CN105096008A - Control method of process industry production system - Google Patents

Abstract

The invention discloses a control method of a process industry production system. The control method comprises the following steps: according to the site production situation and the production requirements of the process industry production system, constructing a system model, and drawing a production technological process chart; on the basis of the production technological process chart, determining the production information of the production system, and establishing a target function based on mixed integer linear programming; and taking system production benefit maximization as an optimization object to carry out optimization solution on the target function, and obtaining optimal production information used for controlling the process industry production system. The invention provides a feasible control method of the process industry production system, the control method realizes the combination of the unified modeling and the logistics optimization of the process industry production system, is effective and universal and can provide effective reference information for a production plan of the process industry for controlling.

Description

A kind of control method of process industry production system

Technical field

The present invention relates to the modeling of process industry production system and optimizing scheduling field, particularly, relate to a kind of control method of process industry production system, based on crossing the modeling method of planning optimization and realizing based on the logistic optmum method of MILP (Mixed Integer Linear Programming).

Background technology

The production system of process industry often has in large scale, complex manufacturing, the features such as resource distribution difficulty is large, and thus the daily production of process industry and system call optimization are often faced with the process of mass data and distributing rationally of resource.Along with system optimization method is at process industry, particularly in continuous application and the popularization of petrochemical field, the system modelling of process industry and optimizing also has become an important research direction and field.

The people such as ConorM.McDonald and IftekharA.Karimi proposed in 1997 the multi-period plan optimization method being directed to single or multiple discrete process units at " PlanningandschedulingofparallelsemicontinuousprocessesPr oductionplanning ".The people such as J.M.Pinto and M.Joly proposed the plan optimization method for refinery integral production system in 2000 in literary composition at " Planningandschedulingmodelsforrefineryoperations ".The method, based on the Building Nonlinear Model of refinery, will comprise the refinery unit such as processing unit (plant) and attemperation apparatus equipment and take into account, and obtain the planning optimization model of refinery on this basis.Robust Optimal methods is applied to scheduling and the optimizing process of process industry by Li and Ierapetritou in the article " RobustOptimizationforProcessSchedulingUnderUncertaintyIn dustrial " of 2008, and the system optimization for process industry is studied with scheduling.The main object more than studied mostly is single process units or by the small-scale production system being no more than ten process units and forming, and correspondingly Optimized model is also the proprietary model for this specific production system, does not have portability and universality; Meanwhile, because the system scale of research object is less, so above method is further proved and research for whether effective also the needing of labyrinth of actual production system.

Some research work, from business administration, material handling management, considers index and the parameter such as transportation cost, production cost based on supply chain.The integrated planning optimization of production run such as manufacturing cost, inventory cost based on supply chain is considered from the angle of business administration in Ji little Li etc. " the Three-level Supply Chain integration scheme Study on Problems based on a genetic algorithm " literary composition.The multi-source supplier selection problem in " logistics service supply chain build in Supplier Selection research " literary composition in integrated use analytical hierarchy process and Research On The Linear Programming Method production system supply chain integrating process such as Tian Yu.This part research work is from the angle of management, do not consider the state of arts of produced on-site, just from distribution and the economic target of the angle analysis management resource of management, do not have the angle of producing from engineering analyze problem and optimize, also corresponding produced on-site parameter and data cannot be obtained, therefore also effective guidance and help cannot be provided for the production at scene, scheduling and system optimization.

Publication number be 1763774 Chinese patent application " a kind of modeling method of visible production process description of process industry " disclose a kind of visual technological process describing method, the method comprises basic data maintenance, data acquisition, production technology description and model generation four steps, this method provide and describe based on visual production system, daily production run scheduling problem can be processed.Although the method can carry out visual description to the production run of system, but the method is just to displaying and the visual description of the production procedure of system, and cannot be optimized and reasonable disposition the production run of system and the resources of production based on set up model.

Publication number is the industrial process modeling Forecasting Methodology that the Chinese patent application " a kind of industrial process modeling Forecasting Methodology of Process-Oriented object " of 104732067A discloses a kind of Process-Oriented object.The method obtains the variation tendency formula of each measuring point data of flow object based on flexible Neural Tree, simulates industrial processes, based on the production status of correlation parameter prediction following a period of time of current production status.The method is based on existing production data and information in the future or have the prediction of production status, its essence to be collection to data, process and prediction, and not from the Modeling and optimization configuration of the angle resolved systems of the model of system and production law thereof.

The research object of the method consideration of existing process industry system modeling and optimization is too single and scale is less, can not reappear the complicated production system of process industry truly; Plan optimization method has stronger specificity, does not have versatility, thus also cannot provide a kind of logistic optmum method being applicable to most process industry production system.

Summary of the invention

For deficiency and the defect of existing process industry production system logistics plan Optimization Modeling and system optimization method, the invention provides a kind of control method of process industry production system, adopt the modeling method of planning optimization and the logistic optmum method based on MILP (Mixed Integer Linear Programming), for solving logistics plan Optimization Modeling and the Solve problems of process industry production system, and the MILP (Mixed Integer Linear Programming) Optimization Solution strategy simultaneously given based on institute's established model, for the logistics plan optimization of produced on-site provides Data support and guidance.

