=Paper=
{{Paper
|id=Vol-2753/paper42
|storemode=property
|title=Simulation of Human-Operator Behavior in Solving Intellectual Problems during Control of Technological Processes in Stresses
|pdfUrl=https://ceur-ws.org/Vol-2753/short14.pdf
|volume=Vol-2753
|authors=Roman Kaminskyy,Natalia Kryvinska
|dblpUrl=https://dblp.org/rec/conf/iddm/KaminskyyK20
}}
==Simulation of Human-Operator Behavior in Solving Intellectual Problems during Control of Technological Processes in Stresses==
https://ceur-ws.org/Vol-2753/short14.pdf
Simulation of Human-Operator Behavior in Solving Intellectual
Problems during Control of Technological Processes in Stresses
Roman Kaminskyy1, Natalia Kryvinska2
Lviv Polytechnic National University, Lviv, 79013, Ukraine;
Comenius University in Bratislava, Bratislava, 81499, Slovakia.
Abstract
The mathematical model of the human-operator of technological process from the point of view of
the mathematical systems theory is developed. The apparatus of set theory was used for modeling.
The model takes into account the influence of the human factor on the quality of process control.
The concept of stress-resistance of the human operator is considered. The stress resistance index is
introduced and the geometric interpretation is given. The model of exit of the person-operator from
a stressful condition which considers its individuality is resulted.
Keywords 1
human operator, process control, operator stress, learning curve.
1. Introduction
One of the most common human-machine interfaces of automated control systems, information
retrieval systems and information processing systems is the "human-computer" linkage, which
practically provides a consistent presentation of information to users. The human-machine interface is
in fact fully responsible for the information provided, and therefore must be reliable, accurate and
efficient. In the systemic aspect, the pair "human - computer" is a system formed by a combination of
subsystems of specific psychophysical features and functional states of human associated with the
processing of various information, and the subsystem of technical capabilities of modern computer
technology. The role of technology is extremely high efficiency of search, special preliminary and
various basic processing of the necessary information, as well as its storage, transmission, conversion
and presentation in various forms.
The modern computer equipment is characterized by a high degree of reliability, has a significant
speed, huge amounts of memory, which allows you to solve the problems in various domains. In
practice, the failure of complex production systems due to the failure of computer equipment is
becoming less common and mainly for non-technical reasons - viruses, inappropriate or poor quality
software and inconsistency of computer equipment used in this class of tasks. This should also include
its service by low-skilled personnel.
Therefore, the concept of reliability, efficiency, adequacy of the solution for the human-machine
interface is mainly expressed by the human factor and in fact all responsibility for the decision lies
with the operator, often even in situations where unforeseen reasons out of order technique.
The main adverse factors for the operator are extreme situations, stress, biorhythms, sleep and
neurosis, which actually act as a consequence of the previous, and which modern science considers as
a boundary between health and mental illness associated with functional disorders in the body.
Different circumstances force a person to adapt quickly and fully and maintain high efficiency
regardless of changes in the environment.
IDDM’2020: 3rd International Conference on Informatics & Data-Driven Medicine, November 19–21, 2020, Växjö, Sweden
EMAIL: kaminsky.roman@gmail.com (R. Kaminskyy); natalia.kryvinska@uniba.sk (N. Kryvinska);
ORCID: 0000-0003-3678-9229 (N. Kryvinska)
© 2020 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)
One of the important tasks of the problem of restoring the functional state of the human operator,
i.e. overcoming stress, is to study the processes of adaptation of this category of workers as operators.
The activity of these workers in the conditions of growth of technical progress becomes more and
more difficult, becomes more responsible and is accompanied by considerable nervous and mental
pressure of a cognitive resource, creative forces and abilities.
The purpose of this study is to develop a mathematical model of the output of the human operator
from a stressful situation, which reflects the general content of his professional activity in the human-
machine interface of process control.
2. Related works
As a rule, various working situations in human activity, in particular the human operator of
technological processes create preconditions for violation of modes of human-machine systems,
occurrence of erroneous actions, threat of emergence of emergency situations. Research [1] is devoted
to the study of such situations in order to model human behavior. The influence of stressful situations
on the human body and behavior during the management of technological processes is analyzed [2].
