An approach to describe a cyber-physical production is studied, which is based on a combination of abstract objects using control technologies, computing and connection to formalize the cyber-physical systems relations in an industrial environment. Abstract objects are used to project the control hierarchy systems engaging the regulator setting adaptation elements controlling equipment functionality. The cyber-physical systems description given with a number of abstract objects is good for a little formalized item manufacturing technological tasks solution, which completion mechanisms coordination is defined in fuzzy logical terms. The technological system properties abstract representation corresponds to object oriented approach to describe the cyber-physical production elements and let create applications in the program machine codes controlling the smart factory inner processes states with a given control level parameter vector. The physical, virtual, logical and functional objects are defined, which is the base to describe the technological environment behavior automatics structural elements placed in different hierarchy levels (cyber-physical system, peripheral equipment workshop, production division). Each abstract object corresponds to a group of equipment units or to a group of software agents participating in the process regulation with the cyber-physical systems and production environment measurements and states evaluation. There is a scheme proposed of abstract objects classes hierarchy, which is the cyber-physical production infrastructure.

1.
J.
Fiaidhi
, and
S.
Mohammed
,
Computer communications
170
,
84
94
(
2021
).
2.
G.
Lyu
,
A.
Fazlirad
, and
R.W.
Brennan
,
Procedia manufacturing
51
,
1200
1206
(
2020
).
3.
G.
Bruno
,
IFAC-PapersOnLine
52
,
13
,
2764
2769
(
2019
).
4.
A. G.
Korobeynikov
,
M. E.
Fedosovsky
,
I. O.
Zharinov
,
V. I.
Polyakov
,
A. V.
Shukalov
,
A. V.
Gurjanov
, and
S. A.
Arustamov
,
Advances in intelligent systems and computing
680
,
50
56
(
2018
).
5.
H.
Panetto
,
B.
Iung
,
D.
Ivanov
,
G.
Weichhart
, and
W.
Xiaofan
,
Annual reviews in control
47
,
200
213
(
2019
).
6.
K.-C.
Ying
,
P.
Pourhejazy
,
C.-Y.
Cheng
, and
C.-H.
Wang
,
Journal of manufacturing systems
58, A
,
452
466
(
2021
).
7.
Y.
Lu
, and
F.
Ju
,
IFAC-PapersOnLine
50
,
1
,
15883
15889
(
2017
).
8.
M.
Matsuda
,
T.
Nishi
,
M.
Hasegawa
, and
T.
Terunuma
,
Procedia CIRP
93
,
688
693
(
2020
).
9.
Y.
Wang
,
S.
Wang
,
B.
Yang
,
L.
Zhu
, and
F.
Liu
,
Journal of cleaner production
248
,
119299
(
2020
).
10.
G. F.
Schneider
,
H.
Wicaksono
, and
J.
Ovtcharova
,
Advanced engineering informatics
39
,
127
143
(
2019
).
11.
G.
Tanganelli
,
L.
Cassano
,
A.
Miele
, and
C.
Vallati
,
Future generation computer systems
109
,
420
430
(
2020
).
12.
X.
Sun
,
Y.
Liu
, and
L.
Deng
,
Renewable energy
155
,
1411
1424
(
2020
).
13.
B.
Farooq
,
J.
Bao
,
H.
Raza
,
Y.
Sun
, and
Q.
Ma
,
Journal of manufacturing systems
59
,
98
116
(
2021
).
14.
C.
Gonnermann
, and
G.
Reinhart
,
Procedia CIRP
81
,
636
640
(
2019
).
15.
V. A.
Bogatyrev
, and
A. N.
Derkach
,
Computers v9
,
2
,
42
(
2020
).
16.
V.
Sood
,
M. K.
Nema
,
R.
Kumar
, and
M. J.
Nene
,
Procedia computer science
171
,
81
90
(
2020
).
17.
A.
Noor
,
K.
Mitra
,
E.
Solaiman
,
A.
Souza
,
D. N.
Jha
,
U.
Demirbaga
,
P. P.
Jayaraman
,
N.
Cacho
, and
R.
Ranjan
,
Computers & electrical engineering
77
,
314
324
(
2019
).
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