=Paper=
{{Paper
|id=Vol-2570/paper11
|storemode=property
|title=Designing of architecture of an intelligent management system for assets by using hydrotreating process as an example
|pdfUrl=https://ceur-ws.org/Vol-2570/paper11.pdf
|volume=Vol-2570
|authors=Elena Andieva,Ilya Kolganov
}}
==Designing of architecture of an intelligent management system for assets by using hydrotreating process as an example==
https://ceur-ws.org/Vol-2570/paper11.pdf
Designing of architecture of an intelligent management
system for assets by using hydrotreating process as an
example
Andieva E. Yu. and Kolganov I.P.
Omsk State Technical University, Pr. Mira 11, Omsk, Omsk region, Siberian federal region,
Russia
55_elena@mail.ru
Abstract. The article suggests the architecture solution based on the digital
twin object model. The solution is based on a synthesis of relevant knowledge
about international concepts of digital transformation of production systems.
The design model is an information object model. The architectural concept is
based on that the state of values of properties material assets, petroleum
products, is affected by the state of the values of the parameters of the role
equipment. On the one hand, the process control contour boundary is a cost
center, on the other hand – is a profit center. The presented model is a digital
twin of the hydrotreating process. The architecture solution can be replicated
for other technological processes (or their segments) of production, which have
continuous production in their life cycle. The architecture is consistent with the
architecture of IoT, provides the ability to use synthesized machine learning
technologies, takes into account landscape interoperability, provides business
logic SAP ERP. Designing model approach as part of a software solution bases
on the principles of system engineering (Model-based systems engineering,
MBSE, system modeling notation SуSML).
Keywords: Architecture Solution, Assets, Digital Twin, Hydrotreating, System
Engineering, Neural Network Technology.
1 Formulation of the problem
The main focus of the article is the management system for assets as a result of the
business activities of a vertically integrated oil and gas company (VIOC) at the stage
of refining petroleum products at the hydrotreatment process.
The Design of digital twins in I4.0 solutions is a main way. There are different
points of view on this question. A digital twin is a synergistic mathematical model
that aggregates knowledge about an object and / or a system of objects [1]. Accept the
fact: «one of the most important steps in engineering design is the choice the structure
of the designed system or analysis of structural representations of the behavior and the
system activity. Even, if we have a detailed mathematical model, it does not fit for
this purpose» [2]. The question is one of priorities.
Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License
Attribution 4.0 International (CC BY 4.0)
ICID-2019 Conference
Let’s accept that the system view of the digital twin complex manufacture control
system [3, 4]. The chosen approach is consistent with Gartner agency definition of a
digital twin, which based on the consolidated opinion of experts: «A digital twin is a
digital representation of a real-world entity or system. The implementation of a digital
twin is an encapsulated software object or model that mirrors a unique physical
object, process, organization, person or other abstraction. Data from multiple digital
twins can be aggregated for a composite view across a number of real-world entities,
such as a power plant or a city, and their related processes» [5].
To design the digital twin for state assets management, the hydrotreating process as
an example, we use a model-based methodology of system engineering – MBSE [6-
8]. This methodology has a high development rate today in practice [9-12].
SySML technology, as part of the MBSE methodology, will be used as the main
design tool in the study of complex systems of various nature, which should include a
hydrotreatment system [12].
2 Design of structural view of the behavior and activities of the
hydrotreatment system
The concept of Digital Transformation of Petrochemical Production was proposed in
[3]: «The main object of management in the new client-driven dynamic business
model I4.0 is the product. As the unit of management, the state of the product is taken
at a certain stage of its life cycle. This concept solves one of the key problems of the
disagreement between the principles of continuous production with a multitude of
simultaneous parallel production processes determined by petrochemical technologies
and the discrete nature of all software systems (SS)». Particular attention is given to
the digital reference architecture transformation concept [3].
As the main material asset, we denote control object – real oil state overall value
chain of the production process from crude oil to marketable products of various
nomenclatures – digital twin based on actually measured [4].
