=Paper=
{{Paper
|id=Vol-3295/paper7
|storemode=property
|title=Project-based Management of the Production Equipment Maintenance and Repair Information System
|pdfUrl=https://ceur-ws.org/Vol-3295/paper7.pdf
|volume=Vol-3295
|authors=Oleksandr Holovin,Varvara Piterska,Anatoliy Shakhov,Olha Sherstiuk
|dblpUrl=https://dblp.org/rec/conf/itpm/HolovinPSS22
}}
==Project-based Management of the Production Equipment Maintenance and Repair Information System==
<pdf width="1500px">https://ceur-ws.org/Vol-3295/paper7.pdf</pdf>
<pre>
Project-based Management of the Production Equipment
Maintenance and Repair Information System
Oleksandr Holovina, Varvara Piterskaa, Anatoliy Shakhova and Olha Sherstiuka
a
    Odesa National Maritime University, 34, Mechnikov str., Odesa, 65026, Ukraine


                 Abstract
                 The relevance of the research is due to the need to create an effective maintenance and repair
                 planning system based on the development and implementation of methods that allow
                 ranking and selecting the most priority maintenance and repair activities, depending on the
                 degree of their impact on the current goals of the enterprise, taking into account financial,
                 labor, regulatory and other types of restrictions. The development of a maintenance and
                 repair management system is impossible without the use of information technology. A
                 solution of this type of questions is proposed based on the project management methodology,
                 which allows taking into account the uncertainty inherent in random events of failures of
                 technical systems. The purpose of this research is to develop a model for managing the
                 equipment maintenance and repair information system based on the use of project and project
                 portfolio management methodology. It has been established that an important advantage of
                 the methodology for planning maintenance and repair work, based on a project-based
                 approach, is its universal nature. It can be used in different industries, for different types of
                 equipment and companies of any level. An information system of indicators of the economic
                 efficiency of the equipment maintenance and repair system has been formed, which contains
                 six coefficients – plan fulfillment, cost intensity, cost proportionality, cost adequacy,
                 outsourcing and downtime. The results of the research are the following: the expediency of
                 using the project, program and portfolio management methodology in solving the problem of
                 developing a comprehensive strategy for managing the maintenance and repair information
                 system at enterprises was confirmed; a structural model for the formation of the architecture
                 of programs and portfolio of maintenance and repair projects was developed; a system of
                 criteria and an integral indicator of the effectiveness of the equipment maintenance and repair
                 strategy are proposed, which will allow the enterprise to reduce the cost of products when
                 using the proposed information system.


                 Keywords 1
                 Project-based management, information technology, maintenance and repair system,
                 production equipment, uncertainty


1. Introduction

    In Western industrialized countries, the system for arranging maintenance and repair (MAR) is
called the "maintenance system", and in Asian countries - the "conservation system" [1].
    According to various literature sources [2,3], the cost of MAR of complex systems is 10-15 times
higher than the cost of a new system. At the same time, the chosen strategy has a direct impact on the
total service life of the system, its reliability, safety and operational efficiency.

Proceedings of the 3nd International Workshop IT Project Management (ITPM 2022), August 26, 2022, Kyiv, Ukraine
EMAIL: holovinoleksandr@gmail.com (Oleksandr Holovin); varuwa@ukr.net (Varvara Piterska); avshakhov@ukr.net (Anatoliy Shakhov);
olusha972@gmail.com (Olha Sherstiuk)
ORCID: 0000-0003-0906-5778 (Oleksandr Holovin); 0000-0001-5849-9033 (Varvara Piterska); 0000-0003-0142-7594 (Anatoliy
Shakhov); 0000-0002-0482-2656 (Olha Sherstiuk)
            ©️ 2021 Copyright for this paper by its authors.
            Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
            CEUR Workshop Proceedings (CEUR-WS.org)
    At domestic enterprises, the general concept of maintaining equipment in good condition and
constant performance is still the preventive maintenance system (PMS), which has developed in
accordance with the requirements of GOST 18322-78 [4-5]. The obvious disadvantages of such a
strategy are economic losses due to the incomplete development of the resource by the time of MAR
and the lack of consideration of the enterprise production needs at any given time.
    The use of the "pure form" of the traditional PMS in today's conditions is complicated not only by
the lack of relevant standards. Measures of the PMS, from the point of view of ensuring operability at
the overhaul interval, are guaranteed, i.e. they are redundant. At the same time, the system assumes
that all of them must be carried out in full, but often (almost always) enterprises have neither time
reserves nor resources to perform such an “excessive” amount of work. In addition, as experience
shows, excessive execution of work on the PMS for various reasons can lead to a decrease in
reliability, for example, due to errors in the performance or violations in the running-in of nodes, non-
compliance with assembly technologies, etc.
    The key issue in creating an effective MAR planning system is the development and
implementation of methods that allow ranking and selection of the highest priority MAR activities
depending on the degree of their impact on the current goals of the enterprise (production indicators,
lost profits), as well as taking into account financial, labor, regulatory and other types of restrictions.
The development of a maintenance and repair management system is impossible without the use of
information technology. The solution of this type of problems is carried out on the basis of the project
management methodology, which allows to take into account the uncertainty inherent in random
events of failures of technical systems.

