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57
Control processes
1. Introduction
The food security problem remains unresolved in the
world today. The problem became more important due to
growing demands of the World Trade Organization for food
quality, because farms of individual communities produce
the major portion of raw milk and they do not have their own
processing shops. Large dairy plants, which are monopolists
in this field, process dairy raw material. Dairy plants dictate
price policy and it becomes unprofitable for small farms to
produce raw milk. Duration of a period from milk production
to its processing increases, which reduces quality of dairy
Received date 29.08. 2019
Accepted date 18.11.2019
Published date 13.12.2019
Copyright © 2019, A. Tryhuba, M. Rudynets, N. Pavlikha, I. Tryhuba,
I. Kytsyuk, O. Korneliuk, V. Fedorchuk-Moroz, I. Androshchuk, I. Skorokhod, D. Seleznov
This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0)
ESTABLISHING PATTERNS OF
CHANGE IN THE INDICATORS
OF USING MILK PROCESSING
SHOPS AT A COMMUNITY
TERRITORY
A. Tryhuba
Doctor of Technical Sciences, Professor, Head of Department
Department of Information Systems and Technologies*
M. Rudynets
PhD, Associate Professor
Department of Civil Security**
E-mail: RudynetsMykola@lutsk-ntu.com.ua
N. Pavlikha
Doctor of Economic Sciences, Professor, Vice-rector***
I. Tryhuba
PhD, Associate Professor
Department of Genetics, Breeding and Plant Protection*
I. Kytsyuk
PhD, Associate Professor
Department of International Economic Relations and Project Management***
O. Korneliuk
PhD, Senior Lecturer
Department of International Economic Relations and Project Management***
V. Fedorchuk-Moroz
PhD, Associate Professor
Department of Civil Security**
I. Androshchuk
PhD, Associate Professor
Department of Civil Security**
I. Skorokhod
PhD, Associate Professor
Department of International Economic Relations and Project Management***
D. Seleznov
PhD, Senior Lecturer
Department of Industry Engineering and Forestry**
*Lviv National Agrarian University
V. Velykoho str., 1, Dublyany, Ukraine, 80381
**Lutsk National Technical University
Lvivska str., 75, Lutsk, Ukraine, 43018
***Lesya Ukrainka Eastern European National University
Voli ave., 13, Lutsk, Ukraine, 43025
Запропоновано пiдхiд до обґрунтування
закономiрностей змiни показникiв викори-
стання молочних цехiв на територiї громад за
рiзних їх параметрiв та iз врахуванням мiн-
ливих виробничих умов. Цей пiдхiд базуєть-
ся на проведенi експериментальних дослiд-
женнях складових виробничих умов, враховує
їх особливостi для кожної окремої громади i
передбачає моделювання виконання робiт у
переробних цехах.
На пiдставi прогнозування добових обсягiв
надходження на переробку молока вiд госпо-
дарств громад впродовж календарного року
встановлено, що iснує два перiоди – iнтенсив-
ний (з 119 по 301 доби календарного року) та
неiнтенсивний (з 1 по 118 та з 302 по 365 добу
календарного року). У iнтенсивний перiод
переробки молока слiд органiзовувати робо-
ту у двi змiни, а у неiнтенсивний перiод у одну
змiну. Встановлено, що добовi обсяги перероб-
ки молока описуються законами розподiлу
Вейбулла, а їх статистичнi характеристи-
ки впродовж iнтенсивного та неiнтенсивного
перiодiв вiдповiдно становлять: коефiцiєнт
варiацiї – 0,65 та 0,62; параметр форми –
1,56 та 1,64. При цьому, довiрчий iнтервал
знаходиться в межах 509…6995 та 46…634 л.
На прикладi виробничих умов Бродiвського
району Львiвської областi (Україна) проведе-
но дослiдження щодо обґрунтування зако-
номiрностей змiни показникiв використання
молочних цехiв на територiї громад за рiз-
них їх параметрiв та iз врахуванням мiн-
ливих виробничих умов. Встановлено, що зi
зростанням продуктивнiстi молочних цехiв
вiд 0,5 до 20 т/добу пропорцiйно знижуєть-
ся питоме споживання електроенергiї вiд 116
до 10 кВт/тону, питоме споживання води вiд
10 до 0,3 м3/тону та питома потреба (Nu) у
людськiй працi вiд 0 до 0,3 осiб/тону за вироб-
ництва рiзних видiв молочних продуктiв.