Assume a feature point of view: value chain – corresponds to the stages of the
material asset life cycle, oil, at the production stage (provided that the oil product is a
system [3, 13, 14]); production stage is a set of technological processes: process
segments, operation, operation segments [15]; process boundaries determine where
profit center according (SAP logic) [16].
To ensure the required actual condition of the control object, the oil product
requires resources. Denote the asset systems that provide the required state of material
assets at the process boundary. These are resource objects – equipment, staff and
other (not related to the place of the Profit center according). Assume a feature point
of view: object resource equipment at the stage of its operation (provided that the
equipment is a system [3, 13, 14]); production stage is a set of technological
processes: process segments, operation, operation segments [15]; process boundaries
determine where cost center accounting (SAP logic) [17].
Conceptual view of technological process management system (see Fig. 1). We use
the domain approach [15]. To describe structure of technological process management
system was used structure diagram, which designing according SysML [18].
The conceptual view of product is represented on Fig. 2. It consists list of products
from hydrotreating process [19]: diesel, hydrocarbon gas, hydrogen gas, MEA,
gasoline, sour gas. Also, it shows connection (dependences) between products. The
block diagram is represented on Fig. 3, which is the object model of structure.
Conceptual view of equipment of the hydro treating process: ReactorBlock,
StabilisationBlock, CleaningGasBlock, GasolineCleaningBlock.
1 «Subsystem» 1 «Subsystem»
Product Equipment
1 «Subsystem»
Process_hydrotreating
1 «Subsystem» 1 «Subsystem»
Others People
Fig. 1. Conceptual view of technological process management system (Structure diagram
technological process management system)
1 «Subsystem»
Product
1 «Subsystem» 1 «Subsystem» 1 «Subsystem»
Diesel Hydrogen_gas Hydrocarbon_gas
1 «Subsystem» 1 «Subsystem» 1 «Subsystem»
Gasoline MEA Sour_gas
Fig. 2. Conceptual view of oil product subsystem (Structure diagram oil product subsystem)
Assume a feature point of view: accept the fact that the equipment is divided into
equipment and role equipment [4, 15]; the state of the values of the parameters of the
role equipment affect the state of the values of the properties of the material asset, oil
product.
1 «Subsys tem»
Equipment
1 «Subsys tem» 1 «Subsys tem»
ReactorBlock StabilisationBlock
1 «Subsys tem» 1 «Subsys tem»
CleaningGasBlock GasolineCleaningBlock
Fig. 3. Conceptual view of equipment subsystem (Structure diagram equipment subsystem)
Conceptual view of subsystem equipment gasoline cleaning block is shown on Fig. 4.
Assume a feature point of equipment view: the equipment is divided into segments
according to technological process. Denote the block for moving the
monoethanolamine to the other block – MEAPumpInBlock, which include role
equipment: MEA transferring pumps: Н_5_1, Н_5_2. Denote the unit for extraction
process – ExtractorBlock that consist extractor K_6 и tank Е_6. Denote the block for
moving the monoethanolamine from the other block – MEAPumpOutBlock: MEA
transferring pumps: H_6_1, H_6_2; Denote the block for moving the gasoline out –
GasolinePumpOutBlock: gasoline pumps H_3_1, H_8_1; Denote the gasoline
production block – GasolineProductionBlock – the source of raw material – L_24_6,
L_24_7. GasolineProductionBlock is an outside system of equipment, which transfer
gasoline for cleaning technological process as a one of the material asset.
Conceptual view of subsystem equipment stabilization block is shown on Fig. 5.
Assume a feature point of equipment view: the equipment is divided into segments
according to technological process. Stabilization block is the next stage, several
technological processes, after Reactor block, which include hydrogenation process –
purification of diesel fuel from harmful impurities oxygen, sulfur, nitrogen, by using
hydrogen and catalysts, reactions occurring under certain technological state.