A control method for process industry production system, comprises the steps:

(1) according to the condition of production and the Production requirement constructing system model at the scene of process industry production system, and production technological process is drawn;

(2) based on described production technological process, determine the production information of production system, and set up the objective function based on MILP (Mixed Integer Linear Programming);

(3) to be optimized described objective function to solve with the maximum optimization aim that turns to of system productivity effect, the production information that is optimized is for control flow industrial production system.

The each component of control method to production system of process industry production system of the present invention establishes unified drawing standard, thus is convenient to the production technological process constructing unified pattern; Meanwhile, the production technological process based on unified pattern just can set up unified mathematical constraint and majorized function, thus forms logistics plan Optimized model and the optimization method with versatility, and then can the productivity effect of process industry production system.

Described step (1) comprises the steps:

(1-1) system element in process industry production system is divided into following six classes according to function and structure: enter plant stand point, stores tank field, process units, split point, confluence and the website that dispatches from the factory, wherein:

Website of marching into the arena is the input node of system raw material, for providing raw materials for production to production system, enters plant stand point by dispatching from the factory node and go out side line and form, arbitrary enter plant stand point comprise a node and some go out side line;

Store the storage unit that tank field is system material, for carrying out short-term or longer-term storage to material involved in the various production systems such as raw material, intermediate material, product, storage tank field is by can body and enter side line, go out side line forms, arbitrary tank field comprises a can body, some enter side line and some go out side line;

Process units is the unit that system carries out materiel machining process and chemical reaction, for processing material thus the product generated or intermediate material, each processing unit (plant) can have one or more processing schemes by adjustment processing conditions, process units is by apparatus main body and enter side line, go out side line forms, arbitrary process units comprises an apparatus main body, some enter side line and some go out side line;

Split point, confluence are virtual system nodes, for refluxing to material of the same race and shunting process, wherein split point is used for material of the same race to be divided into some shuntings, confluence is used for some tributaries of material of the same race being carried out merging and forms interflow, split point is by forking node and enter side line, go out side line forms, arbitrary split point comprises a forking node, article one, enter side line and some go out side line, confluence is by confluxing node and enter side line, go out side line and form, arbitrary confluence comprises the node that confluxes, some enter side line and one go out side line;

The website that dispatches from the factory is the Egress node of system product, exports production system for system being produced the product, intermediate material and the waste material that obtain, the website that dispatches from the factory by dispatching from the factory node and enter side line and form, arbitrary website that dispatches from the factory comprise a node and some enter side line.

(1-2) in conjunction with the practical condition of process industry production system, the structural information of each system element in determining step (1-1), wherein:

The structural information entering plant stand point comprises and goes out side line quantity into plant stand point;

The structural information storing tank field comprises storage tank field and enters side line quantity, goes out side line quantity;

What the structural information of process units comprised process units enters side line quantity, goes out side line quantity;

What the structural information of split point comprised split point goes out side line quantity;

Side line quantity is entered in the confluence that the structural information of confluence comprises;

What the structural information of website of dispatching from the factory comprised the website that dispatches from the factory enters side line quantity.

(1-3) material and the Flow of Goods and Materials relation of each system element side line in production run is determined, determine the annexation of side line between each device, and complete the logic connecting relation of each side line, thus obtain system model, and drafting obtains corresponding flow sheet.

The material variety in the side line of each system components is determined in described step (1-3), and according to the flowing relation of practical condition determination material, go out side line with the directive line of band by what be associated and enter side line and be connected, in order to indicate the flowing relation of material.

Determine the Flow of Goods and Materials relation in whole production system, and then determine the annexation between each system components according to material flow relation, and then the production technological process of whole production system of completing.

Described step (2) comprising:

(2-1) production information of each system element in process industry production system is obtained; The production information of each system element is as follows:

That enters that plant stand point production information comprises enters plant stand point material variety and flow information;

The production information storing tank field comprises tank field production cycle tank storage originally;

The production information of process units comprises the processing scheme information of process units;

The production information of split point comprises entering side line, going out side line material variety of split point;

The production information of confluence comprises confluence and enters side line, goes out side line material variety;

The production information of website of dispatching from the factory comprises material variety and the market demand thereof of the website that dispatches from the factory.

(2-2) according to the production information of each system element, the production technological process described in utilization, sets up the objective function based on MILP (Mixed Integer Linear Programming).

As preferably, described objective function is the productivity effect of process industry production system, and:

Productivity effect=production product income-product purchase cost-material transportation cost-process units processing cost-material carrying cost-market demand does not meet penalty term;

The described market demand does not meet rejection penalty that penalty term is each product unit inventory when unmet demand of process industry production system and the sum of products of the unsatisfied inventory of corresponding product in each time period.