Дослiдженi мiнливi виробничi умови та
визначенi тенденцiї змiни показникiв вико-
ристання молочних цехiв на територiї гро-
мад лежать в основi визначення вартiсних
показникiв. Результати проведених дослiд-
жень будуть корисними пiд час iдентифiка-
цiї конфiгурацiї проектiв створення цехiв
виробництва молочних продуктiв на тери-
торiї громад
Ключовi слова: функцiонування, цех, пе-
реробка молока, ефективнiсть, плануван-
ня, моделювання, стохастичнiсть, вироб-
ничi умови
UDC 005:658.631.3
DOI: 10.15587/1729-4061.2019.184508
Eastern-European Journal of Enterprise Technologies ISSN 1729-3774 6/3 ( 102 ) 2019
58
products. The situation does not meet the requirements of
the EU law. Milk belongs to perishable products and it has
specific requirements for its processing.
It is necessary to implement projects for creation of milk
processing shops (MPS) at community territories to solve
the existing problem. The government developed a series of
programs, which promote development of communities and
creation of manufacturing facilities in their territories. At
the same time, MPS remain out of attention, but their prod-
uct configuration has a significant impact on both quality of
dairy production and its cost.
It is necessary to identify characteristics of configu-
ration objects of the specified projects and their products
for the effective implementation of MPS in territories
of individual administrative communities. We must use
specific methods and models to do this. In particular, the
toolkit for identification of characteristics of MPS product
configuration objects in territories of individual adminis-
trative communities should take into account features of
a production component of the project environment. The
features include presence and parameters of dairy farms,
their territorial location, a state of a road network be-
tween them, etc. Seasonality of milk production plays an
important role. The mentioned features of the production
component of the project environment determine operation
modes of a processing shop and characteristics of equip-
ment for milk processing. The features are specific in each
community and have a significant impact on performance
of milk processing shops. Also, the production component
of the project environment influences operating modes of
processing shops during a calendar year.
Effective implementation of MPS is impossible without
resolution of the task of identification of their products
taking into account the fact that individual communities
have their own specific features of a production component
of the project environment. Quality identification of MPS
products requires justification of regularities of changes in
the use of milk processing shops at community territories
according to their different parameters and taking into con-
sideration changing production conditions.
2. Literature review and problem statement
Authors of study [1] propose an approach to identifica-
tion of characteristics of objects of configuration of project
products. Works [2–5] are about improvement of efficiency
of using of project configuration objects by different criteria
(cost, environmental impact, etc.). Works [6–8] take into
account features of the use of configuration objects in proj-
ects. However, it is impossible to use the results of studies
obtained in [6–8] to establish regularities of changes in the
use of milk processing shops in territories of individual ad-
ministrative communities, because there are no criteria for
the quality of production of dairy products and time for their
production. These criteria are specific for the study on func-
tioning of milk processing shops, which produce perishable
foods including dairy products.
Authors of papers [9–11] suggest to model operation of
system configuration objects to determine indicators of their
use. However, the above methods and models use determin-
istic indicators of the usage of system configuration objects
as their basis. It is impossible to use the results of the studies
on functioning of milk processing shops obtained in [9–11],
because they do not take into account variable volumes of
raw materials coming to processing shops during a calendar
year and conditions and features of performance of works in
production of dairy products.
Works [12–14] suggest substantiating a need for sys-
tem configuration objects taking into account variable
loading volumes, and works [15–17] – taking into account
their risk. However, it is impossible to use the results
obtained in [12–17] to determine trends in changes in the
use of milk processing shops in territories of individual
administrative communities, because authors do not take
into account the specific characteristics of production
conditions. In particular, they do not take into account fea-
tures of the production component of functioning of milk
processing shops, which is specific in each of the territory
communities. In addition, they do not take into account
seasonality of milk production and, accordingly, a volume
of milk processing. All the above affects the efficiency of
operation of milk processing shops [18, 19] and quality of
dairy products produced significantly [20].
One knows that adequate forecasting of characteristics
of a production component of functioning of milk processing
shops is possible through on their modeling only [20, 22].
However, as regards functioning of milk processing shops,
it is necessary to carry out specific studies for each of com-
munity territory where we plan to place a milk processing
shop [21]. It is not possible to determine trends in changes in
the use of milk processing shops adequately and to substanti-
ate the effective configuration of their projects without tak-
ing into account specific production conditions of individual
communities and without taking into account seasonality of
milk production.