2. Analysis of Literature Data and Resolving the Problem

    Since failures of technical systems are random events, in the process of making decisions on the
implementation of certain work on MAR, the inherent uncertainty should be taken into account. One
of the potential models in this direction is presented in [6].
    Let the Gaussian random process X(t) be written as

                                           X(t) = A(t) + X(t),                                        (1)

where A(t) – deterministic, continuously differentiable function$
      X(t) – stationary ergodic normal random process with zero mean.
To predict the output of the process X(t) beyond a fixed level, some auxiliary process is used

                                           Y(t) = A(t) + Y(t),                                        (2)

where Y(t) – predictor for Xε(t), calculated at the moment (t – m), m>0, m is the chosen constant.

    If the value of Y(t) calculated at the moment t – m is more than some critical value uˆ, then a
warning is given about the possible exit of the process X(t) at the moment t beyond the level u (uˆ<u).
In [6], the properties of such a prediction procedure are studied: the probability of correct prediction
of X(t) going beyond a fixed level and the probability of a false alarm.
    Another example of describing the change in the state of the system from deterministic positions
(the aging model) is contained in [7], where the average aging over time is proposed to be described
using a deterministic equation.
    The inspection strategy for determining equipment wear, which is characterized by N levels of
quality, is presented in [8]. The author considers the technical system in the form of a semi-Markov
process with (N + 1) state, as a result of the analysis of which optimal policies are developed that lead
to minimal losses.
    The problem of determining the time of repair and replacement of failed equipment belongs to the
field of production resource management. Poor management due to the use of a suboptimal repair and
replacement policy can have significant financial consequences. The aim of [8] is to describe the
problem, analysis and results of the research related to determining the optimal repair and
replacement strategy for the organization that manages a large number of wooden pallets.
   During the operation of machine repair systems, it is important in plans to increase their reliability
in use to have suitable methods for state maintenance programs that take into account the
characteristics of the systems. An example of taking into account the features of the system (and its
elements) in the organization of maintenance and repair according to the state is indicated in [9]. The
Markov model is used to show the change in the states of the system.
      An interesting and unique model of aggregate replacement of elements in a multicomponent
system using the MAR strategy by state is given in [10]. With the mass use of homogeneous machine
repair systems, the results of this model can become widespread.
   The methodology of project-based management has become widespread in recent years due to a
number of obvious advantages [11-15], namely:
   • Increasing the service life of equipment;
   • More efficient performance of restoration repairs;
   • Reducing excess inventory;
   • Reducing the number of breakdowns and downtime;
   • Increasing the return on the company's fixed assets;
   • Effective budgeting of repairs;
   • Increasing the profitability of the company.
   However, in order to obtain these benefits at a particular enterprise, taking into account the
specifics of the types of equipment, its actual state, planned load, and the capabilities of existing
repair facilities, it is necessary to constantly optimize the content of repair projects and the portfolio
of projects of the repair unit, ensuring maximum efficiency.

3. The Purpose of the Research
   The purpose of this research is to develop a model for managing the MAR equipment system
based on information technology taking into account the use of project and portfolio management
methodology.

