Optimal loading the systems for resource consumption in case of multiproduct and multipurpose batch

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Optimal loading the systems for resource
consumption in case of multiproduct and
multipurpose batch chemical plants

(theoretical aspects and softwarerealization)
K.Mintchev,E.Shopova,B.Ivanov Institute of
Chemical engineering- Bulgarian academy of
sciences ul. Acad. G.Bonchev, 103, Sofia
1113 Fax [phone] e-mail
bivanov_at_bas.bg
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The objects which are considering using ECAM to
solve the problem about operative management are

• Multipurpose batch chemical systems

2. Multiproduct batch chemical systems
3. Manufacture plants including Multiproduct
and Multipurpose batch chemical systems, which
have shared consumption systems

• These systems are the most frequently used in
• Pharmaceutical industry
• Fine chemical plants
• Food industry
• Paint and varnish manufacturing.

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Multipurpose batch chemical systems
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V5m3
V15m3
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V5m3
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1 Batch size80kg Cycle time10h
V8m3
1 Batch size250kg Cycle time15h
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2 Batch size70kg Cycle time12h
2 Batch size250kg Cycle time15h
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3 Batch size150kg Cycle time15h
V15m3
3 Batch size250kg Cycle time15h
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4 Batch size100kg Cycle time15h
4 Batch size250kg Cycle time15h
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5 Batch size250kg Cycle time15h
5 Batch size250kg Cycle time15h
Steam plant
Electric plant
Water
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V12m3
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Production scheduling model
G1 - Planed minimal quantity , which have to be
manufactured for product 1
G2 - Planed minimal quantity , which have to be
manufactured for product 2
The task of Optimal synthesis of manufacture
scheduling is arrived to identify the campaigns,
which are participate and working time, so that
the optimal criteria to be satisfied. The
criteria are
1. Minimum time duration programm.
2. Maximum profit for planning horizon.
MIN(ts1tc1ts2tc2... ts14tc14)
MAX(P1r P2r)
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Loading the consumption systems in case of
manufacture campaigns
Optimal wait time after each batch
Optimal batch size
Optimal start time of manufacture
Optimal loading of steam station in case of
simultaneous work of two manufacture
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Mathematical formulation of the problem
1. Data Let be introduced the following sets
Set Ii1,i2,,iN set of products Set
Jj1,j2,,jN set of stages Set Pp1,p2,,pJ set
of processes
Also the following data are known
Stage duration can be calculated for each stage
each product
The required demand for each product per a
horizon H.
Time horizon H. The cycle time can be calculated
for each productExpression for connecting
Max or Min batch size can be calculated for each
product
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Mathematical formulation of the problem
CONTINUOUS VARIABLES
1. Shifting time for the entire product
These variables present the time of shifting the
beginning of each product with regard the
horizon beginning.
2.The waiting time between different batches
3. Batch size
The batch size for each product could be changed
in the pointed upper and lower boundaries
determined from the technologies. These variables
affect on the power of energy consumption and/or
the time of waiting between batches.
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Mathematical formulation of the problem
CONSTRAINTS
The following constraints are introduced
1.The batch size constraints
2.The waiting time between different batches
Where Ni present the minimum batch numbers that
must be manufactured into a time horizon H.
3.The products shifting time constraints
4. The production constraints
5. The horizon constraints
6. Energy consumption constraints for
simultaneous manufacturing of products
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Mathematical formulation of the problem
Mathematical model of energy
consumption
The energy consumption curve for each stage of
given product can be written, by using the
Fourier transformation as
Where
are the respective Fourier coefficients for the
function distributing stage j o product I. These
coefficients are introduced for the cases when
the energy consumption has the constant power as
it was shown on the pictures.
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Mathematical formulation of the problem
Mathematical model of energy
consumption
Based on the Fourier transformation of the
functions of energy consummationswe are able to
present the following functions.
1. Energy consumption of stage j of product I
Where
2. Energy consummation of product I
Where
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Mathematical formulation of the problem
Mathematical model of energy
consumption
3. Energy consumption of entire campaign
Where
The constant part of the power of energy
consumption distribution in case of simultaneous
product processing presents the ideal case that
must be reached. The variable parts of the
above functions present the variation of the real
curve around the ideal one. For the variable
parts the following is valid
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Mathematical formulation of the problem
Objective function
Case1. The minimum variation of the real curve
with regard to the ideal one to be ensured.
Case 2. The minimum of energy consumption over
the given determined in advance level of energy
consumption.
Case 3. Maximum profit of the product
manufacturing
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The offered software package is created on the
base of original authors methods published in
international journals. Its present version uses
MATLAB 6.5 and is adopted for WINDOWS-XP.
The software package ECAM solves two main
problems
1.Control problem - for a group of compatible
batch products

• 2.Simulation problem - for such
• of product group aiming to determine load
  parameters
• of resources supply systems.