One should note that there are scientific works [13, 16],
which forecast production conditions of milk processing
systems partially. However, authors of scientific works [13,
16] take into account receipt of milk for its processing from
large farms. They do not forecast conditions of milk pro-
duction by farms in a community adequately. In addition,
they do not provide for modeling of the use of milk process-
ing shops, taking into consideration seasonality of milk
production, which makes it impossible to justify trends of
changes in the use of milk processing shops at a community
territory adequately.
Researchers paid enough attention to the solution of the
task of identification of characteristics of project product
configuration objects in different areas. However, authors of
scientific papers do not take into account features of MPS
fully. That is why we need an appropriate scientific research.
In particular, quality identification of MPS products re-
quires justification of regularities of changes in indicators
of the use of milk processing shops at community territories
at different parameters and taking into account changing
production conditions.
3. The aim and objectives of the study
The objective of this study is the identification of trends
in changes in indicators of the use of milk processing shops
at a community territory under different parameters and
taking into account changing production conditions, which
underlie the formation of a knowledge base for supporting
making of management decisions about planning of configu-
ration of the specified milk processing shops.
59
Control processes
We set the following tasks to achieve the objective:
– substantiation of stages and features of forecasting of
functional indicators of milk processing shops at a commu-
nity territory;
– investigation of an influence of parameters of commu-
nity milk processing shops on indicators of their use taking
into account changing production conditions.
4. Stages and features in forecasting functional indicators
of milk processing shops at community territories
Forecasting of the use of milk processing shops at a com-
munity territory consists of five stages (Fig. 1).
Fig. 1. Stages in forecasting indicators of using milk
processing shops at a community territory
Stage 1. Construction of a database on the availability of
modular milk processing shops in the market and their char-
acteristics. The formation of a database on the availability of
modular milk processing shops on the market provides for
the analysis of presence of modular milk processing shops
of different productivity for processing of milk on the do-
mestic market for a given dairy production technology. It is
necessary to fill in the forms for each of the shops of a given
productivity. Forms contain data on characteristics of their
technical equipment (Table 1).
It is possible to analyze the availability of technical
equipment of modular shops for processing of milk on the
market and technological features of their use based on the
completed form (Table 1). Dairy production technologies
use types of obtained dairy products and performance of
separate operations (machine, automated, combined) as a
basis [22–24]. A choice of modular milk processing shops
occurs according to the chosen technology.
Stage 2. Analysis of production conditions of milk pro-
cessing at a community territory. Justification of presence
and territorial location of milk producers in individual
communities occurs based on the analysis of reporting doc-
umentation of these communities. We can express the vol-
ume (Qdn) of milk supply from each of individual producers
of milk at a community territory on the t-th day of a season
of its processing by formula:
1
,
sn
N
dn dxj
х
QQ
=
=å
(1)
where (Qdxj) is the volume of milk production of x-th farm,
which sells it to the n-th shop on the j-th day of a season of
its processing, t; Nsn is the number of farms that sell milk to
the n-th processing shop, units.
Characteristics of the organizational component of milk
processing at a community territory include a mode of work
execution (a number of changes in the operation of milk pro-
cessing shops), which is variable during a separate calendar
year. The cause of its change (adaptation) is a temporary
change in a volume of milk processing during a calendar
year. We can forecast the change in dependence on the
amount of milk supply for processing.
Stage 3. Forecasting trends of change in the volumes of
milk for processing within a calendar year. Daily production
of milk in x-th community, which forms a flow of orders for
implementation of milk processing works on the specified
technical equipment of modular shops, is variable. It has the
following characteristics: a number of dairy herds in a com-
munity (nk), their productivity (qk) and age (vk), a day, when
milk is produced within the period of lactation of cows (τi), a
diet (θ) and conditions of keeping of cows (ω):
( )
, , , ,, .
dxj k k k i
Q fnq v= t θω
(2)
Considering vk, τi, θ, and ω are probable quantities, Qdxj
will also be probable. Therefore, quantitative value of fore-
casting of Qdxj requires application of statistical methods.