As preferably, to objective function be optimized solve time using material balance as constraint condition.

Material balance relationship in the present invention is as follows:

Starting material purchase volume=admission website mass flow and;

The market demand of the sales volume of the product≤product;

Product is for meeting penalty value >=produce market demand-sales volume of the product;

Material goes out the pipeline mass flow of side line flow=be attached thereto;

Material enters the pipeline mass flow of side line flow=be attached thereto;

Shunt volume enters side line flow=this shunting and points out pump-around stream amount sum;

Conflux and point out pump-around stream amount=this confluence and enter side line flow sum;

Processing unit (plant) goes out side line flow=processing unit (plant) processing total amount * corresponding survey line productive rate distribution ratio;

Processing unit (plant) total run time=processing unit (plant) each processing scheme sum working time;

Initial storage+the tank field of tank field end of term stock=tank field material is entered side line flow sum-tank field and is gone out side line flow sum.

Because process industry production system is complicated, corresponding objective function derivation amount is larger, as preferably, the present invention by ILOG platform or GMAS platform etc. to mathematical model (objective function) as Optimization Solution platform, calling CPLEX solver to above-mentioned mathematical model solves;

The main production information such as productivity effect value, processing cost, process units processing scheme that the Optimization Solution result obtained comprises expection (comprises raw material type and amount of purchase thereof, product category and sales volume thereof, the processing scheme of process units, tank field closing stocks, and the flow etc. of transport line), and these production systems are used for the formulation supporting produced on-site scheduling and plan, to control for process industry production system.

Compared with prior art, the majorized function that the present invention sets up is MILP (Mixed Integer Linear Programming) function, does not comprise nonlinear variable, for the solution that has of Optimized model provides guarantee; Simultaneously in conjunction with the requirement of actual production, Optimized model can provide the solution of a global optimum based on given parameters and model, to ensure to maximize based on the productivity effect under specified criteria, and unified drawing standard is established to each component of production system, thus be convenient to the production technological process constructing unified pattern, define and there is versatility, improve the scope of application of method of the present invention.

Accompanying drawing explanation

Fig. 1 is the method step figure of the present embodiment;

Fig. 2 be the present embodiment enter plant stand point schematic diagram, be No. 1, crude oil website in figure;

Fig. 3 is the storage tank field schematic diagram of the present embodiment, is crude oil tank farm in figure;

Fig. 4 is the process units schematic diagram of the present embodiment, is No. 1, atmospheric and vacuum distillation unit in figure;

Fig. 5 is the split point schematic diagram of the present embodiment, is crude oil split point in figure;

Fig. 6 is the confluence schematic diagram of the present embodiment, meeting vacuum residuum confluence in figure;

Fig. 7 be the present embodiment produce website schematic diagram, be No. 1, point of sales station in figure;

Fig. 8 is the side line connection diagram of the present embodiment, for AGO charging mixes the connection diagram of storage tank and No. 1, ethylene unit in figure.

Embodiment

Below with reference to the drawings and specific embodiments, the present invention will be further elaborated and explanation.

As shown in Figure 1, a kind of process industry production system control method its specifically comprise two steps:

Step 1: according to the condition of production and the Production requirement constructing system model at process industry production system scene, and draw flow sheet;

Concrete enforcement and operation as follows:

Step 1-1: according to the difference of the function of each system components in production system, all system components in production system are classified, in the present embodiment, is divided into following 6 classes: enter plant stand point, store tank field, process units, split point, confluence and the website that dispatches from the factory.

First by on-site inspection or consult technological process of production detail file, the system components such as process units all in production system are classified, be divided into into plant stand point, store tank field, process units, split point, confluence and website six class of dispatching from the factory.In production system investigated in this example:

Enter plant stand point to comprise: No. 1 ~ 3, raw material website (can # represent), MTBE supplies website, VGO transportation base etc.;

Storage tank field comprises: petroleum tank, No. 1 ~ 2, naphtha tank, naphtha mixing tank, 1 ~ No. 2 tank in center for distribution tank field etc.;

Process units comprises: No. 1 ~ 2, atmospheric and vacuum distillation unit (CDU), catalytic cracking unit, delayed coking unit, No. 1 ~ 2, ethylene unit etc.;

Split point comprises: crude oil split point, naphtha split point etc.;

Confluence comprises: naphtha confluence, vacuum residuum confluence etc.;

The website that dispatches from the factory comprises: No. 1 ~ 3, point of sale of dispatching from the factory, monoethylene glycol transportation base, diethylene glycol transportation base etc.

Step 1-2: in conjunction with practical condition, the structure of each system components in determining step 1-1.

For each system components, determine the nodal information of this system components and enter side line, go out side line information, thus determining the structure of each system components.

Enter plant stand point by dispatching from the factory node and go out side line and form, arbitrary enter plant stand point comprise a node and some go out side line.As shown in Figure 2, typically enter plant stand point as crude oil website 1#, there is a node and one go out side line.By that analogy, determine the structure all entering plant stand point, and draw diagram.

