=Paper=
{{Paper
|id=Vol-3091/paper07
|storemode=property
|title=Design of neuro-simulation system in situational management of control and quality assessment for complex production assembly system
|pdfUrl=https://ceur-ws.org/Vol-3091/paper07.pdf
|volume=Vol-3091
|authors=Alexander Zolkin,Evgeniy Lavrov,Irina Zaitseva,Alexey Bityutskiy,Vadim Mironchuk
}}
==Design of neuro-simulation system in situational management of control and quality assessment for complex production assembly system==
https://ceur-ws.org/Vol-3091/paper07.pdf
Design of neuro‐simulation system in situational management of
control and quality assessment for complex production
assembly system
A. L. Zolkin 1, E. A. Lavrov 2, I. N. Zaitseva 3, A. S. Bityutskiy 4 and V. A. Mironchuk 5
1
Computer and Information Sciences Department, Povolzhskiy State University of Telecommunications and
Informatics, Samara, 443010, Russia
2
Computer science department, Sumy State University, Sumy, 40007, Ukraine
3
Department of Physics, Radio Engineering and Electronics, Bunin Yelets State University, Lipetsk oblast, Elets,
399770, Russia
4
"Invent Technology" LLP, Almaty A10E5P4, Kazakhstan
5
Department of Economic Cybernetics, Federal State Budgetary Educational Institution of Higher Education
“Kuban State Agrarian University named after I.T. Trubilin”, Krasnodar, 350044, Russia
Abstract
The specific challenge for application of developed system of situational input in control
process is generalized by authors, flowgraph model is demonstrated, synthesis methodology is
generalized and assessment of effectiveness based on group of parameters of regression nature
to implemented neuro-fuzzy regulation system is described. Decomposition and structural
analysis of specificity of application of implemented model, its characteristic function and
balance-model (before implementation) are described. The steps of development of this
complex technology are reviewed.
Keywords 1
Neuro-simulation, fuzzy control, situational control, non-direct input, additive technologies,
automation of technological production
1. Introduction
The process of differentiation of control for complex technical systems – the searching of regulation
method for control system in the context of application in automated assembly line for system of
elevator type with complicated multi-position tools of control is used in this study as studying object
and formalization of object of challenge definition [1].
The organization and technical complex performing discrete number of operations on unlimited
(analogue) space of input values or parameters accepting and registering by system of perception (input
system) is meant under complex technical system.
Control of complex technical systems is one of the key challenge cybernetic and reviewed as specific
goal of cybernetic cooperation. Complexity of goal is explained with object and structure variety of
such complexes which are socially oriented by assignment of some systems [2,3].
Proceedings of MIP Computing-V 2022: V International Scientific Workshop on Modeling, Information Processing and Computing,
January 25, 2022, Krasnoyarsk, Russia
EMAIL: alzolkin@list.ru (A. L. Zolkin); prof_lavrov@mail.ru (E. A. Lavrov); irina-zai73@mail.ru (I. N. Zaitseva); bsalexey@mail.ru
(A. S. Bityutskiy); va_mironchuk@mail.ru (V. A. Mironchuk)
ORCID: 0000-0001-5806-9906 (A. L. Zolkin); 0000-0001-9117-5727 (E. A. Lavrov); 0000-0003-3415-2099 (I. N. Zaitseva); 0000-0002-
2754-1531 (A. S. Bityutskiy) 0000-0001-9160-4704 (V. A. Mironchuk)
© 2022 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)
2. Problem statement
In reviewed study we have to characterize in form of challenge statement the process of functionality
of technical complex of control of elevator stations control on the warehouse of big distributor. We
should assign the complexity of reviewed system from the position of structural analysis: it is assumed
the logistic of item from point “A” to point “B” by cross-movements in space taking into account the
switching on different types of surface and production breaks (such challenge is solved in general by
traditional systems of automotive control systems) as well as role-based significance of combining the
control way with moving the elevator line (line system) and with assurance of unity of verification of
assembly process is emphasized and stated [4]. Even though the reviewed models [5,6,7] of application
of situational control allow to assign the conditions of company’s operation and evaluate the potential
risks but they do not define the technical organization on already presented control systems. However,
the reviewed technical system is significantly complicated from the position of working principles.