We can use analytical-experimental method
based on statistical modeling of the value production
to forecast Qdxj quantitative value. The application of
the method makes possible to justify quantitatively a
variable volume of milk received for processing not
only totally from all farms at a community territory,
but also to forecast a variable volume of milk received
for processing from each farm. This, together with the
territorial location of farms, has an impact on a cost of
milk processing resources and a cost of milk products
obtained after milk processing.
The feature of forecasting of a volume (Qdxj) of
milk received for processing on a single day is that the
volume is variable and depends on the lactation peri-
od of cows. It lasts from 265 to 435 days (depending
on a breed, age and productivity of cows, etc.). The
volume is shifted relatively to a calendar year for in-
dividual cows and milk production goes throughout the entire
calendar year. However, the major portion of milk production
volumes falls on summer months. Therefore, technical equip-
ment of a processing shop works intensively in summer months.
The total volume
k
d
Q
of milk production on the ј-th day is:
1
,
n
kk
d dj j x
j
Q Q zk
=
= ⋅⋅
å
(3)
1
• Formation of a database on the availability of modular milk processing
shops in the market and their characteristics
2
• Analysis of production conditions of milk processing at a community
territory
3
• Forecasting of trends in the change in volumes of milk for processing
within a calendar year
4
• Modeling of functioning of milk processing shops at the territory of a
community
5
• Justification of regularities of changes in indicators of the use of milk
processing shops at the territory of a community
Table 1
The form of characteristics of technical equipment of modular shops
for processing of milk
Indicator Measure-
ment unit
Productivity, tons/day
0.5 1 3 5 10 20
Installed
power kW 57 85 163 222 439 638
Water loss m3/day 5 6 6.5 7 8 20
Drainage
rate m3/h 3.5 3.5 3.5 3.5 5.5 5.5
Human
labor needs persons 1 1 2 3 5 6
Cost UAH,
thousand 2,056.63 2,123.6 5,982.06 7,449.4 12,989 17,744
Eastern-European Journal of Enterprise Technologies ISSN 1729-3774 6/3 ( 102 ) 2019
60
where zj is the number of milking of cows per day; k is a coef-
ficient, which takes into account the proportion of raw milk
left by producing farms for its own use; kx is the settlement
at a territorial community.
Step 4. Modeling of functioning of milk processing shops
at a community territory. The modeling of functioning of
milk processing shops at a community territory occurs based
on implementation of separate daily cycles of their function-
ing, the total duration of which is equal to the duration of
a calendar year (tc=365 days). It is necessary to determine
forecasting functional parameters of milk processing shops
for each of the cycles, such as a daily volume (Qdv) of pro-
cessed milk; daily complexity (θdv) of milk processing; a daily
volume (Pe) of consumed electricity; a daily volume (qw) of
water consumed.
Having the quantitative value of the intensity (Idj) of
milk production on j-th day of a calendar year and given the
value of the daily productivity (Wcd) of a milk processing
shop, we can determine the forecasting volume (Qdvj) of milk
supply for processing from by a milk processing shop on j-th
day of a calendar year, by formula
.
dvj cd dj
Q WI=⋅
(4)
We can determine the daily complexity (θdv) of milk
processing from formula
,
uwds nws stvNt n k= ⋅⋅ ⋅θ
(5)
where Nu is the number of performers, persons; tws is the
duration of a work shift, h; nnws is the number of work shifts
at a milk processing shop, units; kst is the coefficient of time
use factor of a shift.
One can determine the daily volume of electricity con-
sumption (Pe) from formula
,
e c nj ej
P Pt k=⋅⋅
(6)
where Pc is the total installed power of electricity con-
sumers at a milk processing shop, kW; tnj is the duration
of milk processing shop operation on the j-th day of a
calendar year, h; kej is the coefficient of use of electricity
by consumers at a milk processing shop on the j-th day of
a calendar year.
One can determine the daily volume of water consump-
tion (qw) from formula
,
n
w w st
q qk=⋅
(7)
where
n
w
q
is specific water consumption, m3/day;
st
k
is the
coefficient of water use during the change.
One can determine total annual values having quanti-
tative values of the forecasted daily functional indicators of
milk processing shops at a community territory.
Stage 5. Justification of regularities of changes in indi-
cators of the use of milk processing shops at a community
territory. Based on the obtained quantitative values of the
forecasted total annual indicators of functioning of milk
processing shops, one can build their dependences on chang-
es in the productivity of shops. The correlation-regression
analysis of the dependences makes it possible to substantiate
their equations and correlation coefficients, which testifies
to the probability of the obtained regularities of changes in
the use of milk processing shops at a community territory at
their different parameters and taking into account changing
production conditions.