Store tank field by can body with enter side line, go out side line and forms, arbitrary tank field comprises a can body, some enter side line and some go out side line.As shown in Figure 3, crude oil tank farm has a tank field main body, one enter side line and one go out side line.By that analogy, determine the structure all storing tank field, and draw diagram.

Process units is by apparatus main body and enter side line, go out side line and forms, and arbitrary process units comprises an apparatus main body, some enter side line and some go out side line.As shown in Figure 4, as atmospheric and vacuum distillation unit 1#, its have an apparatus main body, one enter side line and five go out side line.By that analogy, determine the structure of whole process units, and draw diagram.

Split point is by forking node and enter side line, go out side line and forms, and arbitrary split point comprises a forking node, one enter side line and some go out side line.As shown in Figure 5, crude oil split point have one enter side line and two go out side line.By that analogy, determine the structure of whole split point, and draw diagram.

Confluence is by confluxing node and enter side line, go out side line and form, and arbitrary confluence comprises the node that confluxes, some enter side line and one go out side line.As shown in Figure 6, vacuum residuum confluence have two enter side line and one go out side line.By that analogy, determine the structure of whole confluence, and draw diagram.

Dispatch from the factory website (point of sales station of namely dispatching from the factory) by dispatching from the factory node and enter side line and form, arbitrary website that dispatches from the factory comprise a node and some enter side line.As shown in Figure 7, the website 1# that typically dispatches from the factory there is a node and one enter side line.By that analogy, the structure of website of determining all to dispatch from the factory, and draw diagram.

Step 1-3: determine the material variety in the side line of each system components, and according to the flowing relation of practical condition determination material, goes out side line with the directive line of band by what be associated and enter side line and be connected, in order to indicate the flowing relation of material.

First, the side line material information of all six type systematic components in determining step 1-1; Then, in conjunction with Flow of Goods and Materials information, be associated two directive lines of side line are connected, instruction Flow of Goods and Materials relation.

As shown in Figure 8, entering side line and going out side line material of AGO charging buffer tank is atmospheric gas oil (AGO), five materials entering side line thing of No. 1, ethylene unit are respectively atmospheric gas oil (AGO), naphtha, light naphthar, cracking tail oil and propane, four materials going out side line are ethene respectively, propylene, cracking c_4 and cracking light oil.Learn in conjunction with production technology, a survey line of AGO charging buffer tank to the AGO charging survey line transferring raw material of ethylene unit 1#, can be connected so go out side line with directed line segment by one of AGO charging buffer tank with the AGO feeding line of No. 1, ethylene unit.

By that analogy, determine the side line material composition of all system components in production system, and determine that then the Flow of Goods and Materials relation between all side lines indicates with directed line segment.

Step 1-4: according to the annexation in step 1-3, determines the Flow of Goods and Materials relation in whole production system, thus determines the annexation between all system components, the production technological process of whole production system of finally completing.

Step 2: based on obtained production technological process, determine the production information (actual is initial production information) of production system, and the mathematics production models set up based on MILP (Mixed Integer Linear Programming), to be optimized production information by solving-optimizing model, thus to provide important data and Informational support for formulating the production schedule.

Step 2-1: determine into plant stand point, stores tank field, process units, the production information of split point, confluence and this six type systematics component of website of dispatching from the factory:

Enter material variety and the flow information of plant stand point, enter the material variety of plant stand point and flow information one of the decision variable as Optimization Solution, just can be obtained by Optimization Solution model.

Store the production information that comprises of tank field to comprise: tank field production cycle tank storage originally (namely originally tank storage), table 1 gives the production cycle originally tank storage of part tank field.

Table 1

The production information of process units comprises: process units processing scheme information;

Split point comprises production information and comprises: enter side line, go out side line material variety;

The production information that confluence comprises comprises: enter side line, go out side line material variety;

The production information that the website that dispatches from the factory comprises comprises: the material variety of the website that dispatches from the factory and the market demand thereof.

Meanwhile, determining material information involved in process industry production system, material price list is as shown in table 2.

Table 2

The cycle information that certainty annuity is produced, the production cycle of the present embodiment is as shown in table 3.

Table 3

Step 2-2: according to explained hereafter process flow diagram and the determined production information of step 2-1, system production information be described and set up mathematical constraint, determining planning optimization target, setting up MIXED INTEGER linear model (i.e. objective function).