3. Research questions
Assembly system of company has a form of iteration algorithm of technology on additive
(composition) type, i.e. consists of some independent processes connecting with each other through
delegation tool on the stage of assembly. The main time period company is involved in logging of wood
incoming from neighboring sites where the system of processing the raw material – wood and different
materials (epoxide, wood dust, round wood) – is performed.
Before going to the optimization challenge description it is required to reduce the informational
entropy about studying object – assembly line [8].
Before reviewing the system of assembly lines (having the form chain of contours of production
associated on functional presentation as well as on structure one) we should to explain the common
characterization function on the example of specific line.
For this purpose, we should refer to formalized presentation of graph-transferring line of company
on Figure 1.
Figure 1: Flowgraph model of production of specific type of product (parquet block from ash in
polygonal format)
Perform the decomposition of flowgraph model and some summarizing of group of activating
functions of production assembly line of elevator type (see Table 1).
Table 1
Decomposition of activating functions of production
Iteration Operation descriptor Unit of measurement
(Semantic description)
WR Raw material storekeeping Cube metres
S1 Raw material cut Cube metres
S2 Manufacturing units
S3 Semi‐finished product formation units
S4 Sorting of parquet boards units
WM Storekeeping of parquet boards units
Assembly process of parquet product units
S5 Engineering conversion units
S6 Sorting and incapsulation of parquet Square metres
WP Finished product storekeeping Square metres
As it was mentioned before, group of events combined in functional group is reviewed in this study;
at the same time, for example, stage of “sorting and incapsulation of parquet” is not a compatible
process performed on previous and next stages, i.e. the strong specific section of assembly line and
procedure of switching are mentioned [9].
4. Materials and methods
Linguistic methods of initiation of numerical variables membership from theory of fuzzy control
and simulation are a basis of developed control method. The approaches presented in modern
applications in area of compositional hybrid simulation were used as materials associated in process of
complex method synthesis [10].
Semantic components defined to rank conditions applicable to specific technological process or
group of events affected on process of decision making directing on specific control action or functional
decision based on situation graphs for acceptance of specific approximative action from linguistic
variable used as identifying the trueness of result for finish action were used as data which are object
of storage, analysis and processing.
Two approaches to neuro-simulation system organization are combined in developed control
method:
the physical nature of proceed event is taken into account in first approach, i.e. the value of
engineering mechanics, section of physics described the ratio of object unreactiveness, as well
as dynamics of material point in the context of reviewed complex technical system is identified
[11];
cybernetic approach indirected by systematic analysis and technical design specification is used
in second approach.
Method of direct inputs from algorithmization was mentioned here directly with neuro-fuzzy
regulator model.
Defined neuro-fuzzy system was based on idea of modified perceptron. The work on modificator
was done within several stages in the frame of consistent work of group of authors. Situational model
resolved into direct inputs described by fuzzy rules with activating function and calculation of
regressions of compliance of estimated operation rules and standard values of outputs from assembly
line [12].
5. Results
The subtraction circuit of activating values based on voltage level (instantaneous voltage) on
windings power stations of contour (situational model becomes effective in case of combination specific
levels of voltage in system as they specifically represent modulate characteristic of operation scenario
of complex assembly line (based on group of working parameters – presenting volume and quality of
work) is defined and demonstrated in Figure 2.
The values from balanced balance-model based on which the calculation was done before start of
work (with the aim to identify the linear regression at the moment of functionality of current control
system) were assigned as econometric data base used for study (metrics of effectiveness and correlation
of system components assessment).
Figure 2: Neuro‐fuzzy independent system of regulation for assembly line
The uniform variances on criteria of number of assembled products for efficient cycle of work
(active equipment of assembly line operates with technological breaks each 30 minutes of continuous
work when the situational algorithm based on heuristic approach, i.e. defining the need of switching of
context of variability) are presented as values in basic Table 2.
Table 2
Balance‐model of production effectiveness of line in case of switching to other types of product’s
assembly with programming algorithm
Number of products, Time on knot line, s
units 1 2 3 4 5
14 10 8 – – –
15 – 12 7 – –
16 – – 28 6 –
17 – – – 8 9
18 – – – – 12
We should calculate the sample coefficient of correlation and determination on the basis of this data
for direct control before implementation of situational simulation and find the sample equation of linear
regression that describes the correlation dependence of Y value (current scenario of control) from X
quantity. Task solution of characterization resolve into composition of correlation table, (ny, nx– value
frequencies x and y correspondingly, n – sample volume) (Table 3).