In [3] the materials of experimental-theoretical research of information stress of the human operator
as one of the types of professional stress are presented. Modern methods and tools for determining
and diagnosing emotional stress are given in [4].
Modeling of human operator dynamics plays an important role in process control and is reflected
in [5]. The study of the reliability of the human operator is considered in [6]. Important for the
admission of a person to the management of the technological process is its preparation primarily in
terms of stress resistance, and it is in this regard, of interest is the study presented in [7]. The decisive
role in modeling human behavior is played by the mathematical apparatus of building a model of
human-machine interface as a holistic intelligent process control system. The most common system
approach for building a human-machine interface model is work [8]. Taking into account the behavior
of the functional state of the operator in models of behavior is of great importance not only in the
management of peaceful technological process, but also for the control of military equipment, in
particular unmanned aerial vehicles [9]. The effective operation of the human-machine interface in the
environment is considered in [10].
Stress-related situations play an important role in the study of operator activity. Stress in the
workplace has been the subject of increased attention by researchers in various countries. The
dynamics of the spread are detailed in the report of the International Labor Office [11].
The influence of distracting situations, as shown in [12], leads to a decrease in the efficiency of the
operator, which indicates that in the models of the operator can not be considered constant. The
relationship between psychological and biological aspects is considered in [13]. Individual differences
in threshold and duration of both internal and external stimuli for stress are given in [14]. The authors
[15] present human-machine systems in which the human factor plays an important role, and therefore
human failure can be dangerous.
Modeling a person's way out of a stressful situation is considered by many researchers. The exit
curve from the stress state of the human operator is quite good, in terms of the nature of this process
can be described by the learning curve given in [16]. The learning curve is an almost universal curve
and is widely used in various industries [17], economic indicators and in terms of reducing production
costs.
3. The materials and methods
3.1. Modeling of the process controlled by the person-operator
The subsystem of psychophysical functional features, i.e. the human operator, in most human-
machine interfaces is a highly qualified specialist, well acquainted with the class of problems,
methods of solving them and approaches and principles of interpretation of the results. However, a
person has certain features, objective and subjective, related to the central nervous system, psyche and
physiology of the whole organism, which must be taken into account when organizing its activities in
the "human-computer" as part of the typical or specialized complex and multifunctional systems.
Objective features include the characteristics of the psychophysiological state of man and the
psychophysical parameters of the organs of interaction with the environment, which directly or
indirectly participate in the work of the human operator. Subjective features, which to some extent are
determined by the functional state of the organism, are manifested in the interaction with the
environment, namely in relation to the work performed, in the assessment of the work situation and in
the choice of decisions made by the operator.
Operator activity can be presented as follows. Suppose that over time [ 0, T ] a human operator
controls some technological process Z t . Human management of such a process includes the most
typical aspects and components of real operator activity. Information display systems include
monitors, mnemonics, information boards. During the process of technical means of the given
technological process and from the environment in regular or casual moments of time ti such that
ti T
where T ti : ti 0, T , i 1, N , some characteristic vector of the controlled
indicators Z t - this technological process, i.e. real values of the controlled parameters is fixed. The
values of these parameters obtained by various measuring and controlling means must meet the
specified standards of the technological process. Information about the state of the controlled
technology and the environment is provided to the operator on the monitor screen, information board,
etc. For changes in these parameters, i.e. their deviation, the operator analyzes the situation and makes
the appropriate decision. The decision made by the operator is made by implementing the necessary
commands in the field of the control panel.
Thus, the human operator and the technical means of displaying information and executing
commands form the control link of virtually any technological process. They are a holistic system
called a human-machine interface.
Any technological process operates within a set of predefined normative and instructional values
of parameters - G which determine the optimal operation of the controlled technology Z t .
However, in real working situations the technological process is characterized by a set - G real
values of these parameters. The values of these parameters determine the current state of this
technology.
In the process of work, at arbitrary moments of time ti , the operator receives information about
the progress of the technological process Z t in the form of reflections of these parameters on the
information field of the control panel.
Simultaneous display of changes in the information field can be represented by an image of the
frame state of the controlled process Z ti . Each such frame xi X , where
X xi : xi x ti , ti T , i 1, N ,
where N is the number of parameter changes.