5. Results of studying the influence of parameters of milk
processing shops on indicators of their use taking into
account changing production conditions
We carried out studies on the functioning of milk pro-
cessing shops at a community territory according to the
above stages (Fig. 1). First of all, we carried out an analysis
of milk processing equipment and shops available on the
market, which meet the current EU requirements for the
quality of dairy production. The analysis of milk processing
shops manufactured in the world shows that they are multi-
variate. Shops differ in both a technology of milk processing
and a type of obtained milk products, their packaging, a use
of human labor, availability and planning of production and
auxiliary premises, features of technological processes and
technical equipment for their implementation. According to
the criteria of cost and quality, we selected modular mini-
plants manufactured by CJSC “COLAX-M” for further
research. The main advantage of “COLAX” modular dairy
mini-plants (shops) is that they are ready-to-use complexes
for milk processing. In addition, the company manufactures
modular mini-plants for milk processing with a wide range
of productivity (from 0.5 to 20 t/day).
Modular “COLAX” milk mini-plant contains a set of
equipment for storage and processing of milk mounted in a
single line. Each mini-plant has systems of cold and hot wa-
ter supply, power supply, drainage, heating, ventilation, and
air conditioning. “COLAX” mini-plant is able to perform the
following operations:
– acceptance, purification, cooling and storage of milk;
– pouring and packing of milk into any packages (poly-
ethylene or Pure-Pack);
– obtaining of any dairy and sour milk products;
– restoration of milk powder;
– storage of finished products in refrigerators of shops;
– provision of living conditions for staff.
Table 2 shows characteristics of dairy products produced
by “COLAX” modular dairy mini-plants (shops), depending
on their productivity.
Table 2
Characteristics of dairy products produced by “COLAX”
modular dairy mini-plants (shops)
Type of a dairy product
Productivity of a milk processing shop,
t/day
0.5 1 3 5 10 20
Pasteurized milk (3.7 %) 0.265 0.431 1.294 2.157 5.914 12.628
Sour cream or dairy
cream (20 %) 0.035 0.069 0.136 0.243 0.4 1
Cultured milk beverage
kefir (2.5 %) 0.1 0.2 0.5 1 1.8 3
Cheese (9 %) – 0.03 0.076 0.153 0.153 0.307
«Selyanske» dairy butter – – 0.019 0.027 0.078 0.101
Adygeiskiy soft cheese 0.01 0.01 0.05 0.05 0.06 0.1
Whey 0.09 0.26 0.874 1.297 1.387 2.594
Buttermilk – – 0.051 0.073 0.208 0.27
An analysis of production conditions of milk processing
for the conditions of territorial communities in the Brodi-
61
Control processes
vsky region of Lviv oblast (Ukraine) was performed. We
used the methodology described above and performed fore-
casting of daily milk supply for processing by community
farms during a calendar year. We used data on volumes of
milk supply for processing on individual days of a calendar
year presented in [16] for each of 27 communities of the spec-
ified administrative district.
Based on the data obtained on the daily volumes of milk
supply for processing from individual territorial communi-
ties during a calendar year and the above methodology, the
volumes of milk processing were forecast during a calendar
year at different productivity of milk processing shops.
Fig. 2 shows forecasting results.
Fig. 2. Forecasted trends of a change in volumes of milk
processing during a calendar year at a given productivity of
milk processing shops
The results obtained of forecasting of trends in changes
in daily volumes of milk processing during a calendar year
shows that the volumes are variable. We established that
there are two periods of milk supply for processing – an
intensive period (from day 119 to day 301 within a calendar
year) and non-intensive one (from day 1 to day 118 and from
day 302 to day 365 within a calendar year). It is necessary
to organize a work of shops in two shifts during the intensive
period of milk supply for processing, and one shift ‒ during
the non-intensive period of milk supply.
We substantiated distribution of daily milk production
on territories of individual communities for each period
within a calendar year. It was established that the Weibull
distributions laws (Fig. 3, 4) describe distributions of a daily
volume of milk production. Table 3 gives their corresponding
statistical characteristics.