Table 3
Correlation table (for direct scenario of work)
Y X ny
1 2 3 4 5
14 10 8 — — — 18
15 — 12 7 — — 19
16 — — 28 6 — 34
17 — — — 8 9 17
18 — — — — 12 12
nx 10 20 35 14 21 n = 100
Find х and y for direct mode of work (formulae 1,2) and corresponding characteristics (formulae
3,4,5,6,7,8,9), manually, to demonstrate later the finish results of calculations in case of using the
apparatus of situational input in production process monitoring:
1 5 1
х xi nxi 110 2 20 3 35 4 14 5 21 3.16 (1)
n i1 100
1 5 1
y yi nyi 14 18 15 19 16 34 17 17 18 12 15.86 (2)
n i1 100
D ~
Calculate the sampling variance x , and then x :
1 5
Dx xi x nxi
n i1
2
1
100
1 3.162 10 2 3.162 20 3 3.162 35
(3)
2 2
4 3.16 14 5 3.16 21 1.554 ,
~ D 1.554 1.25
x x (4)
~ y
Receive the =1.24. Find the sum:
n xy 10 1 8 2 14 12 2 7 3 15 28 3 6 4 16
xy
(5)
8 4 9 5 17 12 5 18 = 5156
Find the unknown sample coefficient of correlation:
rВ
n xy n x y 5156 100 3.16 15.86 0.93 ,
xy
(6)
n ~x ~y 100 1.25 1.24
Therefore, rВ 0.93 .
Coefficient of correlation shows that there is a strong connection between complex index of
effectiveness [10] and number of switching.
Coefficient of determination r 2 ( 0.94) 2 0.884 shows that 88.4% of total effectiveness variation in
work is caused by number of minimal switching, and (11.6%) – by other factors which were not taken
into account in this task. Minimization of 11% factors should be the finish results of this study.
b) substituted the founded values in equation
~ y
y x y rB ~ x x
x
(7)
,
Unknown equation of linear regression У to X will be received:
1.24
y x 15.86 0.93 x 3.16 , (8)
1.25
or finally y x 0.923 x 12 .94 .
So, equation of linear regression
y x a bx 12.94 0.923x (9)
6. Findings
Finally, the coefficient of regression b = 0.923 shows that in case of increasing of number of
switching of assembly line (x) on one determinant of working cycle (y) it is increased on 0.923
conditional units in average.
In case of implementation of situational model, the coefficient of regression takes the average value
(24 versions of work simulation were processed) laying in range of 0.964-0.98 that, generally, presents
the three sigma rule in normal distribution and shows the final objective of optimization. Therefore,
realization of situational monitoring improves the quality and operation speed of complex assembly
line on 9-19% under condition of using the different ways of assembling/ packaging of different
products.
7. Discussion
During development of situational model, it is taken into account that management of parquet
production is realized with the following mutually exclusive parameters composited in function (how
the MUL-fuzzy output of information about control action is explained and that is presented in finish
element of scheme in Figure 1).
The values themselves are determined into functional groups of parameters, where:
MR- consumption of one type of wood material;
L1 –losses of first class production during cut;
L2 –losses of materials;
D4 –waste of frieze;
M4- income of frieze;
MF- consumption of frieze;
L5- total losses (rejects);
D6- waste of product;
M6- income of parquet.
Values of group L are the non-recoverable technological losses of raw material which are calculated
based on the normative coefficients for each type of wood approved in company [12].
8. Conclusion
Taking into account the specific features of control practice in multi-stage production systems, the
wide application for tasks of control with them of profitability analysis models based on assessment of
level of correlation change from situational expenses can be confirmed [13].
Built model of development with next equal transformation to principle (method of correlated
interaction) showed the functional balance and а context based analysis allowed to solve the task of
situational monitoring at production that demonstrated the economic effectiveness of solution [14].
Demonstrated way of complex-system creation for management tool in conditions of indirect and
periodic control allow to create and evaluate the new classes of information analysis systems for
systems with tools – functional and regression nature in which the nature of compliance of expected
functionality with actual compliance of work scenario which is not dissimilar with behavior of
discontinuity function (discontinuous function) is stated and emphasized. The need of working out the
common decisions on finding the discontinuity points – points of determination (direct switching) for
specific technological processes in variety of dynamics of their demonstration is still remained.
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