Separated hydrocarbons are sent to stabilization block. According to technological
operations, the equipment included in this unit divided into groups:
StabilisationColumnBlock, SeparationBlock_of_StabilisationBlock,
GasolineOutPumpBlock, DieselOutCoilsBlock. Marked block for stabilization
process of diesel fuel – StabilisationColumnBlock. It consists stabilization column
K_1 and related equipment – irrigation pumps H_3_1, H_3_2; kilns for heating
diesel in the boiler P_2_R, P_2_L; diesel pumps for movement part of the fuel to the
boiler and other part out H_2_1, H_2_2, H_2_3. Next block is needed for separate
substance, one of them direct to K_1, part of them go out, and gas move to the other
technological block. Denote the separation block, which divide substance into several
layer – SeparationBlock_of_StabilisationBloc. In include some technological
equipment: for substance cooling two air coils XK_1_1, XK_1_2, and one liquid coil
– X_10, and separator C_5; Denote the block, which responsible for the withdrawal of
stable gasoline from process – GasolineOutPumpBlock. This block consists two
diesel pumps H_3_3, H_8_1. Denote heat exchange block – Dieseloutcoilsblock. This
group of equipment is a place of interaction with other blocks – Reactor block and
cleaning gas block. There are exchangers for MEA – T_4; diesel exchangers T_2_1
_n, T_2_2_n, T_2_3_n, T_2_1_v, T_2_2_v, T_2_3_v; exchangers between new
diesel and diesel after hydrotreating T_26, T_27; and the last air cooler for diesel
X_5_1, X_5_2, X_5_3.
Assume a feature point of view: equipment – an object of management; equipment
can perform certain technological functions – it is role-playing equipment. To make
managerial decisions, we will consider only those parameters that affect the properties
of the main material asset, oil product.
Consider the properties of role-based equipment using object – compressor
PK_1_1 as an example. First, we highlight the technological parameters: temperature
and pressure in the compressor row. For a material asset, diesel and gasoline, it is
necessary to maintain the required properties, which are achieved by the required
chemical composition of the substance under certain environmental parameters,
which are provided by a certain value of the role equipment parameters. Therefore,
we identified two main parameters of the compressor.
To maintain normal parameters, it is necessary to maintain a certain, operational
condition of the equipment. The condition of the equipment greatly affects its
operation, and as a result, the main material asset. The compressor is a dynamic
equipment. Dynamic properties of compressor: vibro movement, vibro speed, vibro
acceleration. The listed characteristics are measured on the crankshaft of the
compressor. The rotation of the shaft and its vibrations are affected by bearings. The
condition of the bearings can be monitored indirectly by measuring their temperature.
Therefore, six more parameters are added according to the number of bearings. It is
possible to control the compressor through a system that squeezes the suction valve
when compressing gas. Therefore, the parameters in this row will change differently,
which also affects the output state of the properties of the material asset.
So, the state of the values of the parameters of the role equipment affect the state of
the values of the properties of the material asset, oil product. So, compressor like role
equipment has some parameters: activity – one, two, three or four line, bearings
temperature: first bearing, second bearing, third bearing, fourth bearing, fifth bearing,
sixth bearing; line parameters (temperature, pressure), vibro acceleration, vibro
movement, vibro speed.
On the next stage, parameters are divided from equipment. For example, get object
– compressor PK_1_1. We can see the object, which describe parameters of the
compressor on the Fig. 6. Each object is a specific compressors parameter. Let’s
divide substance properties and parameters of the equipment that we will have a
properties layer. So, we can see equipment parameters of the compressor. This layer
will be used in the neural network.
1 «Subsyst em»
1 H_3_3:Pump
L_24_6:Production be a ringTe mpe ra ture [1.. .. .
id:RhpString
1 GasolinePumpOutBlock
1 na me :RhpString
GasolineProductionBlock
product ion:double
roundSpe e d:double
subst a nce In:Subst a nce
subst a nce O ut:Substa nce
1 «Subsyst em»
1 «Subsyst em» cha nge RoundSpe e d(rou.. .
