Simulation and Optimization of a Kind of Manufacturing
&PackingProcesses
Chun-youLi
College of Transportation & Logistics, CSUFT, Changsha, HN, China
Accounting School, GXUFE, Nanning, GX, China
(lcy0731@qq.com)
Abstract - There’re many factors that influence each
other in production-packaging processes. Resources, objects,
processes and their properties & behaviors can be simulated
to construct a computer simulation model across the whole
production-packing process. Usually, the minimized cost,
maximized profit or reasonable utilization was targeted as
the decision objective, and concerned parameters was
configured as conditions in the simulation model. With
enough repeated runs, the optimization module can seek the
best equipment combination and the best production
schedule.
Keywords - Manufacturing & packing, Simulation,
Optimization
I. INTRODUCTION
In some industries such as food & tobacco industry,
the terminal product is generally made from the
production line and packaged into small boxes or small
bags. The basic process is to produce these products
through one or more production lines, and delivery or
transfer products to packaging. Finally, the smallpackaging products are filled into a larger container
through one or more packaging equipments continuously
or partially and gotten out the lines. Fig.1 is the schematic
diagram of such production and packaging process, two
manufacturing lines produce the same kind of products,
then transfer them to three coordinate packing lines
through a series of buffer vessels, finally package them
into finished goods.
In cases such as designing and recreating a new
packaging process or managing an existing process, we
often have to face the following questions as: how to
reduce process failure? How to reduce the processing
cycle time? How much is the reasonable buffer capacity
and the buffer stock? How to deal with the change of
production scale? And is it necessary to add more and
higher ability production lines, packaging lines and
container?
To simplify the analysis, we can do analysis and
make decision with single process and single factor. For
example, the expansion of the production and logistics
ability can be determined with the output of production or
both speeds. But the whole process is complex and the
relationship between processes is uncertain. Additionally,
there’re various factors influencing mutually in processes
and these factors always interact dynamically along with
time and events. Once a suggestion was put forward or a
measure was imposed, it may be hard to predict the
ultimate effect brought by the changes, so it is very
difficult to determine the exact priority order of the
measures. For example, in order to maintain the reliability
and the inventory balance across processes, designers can
use greater inventory to deal with the less reliability of
equipments. On the contrary, by improving the reliability
of the upstream through equipment, he can reduce the
storage in the processes. Both measures can ensure to
meet the needs of the downstream material and ensure
that production runs smoothly. Even if the relationship
among production, package or buffer process is certain,
there are still many factors interact each other. For
example it is difficult to evaluate the influence degree of
the mutual isolated factors on the production scheduling,
as well as the control of the operation sequence and
rhythm, the product quantity, structure of the production,
or the characteristics of products and so on. These factors
may affect production speed, lead to the failure or
production conversion. In addition, due to manufacturing
and packing may be arranged in different positions apart
from each other, and the difference of scheduling method
and the enterprise culture require different rhythms of
production, the complexity to solve the problems will also
be increased.
There’s a variety of decision tools and the
experimental methods to deal with in this kind of
material
Buffer 1
material
Package 1
Machine 1
Buffer 2
material
Package 2
Buffer 3
material
Machine 2
Buffer 4
Package 3
Fig.1.the schema of production & packaging process
Final goods
problems that schedule manufacturing & packing with
multifactor. This paper presents a simulation method that
simulates the process and interacting factors. It analyses
and evaluates the problems and forecast the effect of the
decision that have been designed or improved. It provides
a tool to test design idea or improvement effect by
developing a manufacturing-packing simulation model.
Just as simulation driving-cabin can help the driver to
learn driving in the best way and to build a good habit, a
manufacture & packaging simulation model can be used
to test and optimize the manufacture & package[1].
II. MODELING AND SIMULATING GENERALLY
The tool that is used to simulate and solve the
problem is the simulation model, or called simulator.
Specific simulation model is based on the research goal
concerning with the problem to solve. This paper involves
a factory to build a new manufacture & packing system.
Preliminary design assume there were two production
lines in the factory and each production line can produce
any kind of the basic specifications. There were three
packaging lines to pack the products into kinds of size and
the shape of the containers with different labels. There
were many parallel buffer tanks between production lines
and packing lines which can receive products from any
production line, then put the products to any packing line.