First determine that the target of Optimization Solution is production maximizing the benefits, its mathematical expression formula is:

$\begin{array}{c}MaxOBJ=\underset{t\∈T}{\mathrm{\Σ}}\underset{cm\∈{\mathrm{MT}}_c}{\mathrm{\Σ}}{\mathrm{TRQ}}_{out,in,ts,cm,t}\×P_{cm}-\underset{t\∈T}{\mathrm{\Σ}}\underset{cm\∈{\mathrm{MT}}_R}{\mathrm{\Σ}}{\mathrm{TRQ}}_{out,in,ts,cm,t}\×P_{cm}-\\ \underset{t\∈T}{\mathrm{\Σ}}\underset{ts\∈TR}{\mathrm{\Σ}}{\mathrm{TRQ}}_{out,in,ts,cm,t}\×{\mathrm{TC}}_{ts}-\underset{t\∈T}{\mathrm{\Σ}}\underset{u\∈U}{\mathrm{\Σ}}{\mathrm{UQ}}_{u,t}\×{\mathrm{OC}}_u-\\ \left(\underset{t\∈T}{\mathrm{\Σ}}\underset{tk\∈TK}{\mathrm{\Σ}}\underset{cm\∈{\mathrm{MT}}_{tk}}{\mathrm{\Σ}}{\mathrm{TQ}}_{tk,cm,t}\×{\mathrm{HC}}_{tk,cm,t}+\underset{t\∈T}{\mathrm{\Σ}}\underset{s\∈S}{\mathrm{\Σ}}\underset{cm\∈{\mathrm{MT}}_{ss}}{\mathrm{\Σ}}{\mathrm{SQ}}_{s,cm,t}\×{\mathrm{HC}}_{s,cm,t}\right)-\underset{t\∈T}{\mathrm{\Σ}}\underset{\∀cm\∈{\mathrm{MT}}_c}{\mathrm{\Σ}}{\mathrm{DPQ}}_{cm,t}\×{\mathrm{DPC}}_{cm}\end{array}---\left(1\right)$

In formula, Section 1 is the gross profit that production system product is sold, Section 2 is raw material buying expenses, Section 3 is the trucking costs of raw material and product, Section 4 is the processing charges that all processing unit (plant)s produce, Section 5 and Section 6 are the inventory cost of product and intermediate material, Section 7 be the market demand do not meet be the penalty term caused.

Then, the various constraint conditions in production run are determined:

TRQ _{out,in,ts,rm,t}＝RQ _rm,t(2)

${\mathrm{RQ}}_{rm}^{lb}\≤{\mathrm{TRQ}}_{out,in,ts,rm,t}\≤{\mathrm{RQ}}_{rm}^{up}---\left(3\right)$

Formula (2) represents that each passes through the raw material into plant stand point input production system, and its purchase volume is equal with freight volume; Formula (3) defines the scope of raw material transport throughput rate, requires that raw material transport throughput rate is between the minimum value and maximal value of raw material purchase volume.

TRQ _{out,in,ts,cm,t}≤DQ _cm,t(4)

DPQ _cm,t≥DQ _cm,t-TRQ _{out,in,ts,cm,t}(5)

DPQ _cm,t≥0(6)

Formula (4) represents that the output quantity of product can not exceed default product consumption, namely requires that the quantity delivered of product can not exceed the actual demand amount in market.Formula (5) is pointed out when Product supply can not meet preset need, and supply difference equals default product consumption and deducts actual product output quantity; It is nonnegative value that formula (6) defines Product supply difference.

TRQ _{out,in,ts,cm,t}＝STRIQ _u,in,cm,t(7)

TRQ _{out,in,ts,cm,t}＝STROQ _u,out,cm,t(8)

MOQ _{out,in,mv,cm,t}＝STRIQ _u,in,cm,t(9)

MOQ _{out,in,mv,cm,t}＝STROQ _u,out,cm,t(10)

${\mathrm{TRQ}}_{out,in,ts,cm,t}^{lb}\≤{\mathrm{TRQ}}_{out,in,ts,cm,t}\≤{\mathrm{TRQ}}_{out,in,ts,cm,t}^{up}---\left(11\right)$

${\mathrm{MOQ}}_{out,in,mv,cm,t}^{lb}\≤{\mathrm{MOQ}}_{out,in,mv,cm,t}\≤{\mathrm{MOQ}}_{out,in,mv,cm,t}^{up}---\left(12\right)$

Formula (7) and formula (8) represent that production system limit transport pipeline freight volume is equal with the flow of the initial side line be attached thereto, target survey line.Formula (9) and formula (10) represent that production system inside transport pipeline is equal with the flow of the initial side line be attached thereto, target survey line.Formula (11) defines the flow bound of production system limit transport pipeline; Formula (12) defines the flow bound of production system inside transport pipeline.

$\underset{in\∈{\mathrm{ST}}_i}{\Σ}{\mathrm{STRIQ}}_{u,in,cm,t}=\underset{out\∈{\mathrm{ST}}_o}{\Σ}{\mathrm{STROQ}}_{u,out,cm,t}---\left(13\right)$

$\underset{in\∈{\mathrm{ST}}_i}{\Σ}{\mathrm{STRIQ}}_{u,in,cm,t}=\underset{out\∈{\mathrm{ST}}_o}{\Σ}{\mathrm{STROQ}}_{u,out,cm,t}---\left(14\right)$

Formula (13) represents at system pipeline split point place, and the inlet amount of material of the same race equals the summation of each bar pipeline material output of the same race.Formula (14) expression is confluxed at system pipeline and is pointed out, and material of the same race each pipeline charging summation equals the load of material of the same race.