The main statistical characteristics of distributions of
the forecasted daily volume of milk production at the ter-
ritory of individual communities in Brodisky region of
Lviv oblast during the intensive (Fig. 3) and non-intensive
(Fig. 4) periods of its supply for processing are, respectively:
a coefficient of variation ‒ 0.65 and 0.62; a shape parameter
is 1.56 and 1.64. The confidence interval is in the range of
509…6,995 and 46…6,34l.
Fig. 3. Distribution of the forecasted
daily volume of milk production in the territory of individual
communities during the intensive period of its supply for
processing
Fig. 4. Distribution of the forecasted
daily volume of milk production in the territory of individual
communities during the non-intensive period of its supply for
processing
0
2
4
6
8
10
12
14
16
18
20
25 50 75 100125150175200225250275300325350
Daily volume of milk pr oc ess ing
Q
dvj
, t/day
Day of a calendar year
– 0,5 t/day; – 1 t/day; – 3 t/day;
– 5 t/day; – 10 t/day; – 20 t/d ay;
Table 3
Statistical characteristics of distributions of the forecasted daily volume of milk production in the territory of individual
communities in separate periods of its supply for processing
Indicator Equations
Statistical characteristics
[ ]
i
MQ
[ ]
i
Qs
Intensive period of milk supply for
processing, l
0,568 1,568
3
509 509
( ) 1 10 exp
2457 2457
ii
i
QQ
fQ
-
--
=⋅ × -
2716 266
Non-intensive period of milk supply for
processing, l
0,648 1,648
3
46 46
( ) 7 10 exp
246 246
NN
N
QQ
fQ
-
--
=⋅ × -
1429 136
Note:
[ ]
i
MQ
,
[ ]
i
Qs
are, respectively, a mathematical expectation and a standard deviation of the forecasted daily volume of milk produc-
tion in the territory of individual communities over the i-th period, l; 509, 46 are, respectively, a minimum value of the forecasted volume of
daily milk production at the territory of individual communities for inten sive and non-intensive periods; 2, 457, 246 are, res pectively, a scale
parameter for intensive and non-intensive periods
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
1,050 2,131 3,212 4,293 5,374 6,45 5
Freq uency, Р
і
Volume o f milk pr oc ess ing, Q
i
, lite rs
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
95 193 291 389 48 7 585
Frequency, Р
і
Volume o f milk pr oce ssing , Q
N
, lite rs
Eastern-European Journal of Enterprise Technologies ISSN 1729-3774 6/3 ( 102 ) 2019
62
The adequacy of the obtained distribu-
tions was checked according to the Pearson
criterion X2. We calculated its values X2 with
tabulated ones
( )
2
*X
for the distributions of
the forecasted volume of daily milk produc-
tion in the territory of individual communi-
ties during the intensive and non-intensive
periods of its supply for processing. Accord-
ingly, the values make up
( )
( )
( )
2
2
0,71 * 4,6XX=< =
,
( )
( )
( )
2
2
0,89 * 3,2 .XX=< =
Therefore, Weibull’s theoretical distribu-
tion curves adequately reflect the empirical
data of the forecasted daily volume of milk
production in the territory of individual com-
munities during the intensive and non-inten-
sive periods of its supply for processing.
Based on the characteristics of “COLA X”
modular dairy mini-plants (shops) and the
forecasted daily volume of milk production
in the territory of individual communities,
we performed numerical modeling of the op-
eration of shops using the MS Excel package.
The modeling made it possible to obtain func-
tional indicators of the use of modular milk
processing shops (Table 4).
Table 4
Functional indicators of the use of modular
milk processing shops
Characteristics
Productivity of a milk
processing shop, t/day
0.5 1 3 5 10 20
Specific con-
sumption of
electricity (Ре),
kW/t of pro-
cessed milk:
option 1 64.0 48.0 17.3 11.4 13.9 7.8
option 2 112.0 64.0 27.6 21 24.6 16.2
option 3 114.0 85.0 54.3 44.4 43.9 31.9
Specific con-
sumption (qw)
of water, m3/t of
processed milk:
option 1 6.0 4.0 1.3 0.8 0.4 0.3
option 2 6.0 4.0 1.5 1.0 0.6 0.45
option 3 10.0 6.0 2.1 1.4 0.8 1.0
Specific need
(Nu) for human
labor, persons/t
of processed milk
2.0 1.0 0.66 0.6 0.5 0.3
Note: option 1 – production of pasteurized milk;
option 2 – production of pasteurized milk and sour
cream; option 3 – production of pasteurized milk, sour
cream, cultured milk kefir beverage, cheese and butter
We constructed the dependences of functional indi-
cators of using modular milk processing shops on their
productivity (Fig. 5–7) based on processing the obtained
data given in Table 4.