The production lines and the buffer tanks should be
cleaned before transform the line for new products.
The simulation model is developed to solve the
following problems: Can the new equipments match the
new production combination and schedule? What kind of
scheduling strategy will make best operation of new
equipment? How many buffer tanks will be need and what
is the reasonable specification of buffer tanks ? How is
reliability? what influence will the production cycle time
brings? Are more packaging lines or production lines
needed?
The model is implemented in the ExtendSim that is a
simulation platform developed and published by Imagine
That. It is a set of software that contains simulation
libraries and tools. It is used to simulate discrete event,
continuous process and discrete process based on rate.
The continuous flow stands for large-amount or highspeed flow, this software includes controls and schedule
parts used for modeling process, and layered structure
templates used to represent a higher level[2,3].
Fig.2 is the general simulation model that shows the
two production lines, four buffer tanks and three packing
lines. The actual parts of the model are included in a level
module. You can double-click any region of higher level
modules image to open lower level modules. The
timetable, equipment performance, fault characteristics,
the conversion rate and other data are included in a builtin a database table of the model and could be visited
through a logical scheduling structure.
In this case, the model manufactures and packs
products by running manufacturing machines and packing
equipments under the control of a logic scheduler. The
scheduler controls the simulation by an order table that
lists products and the amount. The utilization ratio of
equipment was set by the logical scheduler and we can
use the logical scheduler to instruct equipment for
conversion when it’s necessary. The report submitted by
the operation model is like the actual business report. The
researcher can check out these subject reports, and points
out the existing problems.
The simulator is widely used for helping the project
team of the factory, to make sure the number and
configuration of the new manufacturing lines, packaging
lines and buffer tanks. A few test schedules are developed
to represent production requirements in the typical
situation and in the extreme cases. These models are
Fig.2.the simulation model of manufacture & packaging
the effect of improvement of manufacture & packaging
based on the existing factory model and a series of
packing line designs that are recommended.
III. SIMULATINGOBJECTS, ATTRIBUTES AND
ACTIVITIES
A. CreationandTransformationof Objects
When the simulation model operates, the simulation
clock keep recording the running time increasing with
simulation steps. Productions and packaging steps are not
predefined with a table, but caused by events. In this
model, items as objects are produced by a Create module,
and the production rate of the item is decided by "interval
time of two items". The interval can be represented by
species and parameters of designated random distribution
that depicts the item production condition of the making
line. For example, the interval in this case is described
with an exponential distribution.Themean value for one
conduction line is 0.2 and another is 0.4. Both location
values are all zero. Production characteristic of the two
production lines is depicted with different valuesof the
parameter[4].
The manufacture or the packaging process could
machine.
In order to coordinate the input and manufacture or
packaging, a Queue module is needed between input and
the activity as a buffer. Queue module will store items and
wait to release them to next module based on the rules
predetermined. In the module dialog box we can select or
set queuing rules such as resource pool queuing,
according to attribute value, FIFO(first in first out),
LIFO(last in first out), priority, etc. With rule Resource
pool queuing, the resource will be caught from the
resource pool module where the resource number is
limited. A queue based on the attribute value will sort
items by an optional attribute. FIFO queue is the most
common queuing way; LIFO is a kind of reverse queuing,
also known as stack, which means the latest item into the
stack will leave first; under Priority queuing way, the
module uses the Priority attributes to determine the
releasing order of item.
Fig.3. production process model
change the measurement unit. For example, five small
items of product form a larger one after packing. It can be
simulated with a merger module named Batch, it allows
C. INVENTORY AND BUFFER TANK
multiple sources of objects merged into one thing. It will
be of great help in coordinating different machines to
assembling or fusing different parts. In the module dialog
box, we can set the number of each input objects to
produce an output objects, as well as objects from other
input are not allowed to put into this module if some input
objects are not arrive or quantity is not enough.
