for the total cost of depreciation of equipment is (CS1, Cm1, Cl1) = ($ 1,466,590, $
1,652,250, $ 1,792,479).
Figure 1 - Triangular Distribution of Depreciation
This same procedure will be done for the other drivers and costs. Table 5 shows the parameters
for each charge, and Table 6 the drivers.
Table 5 – Summary of Costs
Tipo de Custo Cs Cm Cl
Equipment hours 1.792.479 1.650.000 1.466.591
Procurement 288.001 265.000 237.951
Planning 1.196.425 1.080.000 977.618
Quality control 1.489.375 1.350.000 1.245.434
Administration 3.099.288 2.800.000 2.488.760
Classifier 270.175 245.800 216.603
Tabela 6 – Summary of Drivers
Tipo de Custo Ds Dm Dl
Equipment hours 26.638 24.000 21.625
Procurement 2.321 2.100 1.843
Planning 25.208 22.500 20.431
Quality control 9.398 8.400 7.482
Administration 171.314 158.000 142.640
Classifier 1.532 1.300 1.126
3.3. DEVELOPMENT OF RATES
Once the parameters of costs and drivers were obtained, shall be determined rates Rsi, Rmi, Rli,
calculated for each cost center i. The calculations are presented below.
si mi lisi mi li
si mi li
C C CR ,R ,R , , ,
D D D
(1)
This division operation is an approximation resulting in a triangular quotient more conservative.
Note that, by definition, the rate is most likely the same rate resulting from traditional analysis
costs.
Therefore, the development of the system will contribute to the information provided by a
traditional costing system. Using the estimated parameter in the above example, we performed
calculations for depreciation of equipment. The parameter is generated using the procedure
described in section 3.2:
s1 s2 s3
s1 s2 s3
s1 s2 s3
s1 s2 s3
C ,C ,C 1.792.479,1.650.000,1.466.591
D ,D ,D 26.638,24.000,21.625
1.792.479 1.650.000 1.466.591R ,R ,R , ,
26.638 24.000 21.625
R ,R ,R 67,29;67,75;67,82
Overall rates Rs1, Rs2 and RS3 can be used in many types of analyzes, including product costing,
pricing for profit, product development, analysis and budget development, etc.. The application
presented in this paper uses the general rates for product costing as a tool for determining the
profit / loss of each building system, and these analyzes familiar to anyone working in this area.
Table 7 – Summary of the Rates
Tipo de Custo Rs Rm Rl
Equipment hours 67,29 68,75 67,82
Procurement 126,19 124,06 129,10
Planning 48,00 47,85 47,62
Quality control 166,47 160,71 158,61
Administration 18,09 17,72 17,45
Classifier 192,32 189,08 178,30
To calculate the total cost of each production system, overhead costs are obtained by
multiplying the consumption of each system cost by the corresponding rate for each building
system and adding the resulting values. These overheads are used in the analysis of profit / loss,
to make the comparison with the total cost resulting from the sales price of the vessel. The
algorithm for the calculation is shown below:
1) Calculate the indirect cost to the alternatives, the smaller, the more likely and higher,
OHsk, OHmk, OHlk, respectively, for a system k.
m
sk sm lk si sik mi mik li liki 1
OH ,OH ,OH R CDC ,R CDC ,R CDC
(2)
Where: CDCsik = lower consumption cost driver system i to k
CDCmik = more likely consumption the cost driver system for k i
CDClik = less consumption cost driver system for k i
m = number of systems
Table 8 – Allocation of Overhead
Sistema
Structure Machines Accessories Nets Painting
Equipment hours
CDCs1k 1.033.589,30 226.097,66 129.198,66 113.048,83 113.048,83
CDCm1k 1.056.000,00 231.000,00 132.000,00 115.500,00 115.500,00
CDCl1k 1.041.702,64 227.872,45 130.212,83 113.936,23 113.936,23
Procurement
CDCs2k 63.599,76 31.799,88 58.299,78 68.899,74 42.399,84
CDCm2k 62.526,24 31.263,12 57.315,72 67.736,76 41.684,16
CDCl2k 65.063,91 32.531,95 59.641,91 70.485,90 43.375,94
Planning
CDCs3k 691.200,00 43.200,00 129.600,00 194.400,00 21.600,00
CDCm3k 689.040,00 43.065,00 129.195,00 193.792,50 21.532,50
CDCl3k 685.728,00 42.858,00 128.574,00 192.861,00 21.429,00
Quality control
CDCs4k 894.942,72 195.768,72 111.867,84 97.884,36 97.884,36
CDCm4k 864.000,00 189.000,00 108.000,00 94.500,00 94.500,00
CDCl4k 852.687,36 186.525,36 106.585,92 93.262,68 93.262,68
Administration
CDCs5k 1.025.777,90 436.000,84 336.498,57 472.183,48 587.967,93
CDCm5k 1.004.810,13 427.088,61 329.620,25 462.531,65 575.949,37
CDCl5k 989.293,97 420.493,56 324.530,30 455.389,29 567.055,63
Classifier
CDCs6k 160.010,24 35.002,24 20.001,28 12.500,80 22.501,44
CDCm6k 157.312,00 34.412,00 19.664,00 12.290,00 22.122,00
CDCl6k 148.345,60 32.450,60 18.543,20 11.589,50 20.861,10
2) Calculate the product cost to the alternatives, the smaller, the more likely and higher,
PCsk, PCmk, PClk, respectively, for a system k.