We performed the approximation of the obtained func-
tional indicators of the use of modular milk processing shops
(Table 4) using the MS Excel package. The approximation
made it possible to define trends in changes in the specific
consumption of electricity (Ре) (kW/t of processed milk) on
the productivity (qc) of a milk processing shop in production
of different types of dairy products (Fig. 5). Exponential
lines of trends describe them. The lines have the following
equations:
– production of pasteurized milk
Ре=40.588 qc-0.576, r=0.92; (8)
– production of pasteurized milk and sour cream
Ре=63.787 qc-0.506, r=0.89; (9)
0
20
40
60
80
100
120
5 10 15 20
Sp ecif ic c ons umpt io n of elect ric p o wer,
Р
е
, kW/t
Pro d uc tiv ity, q
c
, t/d ay
productio n of pasteurized milk
produ ctio n of pas teur ized milk and sour cream
produ ctio n of pas teur ized milk, so ur cre am, cul ture d milk kefir beverage, cheese and
butter
Fig. 5. Dependences of specific consumption (Ре) of electricity on
productivity (qc) of a milk processing shop
0
2
4
6
8
10
5 10 15 20
Specific consumption of water, q
w
, m
3
/t
Pr o duc tivity, q
c
, t/day
production of pasteurized milk
product ion of pasteuri zed milk and sour cre am
production of pasteurized milk, sour cream, cultured milk kefir beverage, cheese and
butter
Fig. 6. Dependences of specific consumption (qw) of water on productivity
(qc) of a milk processing shop
63
Control processes
– production of pasteurized milk, sour cream, cultured
milk kefir beverage, cheese and butter
Ре=84.965 qc-0.968, r=0. 9 6 . (10)
Exponential lines of trends describe trends in changes in
the specific consumption of water (qw) on the productivity (qc)
of a milk processing shop in production of different types of
dairy products (Fig. 6). They have the following equations:
– production of pasteurized milk
qw=3.473 qc-0.868, r=0.9 9 ; (11)
– production of pasteurized milk and sour cream
qw=3.601 qc-0 .74 , r=0 .9 9; (12)
– production of pasteurized milk, sour cream, cultured
milk kefir beverage, cheese and butter
qw=5.412 qc-0.704 , r=0 .9 3 . (13)
Exponential lines of trends describe trends in changes
in the specific need (Nu) in human labor on the productivity
(qc) of a milk processing shop for all options of dairy prod-
ucts production (Fig. 7). The lines correspond to equation:
Nu=1.2198 qc–0.453, r=0.94. (14)
The obtained dependences show that the increase in
the productivity (qc) of milk processing shops from 0.5 to
20 t/day leads to a proportional decrease in the specific con-
sumption of electricity (Fig. 5) from 116 to 10 kW/t of pro-
cessed milk, the specific consumption of water (Fig. 6) from
10 to 0.3 m3/t of processed milk and the specific need (Nu)
for human labor (Fig. 7) from 0 to 0.3 persons/t of processed
milk in production of different types of dairy products. The
correlation between the dependencies is within 0.89...0.99,
which indicates a strong relationship between them.
6. Discussion of results of studying the influence of
production conditions on the characteristics of project
configuration objects
The main scientific result is the defined influence of
the parameters of community milk processing shops on
the indicators of their use taking into account changing
production conditions. Studies on the changing production
conditions of milk processing at a community territory
made it possible to determine existence and duration of two
dairy production periods. The periods de-
termine modes of use of processing shops.
Experimentally studied tendencies of
changes in volumes of milk production vol-
umes in separate communities (Fig. 3, 4)
are the initial data for numerical mod-
eling of operation of processing shops at
a community territory. They ensure the
determination of trends in the changes of
indicators of their use at different parame-
ters of the specified shops.