4. Materials and Methods of the Research
    The use of the traditional PMS in today's conditions is complicated, firstly, by the lack of the
necessary standards, and secondly, by their economic inexpediency. The activities of the PMS are
guaranteed, that is, they are redundant.
    At the same time, the system assumes that all of them must be carried out in full. At the same time,
in reality, enterprises do not have sufficient time reserves or resources to perform such an “excessive”
amount of work. In addition, as experience shows, excessive execution of work on the PMS for
various reasons can lead to a decrease in reliability, for example, due to errors in the work
performance or violations in the running-in of nodes, non-compliance with assembly technologies,
etc.
    These circumstances today lead to the fact that at many enterprises there are significant deviations
between the developed PMS plans and the actual scope of work on the MAR. In other words, PMS
work planning ceases to perform its main function, which is the optimal allocation of resources to
achieve production goals.
    Since the external and internal environment of the enterprise is constantly changing, the key issue
in creating an effective management system for MAR is the development and implementation of
information technology methods that allow ranking and selecting the most “important” projects in
terms of their impact on the current goals of the enterprise (production indicators, lost profits) .
    In accordance with the standards of the ISO 55000 Asset Management [16], the realization of the
value of an asset should be carried out by finding a balance between the benefits of owning it, the
costs of maintaining it and the risks inherent in the asset and associated with the ability to achieve the
goals related to it. In the field of MAR, the use of a risk-based approach in planning is aimed at
solving the following tasks:
   • Distribution of available resources between equipment;
   • Determination of terms of service, repair or replacement (modernization) of equipment;
   • Distribution of capital and operating costs of the enterprise repair department.
   One of the important advantages of the MAR planning methodology based on a project-based
approach is its universal nature. It can be used in different industries, for different types of equipment
and companies of any level.
   The main stages in the formation of projects for MAR of this type of equipment based on a risk-
based approach are schematically shown in Figure 1.




Figure 1: Model for the formation of projects for MAR
    The main task of the first stage is to describe the object by forming lists and diagrams of its
elements, for which the planning of measures for MAR will be carried out. Moreover, the description
of the object must have a hierarchical structure and take into account the links between the elements.
    At the next stage, a directory of typical defects and failures is formed. Each element of the object
is associated with its characteristic defects and failures, their probabilities of occurrence are
determined, as well as physical parameters.
    Damage arising in the event of failures or defects is assessed in the third stage. To do this, a
directory of typical damages is formed. Each failure and defect of an element is associated with
damages expressed in money equivalent.
    At the fourth stage, a directory of MAR measures is formed, which includes the norms for the
consumption of inventory items and the lead time for a certain impact (MI-1, MI-2, repair). Typical
impacts and individual operations are assigned to one or more failures and defects.
    At the final stage, the formation of strategies for managing the MAR system is carried out - a
program of projects for diagnosing, maintaining and repairing each type of equipment separately.
    Types of various MAR projects of equipment are shown in Figure 2. Each type of project, in
accordance with the standards adopted by enterprises, requires a variety of resources: material, labor,
financial, etc.




Figure 2: Types of equipment maintenance projects (MI – maintenance inspection)

  The project program is developed for each type of equipment separately and includes diagnostics,
maintenance, repair and modernization projects.
  The mission of such a program is to minimize the objective function:

                             𝐸 = 𝑍1 (𝑡) + 𝑍2 (𝑡) + 𝑍3 (𝑡) + 𝑍4 (𝑡) → 𝑚𝑖𝑛,                           (3)

where t – planning period;
      Z1 – mathematical expectation of the operating costs of the enterprise for the period t;
      Z2 – mathematical expectation of the costs of the enterprise for carrying out planned work on
MAR for the period t;
      Z3 – mathematical expectation of the costs of the enterprise for carrying out unscheduled work
on MAR for the period t;
      Z4 – lost profit of the enterprise due to downtime from the inoperable state of equipment for the
period t.

   The set of programs for projects of various types of equipment makes up the organization's project
portfolio. At the same time, if the production capacity of the repair department does not allow the
portfolio to be realized in full, the management decides on the possibility of transferring individual
projects or programs in the form of outsourcing. In the process of implementing the organization
portfolio, the actual state of the equipment is constantly monitored, which leads to the adjustment of
the planned indicators of programs and project portfolio.
   The block diagram of the project-based management system for MAR of equipment based on
information technology is shown in Figure 3.
   The information basis of the strategy is:
   • Directory of enterprise equipment;
   • Base of projects for MAR of each type of equipment;
   • Directory of resources required for the implementation of a particular project.
   In addition, the basis for the formation of the MAR program is the load graphs for certain types of
equipment, which are determined by the enterprise production plan. It is advisable to build such
graphs in the EAM environment adopted at the enterprise.
   As a result of the analysis of various program architectures, we choose the optimal function (1)
according to the minimum criterion. This architecture of the program allows calculating the list of
required resources.