A highly qualified experienced operator uses for comparison and analysis the image xi X
formed in his memory, which meets the established standards. In other words, analyzing the image
xi and xi* the operator identifies the current situation, selects or constructs and makes the
appropriate decision y j Y ,
Y y j : y j y t j , j 1, N , t j ti , ti , t j , [ 0, T ] ,
where is time for decision making y j .
The decision y j is realized by operator using set of commands u h , with control vector
u j u1, , uh , u j U , where U – set of control command, h 1, 2, – number of
commands in situation j .
Constant nervous and mental stress, a sense of responsibility and duty, long-term work naturally
create a significant psychophysical load on the operator. At the same time, cognitive and motor
functions are slowed down, visual search deteriorates, efficiency and infallibility of actions decrease,
and significant nervous and mental overstrain occurs. Despite the large reserve and adaptive
capabilities of man, this condition has a negative impact on the quality of his work.
Therefore, the efficiency of the operator must be linked to specific operating conditions ck . The
set of these states can be represented as follows:
C ck : ck c tk , tk tk 1 tk ; tk , tk 1 [0, T ] .
General model requirements for the operator and in fact its activities in the control technology
system Z t can be formulated as follows: detect on the information field of the control panel of the
technological process Z t , represented at the time ti of the image-frames xi X and compensate
for existing deviations of the values of current parameters g i from the mode gi , by selecting the
appropriate vector of commands u h , the implementation of which will return the technology Z t
for the mode. Moreover, the choice, adoption and implementation of the decision in this situation
must have the maximum probability p 1 with minimal time 0 , ie
X gi gi
p1
optU x ti , c t j ti , y t j ,
0
where xi - the running frame of the information field, c t j ti c - the time of choice of
solutions and commands, y t j - the decision.
This expression reflects the main requirement for the intellectual activity of the operator, namely,
the optimization of the modes of the process controlled by him.
Thus, the human-machine interface as a system S can be represented by a relation S X Y ,
and given its existence at many points in time T, which are observed, and changes in the functional
state C of the human operator, we can represent it as a tuple:
S X , Y , C, , , T .
Its elements reflect all the main components of the technological process:
X xi : xi x ti , i 1, 2, , ti T
is a set of input frames that reflect the actual state of the technological process, provided on the
monitor for processing;
Y y j : y j y t j , j 1, 2, , t j T ,
a set of decisions made by the human operator, which compensate for changes in parameter values
and ensure the normal course of the technological process;
C ck : ck c tk , k 1, 2, , tk T
the set of functional states of the human operator during the control of this process.
The behavior of such a system is significantly determined by the change in functional state under
the influence of input information, ie
Ct X t Ct , t , t T , t t , t t t 0 ,
if at the time the operator was in a state Ct and at that moment the image of a frame xi t X t with
change of parameters for which the corresponding decision does not exist in memory of the operator
is given. In this situation, the person begins to quickly look for a way out of the situation, resulting in
a nervous breakdown and at the moment t it is already in a state Ct . The transition time from state
to state is very short.
For normal operating situations, the function of obtaining the result of the operator's actions,
depending on the input information X t and the state Ct in which the operator is, has the following
form:
t : t t , Ct X t Yt , t , t , t T , t t t , t t 0 .
Important in this model is the set of time points at which the beginnings and endings of all
changes in the system:
T ti : ti 1 ti , ti 1 ti 0, i 1, 2, . .
The moment of time means the moment of acceptance, but rather its implementation by a set of
commands.
Time moment t means moment of decision making.
The concept of the state of the human-machine interface can be formally presented as follows:
K
C Ck : Ck C , Ck Cl , k 1, K ,
k 1
where k 1 – for working environment parameters, k 2 – for algorithms and software
parameters, k 3 – for psyho-physical state of human-operator. So, the attention is to state k 3 .
3.2. The concept of stress resistance of the human operator
Stress is any external influence on the body that requires an adequate response by mobilizing
certain protective forces. There are three phases of stress (Figure 1).
The first phase is that the body mobilizes the defenses and supplies enough energy at the right
time for an adequate response.
In the second phase, the body realizes its potential. However, this condition can not be long
because it quickly depletes the body's reserves, disarms it, and this leads to the breakdown of
adaptation mechanisms.