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ECAM could be used for investigation of different
manufacturing states and as well as for
evaluation the affect of energy integration
processes on the resources supply systems. Thus,
the technology changes could be properly assessed
that provides opportunities for creation of
proper production schedules ensuring optimal load
of resources supply systems.
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Main principles during the build up of ECAM

• The menus principle is used
• The principle of choices the data is used so that
  the human mistakes be reduced.
• Logical control about correctness the data
• The results are visualized
• All functions consist of subsidiary information
  ECAM working under WindowsXP area
• Matlab 6.50 is used to build up the product

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RUN PROGRAMME
Exit programme
Information gives a detailing account about
different task classes and objects in which ECAM
can be used.
Information about authors and description of the
theoretical base in which ECAM is made of.
After activating (push the button ) the necessary
information (data base) is charged in the
operative memory (RAM). ECAM is started.
Help
Information About authors
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INPUT DATA BATCH PLANTS
INPUT DATA TECHNOLOGY
INPUT DATA CAMPAIGN
Module for creation a date base for a production
system. It ensures a proper description of the
existing plant units and connection between them
OPTIMAL SHEDULING
Module for creation a date base for
technologies. It ensures description of different
technologies available For processing in the
plant.
Module for formulation of different classes
controlling problems. It involves definition of
criteria for optimal control and set of
constraints.
VIZUALIZATION OF SHEDULING
Module for automatically generation or
customization of production campaign (group of
compatible products) available to fulfill a given
production demands.
PRINT SHEDULING
Module for formulation of different classes
controlling problems. It involves definition of
criteria for optimal control and set of
constraints.
Module for graphical interface for visualization
the results obtained under optimal scheduling of
campaign.
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Data for the apparatus and connection between
each other in material flow.
Charging the data base about existing apparatus
and connection between them.
Rule buttons -add new apparatus -delete the
apparatus -edit data base of current
apparatus -save data base of current
apparatus -exit form this module -help.
1.Short name of plant. 2.Full name of
plant. 3.Number of apparatus in Data Base.
Visualization of apparatus which include -short
name of apparatus -image of apparatus -basic
characterizations -image of type apparatus
Creation the new connect or imaging of the
existing connects between apparatus.
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Data technology.
Information about resources -quantity of each
resource required to one unit final
product -apportionment of resources in
time -consumption quantity for the stage.
Rule buttons -add new apparatus -delete the
apparatus -edit data base -save data base
-exit form this module -help.
Buttons which charge data base of chosen
technology -number of stages -obtainable
profit for unit product.
Description the data for each stage of
technology -name of stages -time of
stage -size factor -type of apparatus.
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Rule module for synthesis tasks of production
variants and campaign.
Manuel generation campaign Design of
manufacturing campaigns which a determinate group
of manufacture. The program gives possibility to
define the stages of each apparatus on given
manufacture. After successful defining of all
stages and manufactures the next step is to
calculate evaluation of each variant which are
included in given campaign.
Automatically generation campaign maximum
length Define the available manufacturing
campaign , each one consist of -maximal number
manufactures which the manufacture program is
made of. For obtainable manufacture campaign
evaluate are given and also the variants of every
manufacture which are included in relevant
campaign.
Automatically generation sets full campaign
Define maximal number of campaign in case that
the manufacture are given. For each variant of
manufacture campaign variant which are consist of
are given.
Generation of given technology. Calculating
available disposing in a given technology and
parameters which are consist of -Minimum batch
size -Maximum batch size -Cycle time -Minimum
available manufacturing quantity -Maximum
available manufacturing quantity
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Define the variants of disposing of given
technology
List of apparatus which are disposing on every
stage of technology of considering variant. That
also include information about -Maximum batch
size -Minimum batch size -Cycle time -Maximal
and minimum product demand.
Define the variants in case of given data base.
Rule buttons -delete the technology -edit data
technology -save technology to data base
-exit form this module -print variant -help.
Lead in the data base of technology -Short name
of technology -Full name of technology -Number
of stages.
Lead in the data base about planning horizon.
Lead in the data base about production demand
-Minimum demand of product -Normal demand of
product -Maximum demand of product Lead in the
data base about work regime -Whit overlapping
the cycle -Without overlapping the cycle.
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Design the manufacturing campaign from the
customer.
Rule buttons -add new campaign -delete
campaign -edit data base -save to data
base -exit -help.
Read the campaigns data base
Output information about the campaign -Maximum
batch size -Minimum batch size -Cycle time
whitout overlapping -Cycle time whit
overlapping