The modeling of processing shops op-
eration at a community territory made it
possible to determine indicators of using
of processing shops (Fig. 5–7). It was es-
tablished that the increase in productivity
(qc) of milk processing shops from 0.5 to
20 t/day leads to the proportional de-
crease in the specific consumption of elec-
tricity (Fig. 5) from 116 to 10 kW/t, specific consumption
of water (Fig. 6) from 10 to 0.3 m3/t and specific need (Nu)
for human labor (Fig. 7) from 0 to 0.3 persons/t in pro-
duction of different types of dairy products. The correla-
tion ratio between the dependencies is within 0.89...0.99,
which indicates a strong relationship between them.
The obtained trends in changes in indicators of func-
tioning of milk processing shops at a community territory
(Fig. 2–7) underlie the justification of optimal modes for
the use of processing shops. The defined duration of periods
of milk supply for processing presented in Fig. 2 made it
possible to determine duration of one-shift and two-shift
organization of work in a processing shop during a calendar
year. It was established that there are two periods of milk
processing. The intensive one lasts from day 119 to day 301
within a calendar year, and the non-intensive one has two
half-periods ‒ from day 1 to day 118 and from day 302 to
day 365 within a calendar year. It is necessary to organize
work of shops in two shifts during the intensive period
of milk processing, and one shift ‒ in the non-intensive
period. The results of the studies are the basis for deter-
mination of cost indicators of the use of milk processing
shops at a community territory. In addition, the obtained
dependences underlie planning of resource expenditures
during operation of milk processing shops at the territory
of communities.
The substantiated stages and features of forecasting
of the functional indicators of milk processing shops at a
community territory compose the basis for definition of
trends in changes of the mentioned indicators at differ-
ent parameters of milk processing shops. The proposed
approach to forecasting of functional indicators of milk
processing shops in the territory of communities elim-
inates disadvantages of the existing ones due to taking
into account changing production conditions of operation
of milk processing shops at a community territory and
application of numerical modeling of operation of these
shops. The obtained results compose a basis for the de-
velopment of systems for support of decision-making on
planning of a configuration of milk processing shops at a
community territory. The obtained community statistics
Fig. 7. Dependence of specific need (Nu) for human labor on productivity (qc) of
a milk processing shop
Eastern-European Journal of Enterprise Technologies ISSN 1729-3774 6/3 ( 102 ) 2019
64
on milk production and characteristics of milk processing
shops form a database for the mentioned decision-making
support systems. The established trends of changes in
indicators of using of processing shops in the given pro-
duction conditions provide formation of a knowledge base
in the decision-making support system for planning of a
configuration of milk processing shops at a community
territory.
The proposed approach and the performed studies have
some disadvantages. First, the base of the approach is a series
of specific experiments for determination of characteristics
of production conditions. Second, the approach requires
numerical modeling. Quality numerical modeling requires
creation of a decision-making support system for planning
of a configuration of milk processing shops at a community
territory.
The proposed approach and the stages of the study
compose a basis for the decision-making support system for
planning of a configuration of milk processing shops at a
community territory. The system should provide numerical
modeling of operation of processing shops at a community
territory. This will speed up the process of managerial deci-
sion-making for determination of indicators of using of milk
processing shops under the given production conditions, and
improve their accuracy greatly.
The performed studies are useful for project managers
involved in the implementation of projects for creation
of milk processing shops at community territories and
community leaders, who plan to organize their own dairy
production.
7. Conclusions
1. The substantiated stages and features of forecasting
of functional indicators of milk processing shops at a com-
munity territory have five steps. They provide for modeling
of functioning of milk processing shops taking into account
changing production conditions. They ensure definition of
trends in changes in indicators of use of milk processing
shops at a community territory at different parameters and
taking into account changing production conditions. They
also provide formation of a knowledge base for a system of
support of management decision-making for planning of a
configuration of the mentioned milk processing shops.
2. It was established that the increase in productivity (qc)
of milk processing shops from 0.5 to 20 t/day leads to the
proportional decrease in the specific consumption of elec-
tricity from 116 to 10 kW/t of processed milk, specific con-
sumption of water from 10 to 0.3 m3/t of processed milk and
specific need (Nu) for human labor from 0 to 0.3 persons/t
of processed milk in production of various types of dairy
products. The correlation between the dependencies is with-
in 0.89...0.99, which indicates a strong relationship between
them. We studied changing production conditions and
characteristics of modular milk processing shops available
on the market. The identified trends in changes in indica-
tors of their use at a community territory take into account
changing production conditions and underlie determination
of cost indicators of the use of shops and planning of resource
expenditures in projects for creation of milk processing
shops at a community territory.
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