Figure 3: Project-based strategy for the management of MAR of equipment

   The set of MAR programs for certain types of equipment determines the portfolio of projects for
the planned period of time. At the same time, if the enterprise does not have the necessary production
repair capacities for the implementation of a particular project (program), it can transfer them on an
outsourcing basis.
   In the process of implementing the portfolio, the diagnostics projects are carried out, that is, to
determine the actual technical condition of certain types of equipment. The results of these projects
constantly replenish the equipment base and make adjustments to the program of projects. The basis
for adjusting the program may be changes in the enterprise production plan (equipment loading
graph).
    An important element of the process management system for equipment MAR based on
information technology is a comprehensive assessment of its effectiveness. In our opinion, such an
assessment should be based on the following principles:
    • Implementation of the plan: the allocated limits for the portfolio of operations on MAR, both for
repairs on their own, and for the services of contractors, must be implemented in full [17];
    • Proportionality: MAR costs should be consistent with sales volumes and operating costs, not
ahead of their dynamics [18, 19];
    • Priority: the MAR portfolio should be primarily directed to the technological equipment of the
main production and key infrastructure facilities [20-23];
    • Financial rationality: MAR should be carried out in an optimal form, allowing to reduce non-
production costs and increase the financial efficiency of the organization [24-26];
    • Sufficiency: MAR should not impede the free movement of funds in both the inflow and outflow
of fixed assets;
    • Innovativeness: all work within the MAR portfolio should be carried out using modern high-
performance technologies;
    • Technical effectiveness: MAR of fixed production assets should lead to an increase in equipment
fault tolerance and a reduction in downtime of fixed assets [17, 27].
    Based on the above principles, quantitative indicators of economic efficiency have been
developed.
    Due to the fact that private indicators reflect economic phenomena of various scales, they should
be given a relative character for the purpose of objective comparison. It should also be noted that in
order to generalize the values of the coefficients, they should be given the same direction. The formed
system of indicators of the economic efficiency of the equipment maintenance and repair system
contains 6 coefficients.
    1. The coefficient of implementation of plan K 1 shows the degree of development of the
    allocated limits on the costs of MAR projects of the main production assets:

                                          1,     if 𝑍act ≤ 𝑍pl
                                   К1 = {𝑍pl                                                       (4)
                                           ⁄𝑍 , if 𝑍act > 𝑍act
                                             act

   where Zact – total actual costs for MAR projects of fixed assets, $; Zpl – the planned amount of
   costs for MAR projects of fixed assets, $.
   2. The cost coefficient K2 shows the amount of costs for MAR projects per 1 hryvnia of sales
   volume

                                                       𝑍ф
                                           К2 = 1 −      ⁄ ,                                       (5)
                                                          𝐷

   where D – sales value, $.
   3. The coefficient of proportionality of costs K 3 shows the ratio of the growth rate of operating
   costs and the growth rate of costs for the portfolio of MAR projects:

                                                  ⌊𝛥𝑍𝑜 −𝛥𝑍act ⌋
                                       К3 = 1 −                ,                                   (6)
                                                      𝛥𝑍act


   where ΔZo – growth rate of operating costs of the enterprise, %; ΔZact – growth rate of actual costs
   for MAR projects, %.
   4. The cost adequacy coefficient K4 shows the ratio of the replacement cost of fixed production
   assets to the amount of costs for the portfolio:

                                                    𝑍𝑎𝑐𝑡⁄
                                        К4 = 1 −         𝑆,                                        (7)
   where S – replacement cost of fixed production assets, $.
   5. The outsourcing coefficient K5 shows the proportion of equipment maintenance work
   performed by a contract to the total cost of the MAR portfolio:

                                                     𝑍𝑜𝑢𝑡
                                          К5 = 1 −       ⁄𝑍 ,                                       (8)
                                                           act

   where Zout – costs of payment for work performed by a contractor, $.
   6. The downtime coefficient K6 shows the ratio of equipment downtime due to its inoperable
   state to the planned working time fund of this unit:

                                                       Т𝑑𝑡
                                            К6 = 1 −     ⁄Т ,                                       (9)
                                                           ∑


   where Тdt – equipment downtime, h.; Т∑ - total planned load of this type of equipment.