The third phase is post-stress, which is characterized by a certain type of relief and mostly short
duration, although in many cases this phase is quite long - days, weeks and even months.
Figure 1: General view of the dynamics of the reaction to stress and recovery from stress
The authors of this study proposed an approach to establish the value of the stress indicator of
staff h . The basis of this indicator are the following four general characteristics, namely: the human
operator (two), the working environment and the amount of information about changes in the
parameters controlled by the operator, the technological process. Such characteristics are:
Q - level of qualification of the human operator,
D - experience in managing similar technological processes,
E - discomfort of the working environment,
W - the amount of information with changed parameters.
The relationship between these characteristics is as follows:
QD
h .
E W
The content of this indicator is that a well-trained, ie highly qualified operator Q with
extensive practical experience D is quite difficult to "surprise". Such an operator is very quick to
navigate in possible work situations, even when there is significant discomfort in the work
environment E , and the amount of information about changing parameters W is quite large.
In other words, the value of the stress-resistance h indicator of the human operator significantly
depends on the state of the working environment and the value of the given volume of the changed
parameters that characterize the technological process managed by him.
An important point regarding the use of this indicator is that the values of all four values can be
determined on a scale of, for example, expert assessments. Obviously, they can also be measured as
expert scores on a scale. Although such assessments are very general, in the systems of professional
selection, training and certification of operator personnel, they are quite sufficient to identify
operators and cluster them by level of training.
3.3. Model of operator exit from stress
The model of the operator's exit from the stress state is easily represented by a differential
equation
dh
k hmax h ,
dt
where k is the coefficient of proportionality.
This equation characterizes the growth rate of stress resistance h from the time t j when the
operator made a decision.
The following differential equation is an equation with separable variables, so its solution can be
easily found in general:
hmax h Ce kt
.
The constant C can be found from the initial condition: h t j 0 V . Therefore,
C hmax V . Here the moment t j 0 means that the counting of the argument of the curve of the
operator's exit from the stress state refers to this moment.
The operator's exit curve from the stress state is called the "learning curve", but its application is
much wider. Thus, this curve in our case is described by the following formula:
h t hmax hmax V ekt
.
The parameter V means the minimum level of stress resistance, at which the operator is still able
to make and implement an adequate decision (save the process). The difference hmax V
characterizes the stress potential of the human operator.
If V 0 the operator needs to stop controlling the process.
4. Conclusions
The presented models of human-machine interface, indicator of human operator stress and
operator exit from stress can be interpreted as an attempt to formalize operator activity in human-
machine control systems of many types of technological processes. From a practical point of view,
these three models are focused on the use of quantitative indicators and characteristics, not only of the
human operator, but also to some extent relate to both the technological process and the environment.
The model of human-machine interface, implemented by the apparatus of set theory, gives an
idea of the technological process in this way.
First, the input information is clearly defined by a set of frame images, namely: possible number
of adverse events (changes in process parameters). And these events, although they can be dangerous
in different ways, but in fact their danger unites them in a set. In addition, they can be very different,
but they all characterize this process, although at different times in its operation.
Secondly, the initial result of such a human-machine interface is a set of commands that
implement the decisions made by the operator. The analysis of such sets of teams as well as the
decisions implemented by them gives grounds to assess the professional level and efficiency of this
operator in relation to the process managed by him.
Third, an extremely important point of such a model is the formal consideration of the state of
the system - the human-machine interface. Such a system mapping draws attention to the human
operator, indicating that he is a weak link in the whole system. In other words, the "human operator"
component of the process control system requires appropriate attention from the organization of its
operation. This in turn stimulates the selection, training and certification of operator personnel.
The proposed indicator of stress resistance of the human operator, already under the condition of
using the appropriate scale of expert evaluation of its four elements, provides an opportunity to select
the best from the group of candidates for the position of operator. This indicator, given the
quantitative values of its elements, the relationship between the professional level of the operator, the
external environment and the amount of information provided.
The model of the dynamics of the operator's exit from the stress state follows from the results of
the analysis of the stress resistance indicator. Analysis of numerous data on human stress shows that
the way out of stress is not instantaneous, but lasts for some time. In addition, the dynamics of the
restoration of a person's functional state to normal is usually nonlinear and monotonous, and there
may be a final nervous and mental stress, which accelerates his fatigue.