${\mathrm{RUN}}_{u,um,t}\×{\mathrm{UQ}}_{u,t}^{lb}\≤{\mathrm{MOQ}}_{u,um,t}\≤{\mathrm{RUN}}_{u,um,t}\×{\mathrm{UQ}}_{u,t}^{up}---\left(15\right)$

${\mathrm{UQ}}_{u,t}=\underset{um\∈{\mathrm{MOI}}_u}{\Σ}{\mathrm{MOQ}}_{u,um,t}---\left(16\right)$

${\mathrm{UQ}}_{u,t}=\underset{in\∈{\mathrm{ST}}_i}{\Σ}{\mathrm{STRIQ}}_{u.in,cm,t}---\left(17\right)$

${\mathrm{STROQ}}_{u,out,cm,t}=\underset{um\∈{\mathrm{MOI}}_u}{\Σ}{\mathrm{MOQ}}_{u,um,t}\×{\mathrm{YIE}}_{um,cm}---\left(18\right)$

Formula (15) is described and restriction to formula (18) the production decision of processing unit (plant) in production system.Formula (15) represents that the inventory of the particular process scheme process of any device is no less than the product of this processing unit (plant) working ability lower limit and particular process scheme application duration, is no more than the product of this processing unit (plant) working ability upper limit and particular process scheme application duration simultaneously.Formula (16) represents that the processing total amount of any processing unit (plant) equals processing capacity sum under the various processing scheme of this process units.Formula (17) represents that the processing total amount of any processing unit (plant) also equals the summation of this device charging in the corresponding production cycle.Formula (18) describes the yield model of processing unit (plant), represents that the exit side linear flow rate total amount of any processing unit (plant) equals respective side linear flow rate sum under each processing scheme of this device; Wherein on the downside of each processing scheme, linear flow rate equals the output of line material on the downside of this kind of processing scheme.

In optimized mathematical model (i.e. objective function), website and tank field have material memory function, in order to distinguish the starting material amount of website and tank field, the cycle of production run are divided into initial period T here ₀and other situations process.

${\mathrm{SQ}}_{u,cm,t_0+1}={\mathrm{SQ}}_{u,cm,t_0}+\underset{in\∈{\mathrm{ST}}_i}{\mathrm{\Σ}}{\mathrm{STRIQ}}_{u,in,cm,t_0}-\underset{out\∈{\mathrm{ST}}_o}{\mathrm{\Σ}}{\mathrm{STROQ}}_{u,out,cm,t_0}---\left(19\right)$

${\mathrm{SQ}}_{u,cm,t}={\mathrm{SQ}}_{u,cm,t-1}+\underset{in\∈{\mathrm{ST}}_i}{\mathrm{\Σ}}{\mathrm{STRIQ}}_{u,in,cm,t}-\underset{out\∈{\mathrm{ST}}_o}{\Σ}{\mathrm{STROQ}}_{u,out,cm,t}---\left(20\right)$

${\mathrm{SQ}}_{u,cm,t}^{lb}\≤\underset{cm\∈{\mathrm{MT}}_{ss}}{\Σ}{\mathrm{SQ}}_{u,cm,t}\≤{\mathrm{SQ}}_{u,cm,t}^{up}---\left(21\right)$

Formula (19) and formula (20) represent that when cycle production time be initial operating time T ₀time, the inventory that website stores equals website initial storage amount and adds that website enters side line flow and deducts website again and go out side line flow; And when running between be not initial operating time T ₀time, the inventory that website stores equal one production cycle Mo material memory space add that this production cycle enters side line flow and deducts this production cycle again and go out side line flow.Formula (21) defines the bound of website memory space.

${\mathrm{TQ}}_{u,cm,t+1}={\mathrm{TQ}}_{u,cm,t_0}+\underset{in\∈{\mathrm{ST}}_i}{\mathrm{\Σ}}{\mathrm{STRIQ}}_{u,in,cm,t_0}-\underset{out\∈{\mathrm{ST}}_o}{\Σ}{\mathrm{STROQ}}_{u,out,cm,t_0}---\left(22\right)$

${\mathrm{TQ}}_{u,cm,t}={\mathrm{TQ}}_{u,cm,t-1}+\underset{in\∈{\mathrm{ST}}_i}{\mathrm{\Σ}}{\mathrm{STRIQ}}_{u,in,cm,t}-\underset{out\∈{\mathrm{ST}}_o}{\Σ}{\mathrm{STROQ}}_{u,out,cm,t}---\left(23\right)$

${\mathrm{TQ}}_{u,cm,t}^{lb}\≤\underset{cm\∈{\mathrm{MT}}_{tk}}{\Σ}{\mathrm{TQ}}_{u,cm,t}\≤{\mathrm{TQ}}_{u,cm,t}^{up}---\left(24\right)$

Formula (22) and formula (23) represent that when cycle production time be initial operating time T ₀time, the inventory that tank field stores equals tank field initial storage amount and adds that tank field is entered side line flow and deducted tank field again and go out side line flow; And when running between be not initial operating time T ₀time, the inventory that tank field stores equal one production cycle Mo material memory space add that this production cycle enters side line flow and deducts this production cycle again and go out side line flow.Formula (24) defines the bound of tank field memory space.