L_24_7:Production
Equipment::GasolineCleaningBlock compre ss(substa nce In:S. ..
1 MEAPumpInBlock ge t Subst a nce O ut():Subs.. .
of f():void
on():void
1 ExtractorBlock 1 MEAPumpOutBlock
1 H_5_1:Pump 1 H_5_2:Pump 1 H_8_1:Pump
be a ringTe mpe ra ture [1. . *]:double be a ringTe mpe ra ture [1.. *]:double be a ringTe mpe ra ture [1. . *]: . ..
id:RhpString id:RhpString id: RhpString
na me :RhpString na me :RhpString 1
1 H_6_1:Pump 1 H_6_2:Pump na me : RhpString
K_6:Extractor
product ion:double product ion:double
1 E_6:Tank product ion: double
be a ringTe mpe ra ture [1. . *]:. .. be a ringTe mpe ra ture [1.. .. .
roundSpe e d:double roundSpe e d:double subst a cne He a vyO ut :. .. roundSpe e d: double
volume:do.. . id:RhpString id:RhpString
subst a nce In:Subst a nce subst a nce In:Subst a nce subst a nce He a vyIn: S. .. subst a nce In: Subst a nce
na me :RhpString na me :RhpString
subst a nce O ut:Substa nce subst a nce O ut:Substa nce subst a nce Light In:Su. .. subst a nce O ut: Subst a nce
product ion:double product ion:double
subst a nce Light O ut : .. .
cha ngeRoundSpe e d(roundSpe e d:i. .. cha nge RoundSpe e d(roundSpe e d. . . roundSpe e d:double roundSpe e d:double cha ngeRoundSpe e d(round. . .
compress(substa nce In:Substa nce ):. .. compre ss(substa nce In:Substa nce . .. subst a nce In:Subst a nce subst a nce In:Subst a nce compress(substa nce In:Subs.. .
ge t Subst a nce O ut():Substa nce ge t Subst a nce O ut():Substa nce subst a nce O ut:Subst a nce subst a nce O ut:Substa nce ge t Subst a nce O ut():Substa nce
of f():void of f():void of f():void
on():void cha ngeRoundSpe e d(round. . . cha nge RoundSpe e d(rou.. .
on():void on():void
compress(substa nce In:Subs.. . compre ss(substa nce In:S. ..
ge t Subst a nce O ut():Substa nce ge t Subst a nce O ut():Subs.. .
of f():void of f():void
on():void on():void
Fig. 4. Conceptual view of gasoline cleaning block (Block diagram subsystem equipment gasoline cleaning block)
1 X_5_1:AirCoil
1 X_5_3:AirCoil id:RhpString
1 T_2_2_v:Exchanger
1 T_26:Exchanger name:RhpStri ng
id:RhpString 1 X_5_2:AirCoil
1 T_2_1_v:Exchanger substanceColdI n:Su... open:bool
name:RhpString
substanceColdI n:Su... substanceColdO ut:S... id:RhpString roundSpeed:i nt
substance ColdI n:Substance open:bool
T_27:Exchanger substanceColdO ut:S... name:RhpString s ubs tanceH otI n:S...
1 roundSpeed:int
substance ColdO ut:Substance open:bool s ubs tanceH otO ut:...
exchange( hotI n:Sub... substanceH otI n:S...
substanceCol dI n:S... roundSpeed:int tEnv:double
exchange( hotI n:Sub... getColdO ut( ) :Substa... substanceH otO ut:...
substanceCol dO ut:... exchange( hotI n:Substance... substanceH otI n:S...
getColdO ut( ) :Substa... getH otO ut( ) :void tEnv:double getH otOut( ) :void
getColdO ut( ) :Substance substanceH otO ut:...
