In-depth | cost analysis
Figure 6. assembly-related allocation of
Figure 5. Differentiated allocation of hardness grades. hardness grades.
calculated as: The quantitative meanings of these hardness
grades are specified centrally in the system
n
(Figure 4). In the shown example a forecast
∑
(f
i
⋅ y
i
)
2
divergence of +/- 30% is assigned to the
f
s
=
i=1
um
y
2
hardness grade 1. This means that the
sum
with actual costs of a calculation object with this
f
sum
=relative error of the complete forecast value hardness grade will vary probably in the
f
i
=relative error of the single forecast values
area between 70% and 130% of the forecast
y
sum
=complete forecast value (sum of single
value. Beside the percentage value also a
forecast values)
comment can be given in another column.
Figure 7. Risk analysis – forecast error at
y
i
=single forecast values
This comment is later indicated to the user
project or assembly level. as information in which case the respective
Figure 3 shows exemplary the decrease hardness grade should be chosen.
of the relative error of the complete forecast The reason for not assigning a percentage
a binding offer of a supplier is already value depending on the number of the value of the prospective forecast error to a
given for the considered object or whether single forecast values. Here it is assumed component directly is that the allocation of
the cost can be estimated by referring to that all single forecast values are estimated a hardness grade of one of maximum five
a comparative object. To quantify this with a divergence of ± 50% and have the different classes is much more practicable
uncertainty, costfact offers a risk analysis same share of the total sum. than to estimate a percentage value with
function. This function calculates the Beside the advantage of the statistical every input.
prospective forecast error for a calculation error compensation the splitting of an Within the project calculation there
object, e.g. a subordinated or higher estimate improves its quality because are two different ways to fix the hardness
assembly, as well as the complete project. it is more simple to forecast single cost grades for the cost forecast of a component.
The calculation is made on the basis of components, than a whole cost block. In On the one hand, it can be differentiated for
evaluations with regard to the forecast such a manner it will be always easier to every single cost component. This is carried
errors of the single components of this estimate the production costs of an object out in the dialogue mask for the input and
object and the statistical compensation of if this takes place divided into material editing of the calculation objects (Figure 5).
any divergence. This compensation effect costs and production costs or valued The applicable hardness grade is selected
is briefly described in the following. manufacturing hours. Also the costs of from the dropdown list in column ‘HG’.
an assembly can be easier predicted if On the other hand a hardness grade can be
Statistical error compensation: The the single components are considered also specified for complete building groups.
exactness of an estimate can be improved individually. Therefore, the user selects the respective
substantially by determining the value to be building group in the project view which
forecast as a sum of its single components. ‘Hardness grades’ to describe the is shown in Figure 2. This building group
If only accidental and no systematic errors uncertainty: In costfact the evaluation may be both a final assembly as well as
appear with the determination of the single of the prospective exactness of the cost a group on another structure level (e.g.
components, the positive and negative forecast of single components is expressed 2000 – Propulsion plant). Afterwards
distributed divergences will compensate by so-called ‘hardness grades’. These grades the user chooses the hardness grade that
themselves partly. can assume values between 1 and 5. A shall be given for the single components
If the Gaussian normal distribution hardness grade of 1 shows a forecast with of the selected object (Figure 6). After the
can be assumed, the relative error of high uncertainty, while the hardness grade selection of the suitable hardness grade in
the complete forecast value can be 5 represents an especially low uncertainty. the list, the user associates this grade to
24 The Naval Architect February 2010
NA Feb10 - p20+p22+p24+p26.indd 24 02/02/2010 16:44:26
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