(PCsk, PCmk, PClk ) = (DLk + DMk +OHsk, DLk + DMk +OHmk, DLk + DMk +OHlk) (3)
Where: DLK = directly labor cost assumed for the system k
DMK = material cost assumed for the system k
Table 9 – Total Costs by System
Item Estutura Máquinas Acessorios Redes Pintura
PCsk 32.938.406,92 15.768.949,34 5.621.066,13 3.251.240,21 6.529.678,40
PCmk 32.902.975,37 15.756.908,73 5.611.394,97 3.238.673,91 6.515.564,03
PClk 32.852.108,49 15.743.811,93 5.603.688,16 3.229.847,60 6.504.196,57
3) Calculate the estimated profit to the alternatives, the smaller, the more likely and higher,
SPsk, SPmk, SPlk, respectively, for a system k.
(NPsk, NPmk, NPlk) = (SPk - PCsk, SPk - PCmk, SPk - PClk) (4)
Where: SPk = estimated profit for the system k
Table 10 – Profit by System
Item Structure Machines Accessories Nets Painting
NPsk 3.262.641,16 2.643.561,68 399.518,88 -392.587,72 494.229,14
NPmk 3.229.748,77 2.641.604,89 398.338,00 -390.863,66 500.038,00
NPlk 3.226.635,11 2.643.376,02 400.075,07 -386.729,83 505.825,54
3.4. ANÁLISE DOS RESULTADOS
The traditional cost analysis will give us the profit of the vessel is $ 6,378,866.00, which is the
same result obtained by the most probable hypothesis, however, does not present the results
for each system. When analyzed individually each system we can observe that the profit of the
yard is guaranteed, however, in our example, the system "Nest and Piping" presents a loss.
This fact may be related to drivers adopted, however, is an answer that was not visible in the
traditional system. It is therefore the manager to analyze data and adjust the parameters
adopted in order to be sure of the profitability of each system. It is also important to note that
the entry of uncertainty in the system, provides the shipyard the boundaries of its profitability,
since the Indirect Costs and Profit, are spending under your control.
Figure 2 – Probability distribution of Profit
4. CONCLUSION
Os sistemas de cálculo de custos devem basear-se em dados precisos, levantados
meticulosamente. Na maioria das vezes, as empresas não conseguem incorporar em seus
sistemas de custos dados mais detalhados, devido às despesas que isso acarreta, bem como, os
requisitos de tempo necessários. Os sistemas de custeio são construídos utilizando dados
estimados. Portanto, desenvolver um sistema de custeio, que permita lidar com a imprecisão de
dados, e a incerteza inerente, é uma abordagem de custo-benefício atrativa para a gestão da
empresa. Fornece ao gestor uma alternativa de geração de informações gerenciais com três
estimativas para cada parâmetro estimado, permitindo que o usuário reconheça que essas
estimativas apesar de não representarem os valores verdadeiros, incorporam uma noção sobre a
variabilidade dos dados, e a incerteza em seus processos decisórios.
Este trabalho abordou a atividade de custeio, detalhou o desenvolvimento de um modelo, e
apresentou uma aplicação hipotética. Trabalhos futuros nesta linha irão pesquisar o
detalhamento dos subsistemas e suas atividades, de forma a se obter uma visão analítica da sua
lucratividade, uma vez que em construção naval, além dos direcionadores de custos, tem-se
também os estágios de produção, atividade na qual os custos devem ser apropriados.
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