Vizualization of apparatus in which the stage
will carry out.
Choise the existing campaign from data base or
lead in the data for new one.
Choise of relevant product who will be
manufactured simultanuasly in campaign.
Lead in the stage into relevant apparatus.
Choise tha apparatus in which the stage will
carry out.
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Synthesis of variants of campaigns with relatable
size to number of manufacture which are included
in a plan.
Output information about obtained variant of
campaign -list of apparatus which have to placed
in relevant stage -basic characterization -maxim
um batch size, minimum batch size -cycle
time -maximum demand,minimum demand -maximum
number of variants.
Rule buttons -delete campaign -edit data base
of given campaign -save to data
base -exit -help.
Lead in the data base of existing manufacture
plan or including the new one.
Choice the regime of manufacture -With
overlapping the cycle or without overlapping the
cycle -Production demand for the
product -minimum product quantity -normal
product quantity -maximum product
quantity -Include the planning horizont.
Calculating the all available campaigns which are
consist of the maximum number manufacture working
at the same time.
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Synthesis of maximal number independent
campaigns.
Generalize information of found campaign, Gives
the maximum number of in depended campaign.
Rule buttons -delete campaign -edit data base
of given campaign -save to data
base -exit -help.
Lead in the data base of existing manufacture
plan or including the new one.
Choice the regime of manufacture -With
overlapping the cycles or without overlapping the
cycles -Production demand for the
product -minimum product quantity -normal
product quantity -maximum product
quantity -Include the planning horizon.
Calculating the all available campaigns which are
consist of the maximum number manufacture working
at the same time.
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Output the result of procedure of synthesis of
maximal number independent campaigns in given
manufacture plan.
Choice the manufacture variant included in given
campaign which will be show on.
Rule buttons -delete campaign -edit data base
of given campaign -save to data
base -exit -help.
List of apparatus in which have to placed the
relevant stages.
Output the obtained results for given variants of
campaign.
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Module explaining different optimizing tasks.
Optimal scheduling. Optimal scheduling
multicriteria formulation. 1.Minimum time
production plane. 2.Maximum profit. Restriction 1
.Minimum demand 2.Minimum resource.
Optimal use of resource. Optimal sheduling for
given variant of canpaign-one criteria
formulation.
Optimal use of resource. Optimal sheduling for
full variant of canpaign. Multicriteria
formulation.
Optimal use of resource. Optimal sheduling for
full variant of canpaign. One criteria
formulation.
Optimal scheduling. Optimal scheduling with
possible one criteria. 1.Minimum time poduction
plane. 2.Maximum profit. Restriction 1.Minimum
demand 2.Minimum resource.
Optimal use of resource. Optimal sheduling for
given variant of canpaign. Multicriteria
formulation.
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Optimal loading the system. /formulation the task/
Define the optimization criteria for chosen
campaign who consist of -resource for
optimization -choice the regime -variation -
constant
Output the results -included technologies -opt
imal start time -optimal wait time -optimal
batch size. Of each manufacture
Define the restrictions which are consist
of -restrictions about another
resources -minimum and maximum quantity in case
of constant -minimum and maximum quantity in
case of variation.
Choise the variant of campaign who will search
optimal rule, in case of choosen criteria and
defineded restrictions.
Read the data base for existing plans and
available campaign.
Define the planning horizon in which a given
campaign have to be done.
Start the optimization procedure
Define the quantity demand of each product.
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Optimal loading the system in case of given
manufacture program.
Define the optimization criteria for chosen
campaign who consist of -resource for
optimization -choice the regime -variation -
constant
Output the results -included technologies -opt
imal start time -optimal wait time -optimal
batch size. Of each manufacture
Define the restrictions which are consist
of -restrictions about another
resources -minimum and maximum quantity in case
of constant -minimum and maximum quantity in
case of variation.
Choise the variant of campaign who will search
optimal rule, in case of choosen criteria and
defineded restrictions.
Read the data base for existing plans and
available campaign.
Define the planning horizon in which a given
campaign have to be done.
Define the quantity demand of each product.
Start the optimization procedure
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Optimal loading the system in case of given
manufacture program.
Lead in the nesesary information which are
consist of -DB for existing plants -Planning
horizon -Production demands for each
product -Optimization criteria -Restrictions.
Output the optimal parameters of each campaign
which are consist of -Service time -Time
duration campaign -List of manufacture included
in campaign -Start times -Wait time -Cycle
time -Optimal batch size -Optimal batch
number -Quantity which are manufactured during
campaign.
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Visualization of obtainable scheduling.
Summarize data -Batch size -Start
time -variation -wait time -constant
production -horizon
Choice the resource for visualization
Choice the production of given campaign
Summarize data -variation -max pic -min pic
Manual input the data -Batch size -Start
time -wait time -horizon
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Thank you for your attention