These results can be used in various laboratories and institutions for the organization of
professional selection of applicants for the staff of operator personnel, their training and retraining, as
well as for the certification of the qualification level. It is obvious that in such cases an expert
commission should be formed and the characteristics of a specific technological process and
requirements to it should be taken into account.
5. References
[1] Kaminsky, R., Mochurad, L., Shakhovska, N., & Melnykova, N. Calculation of the Exact Value
of the Fractal Dimension in the Time Series for the Box-Counting Method. In 2019 9th
International Conference on Advanced Computer Information Technologies (ACIT) 2019, 248-
251.
[2] Morushko A., Khymytsia N., Shakhovska N. Determining the Psychological Portrait of Members
of Web Communities through Socionic Analysis. Ceur, Vol-2616, 112-124
[3] Karp Ch. Unstressing intemperate models: how cold stress undermines mouse modeling. Journal
of Experimental Medicine, 2012, 209.6: 1069-1074.
[4] Havlikova M., Jirgl M., Bradac Z. Human Reliability in Man-Machine Systems. / Procedia
Engineering 100, 2015, 1207 – 1214.
[5] Jiacai Huang, Yang Quan Chen, Haibin Li, Xinxin Shi. Fractional Order Modeling of Human
Operator Behavior with Second Order Controlled Plant and Experiment Research[J]. IEEE/CAA
Journal of Automatica Sinica, 2016, 3(3): 271-280.
[6] Marie Havlikova, Miroslav Jirglb, Zdenek Bradacc. Human Reliability in Man-Machine
Systems. 25th DAAAM International Symposium on Intelligent Manufacturing and Automation,
DAAAM 2014/ Procedia Engineering Volume 100, 2015, 1207-1214
[7] Sandhu, M. M., Javaid, N., Jamil, M., Khan, Z. A., Imran, M., Ilahi, M., & Khan, M. A.
Modeling mobility and psychological stress based human postural changes in wireless body area
networks. Computers in Human Behavior, 51, 2015, 1042-1053.
[8] Mesarovic M. and Yasuhiko Takahara. General systems theory: Mathematical foundations //
Mathematics in science and engineering Volume 113, Academic Press New York, San Francisco,
London 1975. 316 p.
[9] Kryvenchuk, Y., Helzynskyy, I., & Danel, R.Synthesis Сontrol System Physiological State of a
Soldier on the Battlefield.ceur, Vol-2488, 2019, 35-46
[10] Kralikova R., Dzunova L., Pinosova M., Wessely E.,& Koblasa F. Man-Machine-Environment
System Analyses and Impact of Environment Factors to Productivity and Health of Employees,
Proceedings of the 30th DAAAM International Symposium, 2019, 10131-10138,
[11] B. Katalinic (Ed.)Workplace Stress: A collective challenge – Report, 04 April 2016, 978-92-2-
130642-9, https://www.ilo.org/safework/info/publications/WCMS_466547/lang--en/index.htm
[12] Kopyt A., Zużewicz K., Bartuzi P. Experimental identification of a mathematical model of
human operator working under mental stress. Acta of Bioengineering and Biomechanics. 19(3),
2017, 177 – 185.
[13] Savic D., Knezevic G. and Opacic G. A mathematical model of stress reaction: Individual
differences in threshold and duration. Psychobiology 2000, 28 (4), 581-592.
[14] Peter F. W. Mathematical modeling of learning. Journal of research in science teaching. England,
21 (9), 1984, 953-955.
[15] Anzanello M., Fogliatto F. Learning curve models and applications: Literature review and
research directions Federal University of Rio Grande do Sul (UFRGS), Av. Osvaldo Aranha, 99 -
5 andar, Porto Alegre e CEP 90.035-190, Rio Grande do Sul, Brazil.International Journal of
Industrial Ergonomics 41, 2011, 573 – 583.
[16] Levente Malyusz and Attila Pem / Predicting future performance by learning curves. Procedia -
Social and Behavioral Sciences 119, 2014, 368 – 376.
[17] Vytautas Kleizaa, Justinas Tilindisb. An almost learning curve model for manual assembly
performance improvement. Nonlinear Analysis: Modelling and Control, 21 (6), 2016, 839 – 850.