getH otO ut( ) :void
getH otO ut( ) :void tEnv:double
exchange( hotI n:S... getH otO ut( ) :void
1 T_2_3_n:Exchanger
getColdO ut( ) :Subs... getH otO ut( ) :void
getH otO ut( ) :void substance ColdI n:Substance
1 DieselOutCoilsBlock substance ColdO ut:Substan...
1 T_2_2_n:Exchanger
1 H_3_2:Pump
1 K_1:StabilisationColumn substance ColdI n:Substance exchange( hotI n:Substanc...
bearingTempera... substance ColdO ut:Substance getColdO ut( ) :Substance
id:RhpString heavySubstanceI n:Substance 1 T_2_1_n:Exchanger getH otO ut( ) :void
1 T_4:Exchanger
name:RhpString lightSubstanceI n:Substance
exchange( hotI n:Substance...
production:double substanceCol dI n:S... substanceColdI n:Sub...
getColdO ut( ) :Substance
roundSpeed:dou... substanceCol dO ut:... substanceColdO ut:Su...
getH otO ut( ) :void 1 T_2_3_v:Exchanger
s ubs tanceI n:Su...
1 «Subsystem» exchange( hotI n:S...
s ubs tanceO ut:S...
Equipment::StabilisationBlock getColdOut( ) :Subs... exchange( hotI n:Subs... substance ColdI n:Substance
getColdO ut( ) :Substan... substance ColdO ut:Substance
changeRoundSp... getH otO ut( ) :void
compress( s ubs... 1 StabilisationColumnBlock exchange( hotI n:Substance...
getSubstanc eO ... getColdO ut( ) :Substance
off( ) :void 1 SeparationBlock_of_StabilisationBloc k 1 GasolineOutPumpBloc k getH otO ut( ) :void
on( ) :void
1 P_2_R:Kiln
airProductio...
1 H_2_1:Pump fireTemperat...
substanceI ... 1 H_3_3:Pump 1 H_8_1:Pump
bearingTempera... 1 H_2_2:Pump 1 H_2_3:Pump 1 P_2_L:Kiln substanceO ... 1 X_10:LiquidCoil bearingTempera... bearingTempera...
id:RhpString
bearingTempera... bearingTempera...
1 XK_1_2:AirCoil
name:RhpString fireTemperat... heat( substa... id:RhpString 1 C_5:Separator id:RhpString id:RhpString
production:double id:RhpString id:RhpString s ubs tanceI ... id:RhpString name:RhpString name:RhpString
name:RhpString
roundSpeed:dou... name:RhpString name:RhpString s ubs tanceO ... name:RhpString pressure:double production:double production:double
substanceColdI n:Sub...
substanceI n:Su... production:double production:double 1 XK_1_1:AirCoil open:bool substanceI n[ 1..*] ... roundSpeed:dou... roundSpeed:dou...
substanceColdO ut:Su...
substanceO ut:S... roundSpeed:dou... roundSpeed:dou... roundSpeed:int substanceO ut[ 1..*... substanceI n:Su... substanceI n:Su...
id:RhpString substanceH otI n:Sub...
substanceI n:Su... substanceI n:Su... heat( substa... substanceO ut:S... substanceO ut:S...
substanceH otI n:Sub... substanceH otO ut:do... volume:doubl e
changeRoundSp... name:RhpString
substanceO ut:S... substanceO ut:S... substanceH otO ut:do...
open:bool tEnviroment:double
compres s ( s ubs ... changeRoundSp... changeRoundSp...
tEnv:double
getSubs tanc eO ... changeRoundSp... changeRoundSp... roundSpeed:int compress( s ubs... compress( s ubs...
getColdO ut( ) :Substa...
off( ) :void compress( s ubs... compress( s ubs... substanceH otI n:S... getSubstanc eO ... getSubstanc eO ...
getH otO ut( ) :void getH otO ut( ) :Substan...
on( ) :void getSubstanc eO ... getSubstanc eO ... substanceH otO ut:... off( ) :void off( ) :void
refrigerate( coldI n:Su...