    The formulas for calculating the coefficient based on the conditions of their dimensionlessness and
standardization are proposed. In addition, when calculating all performance indicators, the following
relation is fulfilled:
                                       0 ≤ К𝑖 ≤ 1 ∀ 𝑖 = 1, … 6                                     (10)

  This allows us to determine the integral indicator of the effectiveness of the MAR strategy as the
Euclidean distance K according to the following formula:

                                                    ∑6 𝐾 2
                                             К=√ 1 𝑖                                               (11)
                                                       6


The results of calculating the strategy performance indicators are presented in Table 1 and Figure 4.

Table 1
Calculation of MAR equipment strategy performance indicators
                   Initial data                                  Calculation results
       Indicator                 Value                  Indicator                    Value
          Zact,$                  8500                     К1                        0,965
          Zpl,$                   8200                     К2                        0,888
          D, $                   76000                     К3                        0,818
        ΔZact,%                   3,25                     К4                        0,943
         ΔZo,%                   2,657                     К5                        1,000
           S,$                  150000                     К6                        0,996
         Zout,$                     0
          T ∑, h                  2400                      К
         Тdt, h                    10

5. Conclusions
   1. The expediency of using the methodology of managing projects, programs and portfolios in
solving the problem of developing a comprehensive strategy for managing the MAR system at
enterprises has been confirmed.
   2. А model for managing the MAR equipment system based on information technology has been
developed taking into account the use of project and portfolio management methodology.
   3. A structural model for the formation of the architecture of programs and a portfolio of MAR
projects aimed at improving the organization efficiency has been developed.
Figure 4: Analysis of the effectiveness of the MAR equipment strategy

   4. A system of criteria and an integral indicator of the MAR equipment strategy effectiveness are
proposed, which will allow the enterprise to reduce the cost of products by 2–3%.