(3) parameter and variable implication

Variable wherein in above mathematical model and meaning of parameters as follows:

S---entry and exit factory Website Hosting

U---processing unit (plant) set

R---raw material supply point (supplier) is gathered

C---output of products point (client) is gathered

SS---storage site set

TK---store tank field set

SM---point confluence

SM _s---split point set

SM _m---confluence is gathered

ST---side line set

ST _i---enter side line set

ST _o---go out side line set

ST _u---the side line set of process units u

MV---the mobile transport set in production system inside

TR---production system Boundary Moving transport set

MT---all material set

MO _u---all processing scheme set of device u

MOI _u---device u processing scheme information aggregate

MT _s---the set of website s material

MT _r---all feed product set

MT _c---the set of all product materials

MT _ss---the set of storage site SS material

MT _tk---tank field TK material set

T---optimize time set

OBJ---production economy benefit, unit

CPRO---sales and distribution cost, unit

CPUR---raw material buying expenses, unit

CTS---material transportation expense, unit

COP---device processing charges, unit

CHO---stock control expense, unit

CDP---product demand does not meet rejection penalty

DEM _{cm, t}---material cm in the demand of production cycle t, ton

P _cm---the unit price of material cm

TC _ts---transport the transport unit price of mobile ts

OC _u---the processing unit price of processing unit (plant) u

HC _{u, cm, t}---device u is to the inventory cost of material cm in time t

DPC _cm---the rejection penalty of product cm unit inventory when unmet demand

IN _{um, cm}---the charge proportion of corresponding material cm in processing scheme um

YIE _{um, cm}---the productive rate of corresponding material cm in processing scheme um

STRQ _{no, st, cm, t}---on the side line st of node no (device, website or point confluence) in time t, the flow of material cm on side line, ton

STROQ _{no, out, cm, t}---node no (device, website or point confluence) goes out side line st in time t, goes out the flow of material cm on side line, ton

STRIQ _{no, in, cm, t}---node no (device, website or point confluence) enters side line st in time t, enters the flow of the material cm on side line, ton

MQ _{out, in, mv, cm, t}---from going out side line out to the flow of the material cm of mobile mv in time t entering side line in, ton

TRQ _{out, in, ts, cm, t}---from going out side line out to the mobile flow transporting the material cm of ts in time t entering side line in, ton

SQ _{u, cm, t}---the memory space of storage site u material cm in time t, ton

TQ _{u, cm, t}---store the memory space of tank field u material cm in time t, ton

DQ _{cm, t}---the demand of product cm in time t, ton

RUN _{u, um, t}---the processing number of times of device u under processing scheme m in time t, secondary

MOQ _{u, um, t}---processing capacity when device u is in scheme um in time t, ton

UQ _u,t---the processing capacity of device u in time t, ton

RQ _{cm, t}---the amount of purchase of raw material rm in time t, ton

DPQ _{cm, t}---the unsatisfied inventory of product cm in time t, ton

Subscript:

Up---the upper limit

Lb---lower limit

Ini---initial value

Subscript:

U---device

S---website

Tk---storage tank

Um---device processing scheme

Cm---material

T---the time cycle

Ts---transport

Mv---mobile

No---node

St---side line

In---enter side line

Out---go out side line

Rm---raw material

Step 2-3: the mathematical model (i.e. objective function) in step 2-2 is solved.

Adopt IBMILOGOptimizationStudio12.4 to carry out solving of model in this example, the solver called is: CPLEX12.4.0.The concrete configuration solving relied on PC platform is: IntelXeonE5-2403CPU, dominant frequency 1.8GHz, internal memory 8G, operating system WindowsSever2008.The MIXED INTEGER linear model (MILP) of this production system altogether comprises 6408 constraint conditions in solution procedure, 3061 variablees, and wherein integer variable is 186, and continuous variable is 2875, calculates 5.40s consuming time.

Solved by actual, what also demonstrate model has solution certainty; Have also been obtained the globally optimal solution of optimization simultaneously.

Step 2-4: according to solving the parameter information obtained, correspondence obtains the concrete production information (i.e. final production information) in production system, production information specifically comprises: raw material type and amount of purchase thereof, product category and sales volume thereof, the processing scheme of process units, tank field closing stocks, and the flow etc. of transport line.

By analyzing the solving result of step 2-4, the production information relevant to production line can be obtained.

Table 4 analyzes the product sales revenue of production system, and device operation processing charges, raw material buying expenses, material transportation expense, stock material expense, product demand does not meet expense and productivity effect 7 indexs.