off( ) :void off( ) :void tEnv:double on( ) :void on( ) :void
on( ) :void on( ) :void getH otO ut( ) :void
Fig. 5. Conceptual view of stabilization block (Block diagram subsystem equipment stabilization block)
1 temperature_bearing_1_PK_1_1
1 bearing_1_PK_1_1 1 activityPK_1_1 1 PK_1_1:Compressor 1 production_PK_1_1
1 bearing_2_PK_1_1 activity:d ouble
bearingTemperatu re[1. . *].. .
id :Rh pString 1 line_4_PK_1_1
1 temperature_bearing_2_PK_1_1 lineParameter[1. . *]:S ubst. . .
name:RhpString
1 bearing_3_PK_1_1 1 bearings_PK_1_1 production:dou ble
1 lineParameters_PK_1_1
vibroAcceleratio n:d ouble
vibroM ovement:double 1 temperature_line_4_PK_1_1
vibroSpe ed:double
1 temperature_bearing_3_PK_1_1
1 bearing_4_PK_1_1 changeA ctivity(numberActiv. . .
comp ress(su bstanceIn:Subs. . .
1 pressure_line_4_PK_1_1
getSubst anceO ut():Subst a.. .
1 bearing_5_PK_1_1 1 bearing_6_PK_1_1 1 line_2_PK_1_1 1 line_3_PK_1_1
of f ():void
O n():void
1 temperature_bearing_4_PK_1_1
1 temperature_line_3_PK_1_1
1 line_1_PK_1_1
1 1
1 crankshaft_PK_1_1
temperature_bearing_5_PK_1_1 temperature_bearing_6_PK_1_1
1 pressure_line_3_PK_1_1
1 vibroMovement_PK_1_1 1 vibroSpeed_PK_1_1 1 temperature_line_1_PK_1_1 1 temperature_line_2_PK_1_1
1 vibroAcceleration_PK_1_1 1 pressure_line_1_PK_1_1 1 pressure_line_2_PK_1_1
Fig. 6. Conceptual architecture of compressors parameters
Take hydrogen gas as an example, because it interacts with the PK_1_1 compressor –
resource object, which described above. We distinguish the following properties of
the substance destiny, fair temperature, sour percent (special quality, that not included
in the physicochemical properties of substances, but isolated and important) boiling
temperature, autoignition temperature, ignition temperature, flash point, heat capacity.
The achievement of the required properties values of substances described earlier is
the goal of controlling the values of equipment parameters. To identify complex
dependencies between the values of the equipment parameters, – the resource object
and the material asset, – oil property values, consequently, neural network
technologies will be used to calculate the control action. Neural networks are widely
used for decision-making based on the analysis using technology data mining [20, 21].
The equipment parameters obtained from sensors and the state of oil products
provide to the input layer of the NN. We use a multilayer neural network to identify
complex hidden relationships between input and output vectors. At the output, we get
a vector that describes the state of the oil product – the main asset, based on which,
through communications, we will determine the most influential equipment and
manage it.
The target system is divided into five stage. The data from the sensors, that
describes real equipment, must be collected and processed. The first component will
collect data from sensors. The second component should sort into two parts: negative
and positive example. Then several data problems should be solved. Firstly, some
parameters or properties are analyzed once during a day or week. Second, data
dimensions are various. So, temperature is measured between minus 70 and plus 700 oC,
but pressure is measured between 0,1 and 6 MPa. It is a problem for NN training.
Management system – is a deep neural network, which has input vector and output
vector. Input vector is a data, which describes real substance property, property, that
we wish, and the ideal property. Output vector is a data, which describes parameters
of the equipment; owing to we can reach necessary property.
3 Summarize
The main distinctive features of the proposed concept of the digital transformation
reference architecture are the following. The article presents the architecture solution
based on the digital twin object model. The architecture solution can be replicated for
other technological processes (or their segments) of production, which have
continuous production in their life cycle. The architecture is consistent with the
architecture of IoT, provides the ability to use synthesized machine learning
technologies, takes into account landscape interoperability, provides business logic
ERP SAP. Designing model approach as part of a software solution bases on the
principles of system engineering (MBSE, SуSML).
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