6. References

[1] V. Khristianovsky, V. Shcherbina, Economic-Mathematical Methods and Models: Theory and
     Practice, DonNU, Donetsk, 2010.
[2] G. Pekelis, B. Gelber, Technology of repair of metal-cutting machine tools, Engineering, Kiev,
     1970.
[3] A. Yashura, System of maintenance and repair of general industrial equipment, ENAS, Kiev,
     2012.
[4] A. Pavlov, P12 Project portfolio management based on PMI The Standard for Portfolio
     Management R, Presentation of the methodology and recommendations for application, 2nd ed.,
     BINOM Knowledge Laboratory, 2015.
[5] H. Asher, H. Feingold, Is there repair after failure?, in: Proceedings of the Annu. Reliab. and
     Maintainab. Symp. Los Angeles, Calif., 1978. New York, N.Y., 1978, pp.190 – 197.
[6] G. Lindgren, Prediction of level crossings for normal processes containing deterministic
     components, Adv. Appl. Probab. 11(1) (1979) 47-54.
[7] C. Dorgan, D. Ermer, A degradation reliability models, in: Proceedings of the Annu. Reliab. and
     Maintainab. Symp. Los Angeles, Calif., 1978. New York, N.Y., 1978, pp. 510–518.
[8] Z. Kander, Inspection policies for deteriorating equipment characterized by N quality levels,
     Nav. Res. Log. Quart 25(2) (1978) 243–255.
[9] C.H. Lanzenauer, D.D. Wright, Developing an optimal repair replacement strategy for pallets,
     Nav. Res. Log. Quart 25(1) (1978) 169–178.
[10] B. Sivazlian, J. Mahoney, Group replacement of a multicomponent system which is subject to
     deterioration only, Adv. Appr. Probab 10(4) (1978) 867 – 885.
[11] V. Pasichnyk, N. Kunanets, IT education and IT business in Ukraine: Responses to the modern
     challenges, in: 2015 Xth International Scientific and Technical Conference "Computer Sciences
     and Information Technologies" (CSIT), 2015, pp. 48-51, doi: 10.1109/STC-CSIT.2015.7325428.
[12] A. Ivankevich, V. Piterska, A. Shakhov, V. Shakhov, V. Yarovenko, A Proactive Strategy of
     Ship Maintenance Operations, in: 2019 IEEE 14th International Conference on Computer
     Sciences and Information Technologies (CSIT 2019), Lviv, 2019, pp. 126–129. doi:
     10.1109/STC-CSIT.2019.8929741.
[13] V. Piterska, A. Shakhov, O. Lohinov, L. Lohinova, The Method of Transfer of Research Project
     Results of Institution of Higher Education, in: 2019 IEEE 14th International Conference on
     Computer Sciences and Information Technologies (CSIT), 2019, pp. 77-80, doi: 10.1109/STC-
     CSIT.2019.8929887
[14] V. Pіterska, S. Rudenko, A. Shakhov, Development of the Method of Forming of the
     Architecture of the Innovation Program in the System "University-State-Business", International
     Journal of Engineering & Technology (UAE) 7(4.3) (2018) 232–239. doi:
     10.14419/ijet.v7i4.3.19793/
[15] A. Rzheuskyi, A. Shakhov, V. Piterska, O. Sherstiuk, O. Rossomakha, Management of the
     technical system operation based on forecasting its “aging”, in: CEUR Workshop Proceedings
     2565, 2020, pp. 130–141.
[16] N. Kunanets, A. Kazarian, R. Holoshchuk, V. Pasichnik, A. Rzheuskyi, Information support of
     the virtual research community activities based on cloud computing, in: International Scientific
     and Technical Conference on Computer Sciences and Information Technologies,
     CSIT 2018, 2018, pp. 199–202.
[17] ISO 55000:2014. Asset management — Overview, principles and terminology // Электронный
     ресурс https: //files.stroyinf.ru/Data/588/58869.pdf.
[18] E. Barzilovich, V. Kashtanov, Organization of service with limited information about the
     reliability of the system, Radio, Kiev 1975.
[19] O. Zachko and D. Kobylkin, Discrete-Event Modeling of the Critical Parameters of Functioning
     the Products of Infrastructure Projects at the Planning Stage, in: 2018 IEEE 13th International
     Scientific and Technical Conference on Computer Sciences and Information Technologies
     (CSIT), 2018, pp. 152-155, doi: 10.1109/STC-CSIT.2018.8526629.
[20] Bushuyev, D. Bushuiev, V. Bushuieva, Interaction Multilayer model of Emotional Infection with
     the Earn Value Method in the Project Management Process, in: 2020 IEEE 15th International
     Conference on Computer Sciences and Information Technologies (CSIT), 2020, pp. 146-150,
     doi: 10.1109/CSIT49958.2020.9321949.
[21] S. Bushuyev, I. Babayev, J. Babayev, B. Kozyr, Complementary Neural Networks for Managing
     Innovation Projects, in: 2019 IEEE International Conference on Advanced Trends in Information
     Theory (ATIT), 2019, pp. 393-396, doi: 10.1109/ATIT49449.2019.9030454.
[22] S. Bushuyev, A. Puziichuk, Development organizational structure for value-oriented
     reengineering project of construction enterprises, in: 2021 IEEE 16th International Conference
     on Computer Sciences and Information Technologies (CSIT), 2021, pp. 367-370, doi:
     10.1109/CSIT52700.2021.9648758.
[23] A. Sagaydak, V. Torskiy, Ship-Cargo Interface: Concept of Optimization, Using Risk
     Assessment Methods and Network Data Exchanging Technologies. TransNav, the International
     Journal on Marine Navigation and Safety of Sea Transportation 15(2) (2021) 359-364.
     doi:10.12716/1001.15.02.12.
[24] N. Veretennikova and N. Kunanets, Automated System of Information Support of Virtual
     Research Team, in: 2017 12th International Scientific and Technical Conference on Computer
     Sciences and Information Technologies (CSIT), 2017, pp. 20-23, doi: 10.1109/STC-
     CSIT.2017.8098727.
[25] R. Holoshchuk, V. Pasichnyk, N. Kunanets, N. Veretennikova, Information modeling of dual
     education in the field of IT, in: Advances in Intelligent Systems and Computing, 2020, pp. 637-
     646.
[26] A. Bomba, N. Kunanets, M. Nazaruk, V. Pasichnyk, N. Veretennikova, Model of the Data
     Analysis Process to Determine the Person’s Professional Inclinations and Abilities, in: Advances
     in Intelligent Systems and Computing, 2020, pp. 482-492.
[27] O. Duda, N. Kunanets, O. Matsiuk, V. Pasichnyk, N. Veretennikova, A. Fedonuyk, V. Yunchyk,
     Selection of Effective Methods of Big Data Analytical Processing in Information Systems of
     Smart Cities, in: Proceedings of the 2nd International Workshop on Modern Machine Learning
     Technologies and Data Science (MoMLeT+DS 2020), Volume I: Main Conference, Vol. 2631,
     pp. 68-78.

</pre>