Table 4

Kind and the flow of the raw material bought can also be obtained simultaneously.Table 5 illustrates the purchase volume of different raw materials:

Table 5

As can be seen from the above table in the production cycle in 2014-5 to 2014-7 March, every month is for the purchase volume of different material.

Table 6 illustrates the market demand of portioned product, effective sale amount, and the non-meet volume of the market demand.

Table 6

Upper table, for diesel oil and propylene two kinds of products, gives the monthly output information of integraterd manufacturing system product, and this information is contrasted with the pre-set product demand before production.As can be seen from the table: for " 2014_5 " to " 2014_7 " three months, the product yield of diesel oil meets the pre-set product demand before production; And the product yield of propylene exist respectively " 2014_5 " and " 2014_6 " bimester 19 tons with 119 tons do not meet difference.

Table 7 illustrates storage tank end of term tank and deposits information:

Table 7

For Naphtha tank, diesel product tank and product butadiene tank in upper table, give three storage tank " 2014_5 " to " 2014_7 " material reserves at the trimestral the end of month.As can be seen from data in table: naphtha tank 1# is as a material buffer tank, and in " 2014_5 " to " 2014_7 " three middle of the month, stock is steady, does not have naphtha to retain, this is because downstream component by all naphthas for the production of processing.Diesel product tank all maintains stable retention amount in above three middle of the month, for tackling the demand fluctuation situations such as the product demand surge in market.And product butadiene tank has trickle fluctuation in the tank storage in " 2014_5 " to " 2014_7 " three middle of the month, this with this three the middle of the month product butadiene demand fluctuation be associated.

Claims (8)

1. a control method for process industry production system, is characterized in that, comprises the steps:

(1) according to the condition of production and the Production requirement constructing system model at the scene of process industry production system, and production technological process is drawn;

(2) based on described production technological process, determine the production information of process industry production system, and set up the objective function based on MILP (Mixed Integer Linear Programming);

(3) to be optimized described objective function to solve with the maximum optimization aim that turns to of system productivity effect, the production information that is optimized is for the process industry production system described in controlling.

2. the control method of process industry production system as claimed in claim 1, it is characterized in that, described step (1) comprises the steps:

(1-1) system element in process industry production system is divided into following six classes according to function and structure: enter plant stand point, stores tank field, process units, split point, confluence and the website that dispatches from the factory;

(1-2) in conjunction with the practical condition of process industry production system, the structural information of each system element in determining step (1-1);

(1-3) material and the Flow of Goods and Materials relation of each system element side line in production run is determined, determine the annexation of side line between each device, and complete the logic connecting relation of each side line, thus obtain system model, and drafting obtains corresponding flow sheet.

3. the control method of process industry production system as claimed in claim 2, it is characterized in that, described step (1-2) is specific as follows:

The structural information entering plant stand point comprises and goes out side line quantity into plant stand point;

Store the structural information of tank field to comprise and store entering side line quantity, going out side line quantity of tank field;

What the structural information of process units comprised process units enters side line quantity, goes out side line quantity;

What the structural information of split point comprised split point goes out side line quantity;

Side line quantity is entered in the confluence that the structural information of confluence comprises;

What the structural information of website of dispatching from the factory comprised the website that dispatches from the factory enters side line quantity.

4. the control method of process industry production system as claimed in claim 3, it is characterized in that, described step (1-3) is specific as follows:

Determine the material variety in the side line of each system components, and according to the flowing relation of practical condition determination material, go out side line with the directive line of band by what be associated and enter side line and be connected, in order to indicate the flowing relation of material.

5. as the control method of the process industry production system in Claims 1 to 4 as described in any one, it is characterized in that, described step (2) comprising:

(2-1) production information of each system element in process industry production system is obtained;

(2-2) production technological process described in utilization, sets up the objective function based on MILP (Mixed Integer Linear Programming) according to the production information of each system element.

6. the control method of process industry production system as claimed in claim 5, it is characterized in that, the production information of each system element is as follows:

Enter the material variety entering plant stand point and flow information that plant stand point production information comprises;

The production information storing tank field comprises tank field production cycle tank storage originally;

The production information of process units comprises the processing scheme information of process units;

The production information of split point comprises entering side line, going out side line material variety of split point;

The production information of confluence comprises entering side line, going out side line material variety of confluence;

The production information of website of dispatching from the factory comprises material variety and the market demand thereof of the website that dispatches from the factory.

7. the control method of process industry production system as claimed in claim 6, it is characterized in that, described objective function is the productivity effect of process industry production system, and:

Productivity effect=production product income-product purchase cost-material transportation cost-process units processing cost-material carrying cost-market demand does not meet penalty term;

The described market demand does not meet rejection penalty that penalty term is each product unit inventory when unmet demand of process industry production system and the sum of products of the unsatisfied inventory of corresponding product in each time period.

8. the control method of process industry production system as claimed in claim 7, it is characterized in that, objective function is optimized when solving using material balance as constraint condition.