B. Productionand Packaging
We can simply use a process with time parameters to
simulate the manufacturing or packaging. The most
important activity module of ExtendSim is Activity. Its
basic parameter is Delay that is the processing time of the
activity module. In addition, it can also define and deal
with several items at the same time. In the module dialog
box, the processing time can be designated as a fixed
value, or input from the D(Demand) port of the module,
or fromattribute value of another module, as well as from
an inquiring form. The last 3 ways can realize more
plenty and slightly modeling for processes. In this case,
the initial processing time of two host machines was set
constants, more detailed time table can be set up in the
subsequent according to the specific situation of the
There exist differences of space distance and rate
between the Processing and packing process. In practice,
it often use the way of setting up stock in factory or
production inventory to coordinate the contradiction. The
specific physical form of this inventory may be a
universal warehouse, some cargo space or buffer tanks
exist between the processing and packing line. In this case
we assume the way of buffer tank. A buffer tank store the
same kind of products only, but receive the products from
different production lines, it can also release to any
packing line for packaging.
We still use Queue module to realize the simulation
of buffer tank. But since there are multiple buffer tanks,
the model needs to choose the reasonable buffer tank to
store the products from the end of production lines. And
because there are more than one packaging lines, the
model should also do a reasonable choice when the buffer
tanks release products so as to put the products into the
free packing line. We can use two kinds of module like
Select Item In and Select Item Out to realize the
simulation of the product routing. A Select Item In
module receives items from more input branches and
release items out through its only output port. A Select
Item out module receives items from its only input port
and release items by choosing one of export branches.
The selections in the dialog box include based on priority,
random selection, sequential selection or based on Select
port selection. In this case, between production line and
buffer tank, and firstly establish a Select Item In with two
inputs branches, output randomly to Select Item out with
four branches, completing the routing of bulk products
from the buffer tank to the packing line. Between the
buffer tanks and packing lines, establish a Select Item In
with four input branches, randomly output to a Select Item
out with three output branches to realize the route from
the buffer tank to the packaging line.
Fig.4. routing of production lines to buffers
D. ABOUT THE SCHDULE
The simulation model is driven to operate and
interact by a schedule, just like an opera showing step by
step with a script written by the editor. The model can be
used to evaluate potential of a specific schedule in realworld, or compare one schedule against another, on the
basis of how well schedules perform in the model. We can
discover which schedule is the best by testing with the
different schedules, as well as what kind of scheduling
generating rules is the best. Since for each schedule, the
model will show real-world operation results such as
production, utilization, and down time[5].
A simulation model of using schedule should be
able to introduce a sequence of operations that was
created by embedded data table or database, or use a
external table or external database to manipulate the
schedule. There is a built-in module in some simulation
model, for setting scheduling method, rapidly and flexibly
IV. TO EVALUATE AND OPTIMIZE PROCESSES
A．EVALUATION INDEXES
The simulation model is used to analysis the
manufacturing & packaging system and the problems are
to be solved. Some models involve manufacturing
operation only or involve packaging operation only, and
the other involves both. Normally, it’s based on problems
which will be solved to determine the corresponding
evaluation index such as the equipment utilization, the
processing cost and the queue length[7].
Utilization.Utilization is the ratio of the working
time and all running time of the equipment. Low
utilization means that the resources haven't been made
fully use, but high utilization rate is sometimes not a good
thing because it means ability tension. Once the
equipment runs failure, inevitably leads to the production
halt and extend the production cycle, which leads to the
failure of the production scheduling[8].
Ult =
∑n
i=1 ti
T
(1)
Ult - equipment utilization
Ti - the processing time of product number i
i - ID of products
T - running time of the equipment
Cost.Any manufacturing & packaging process must
spend some resource and its cost is a key management
tool. An activity module has cost parameters in the dialog
box that can simulate the cost of the process. We can set
the cost information in the cost page in the dialog box.
According to the character of cost, we can set two kinds
of cost, fixed cost and time cost. Fixed cost is the cost that
happens when deal with every product, its value is a
constant, unrelated with the delay of products. The time
cost is relevant with the processing time, it equals to the
multiplication of the cost per unit time and the operation
time[9]. The module will automatically calculateits
cumulative cost and display on the plot.
to generate the typical schedule or the experimental
schedule. It can be based on demand conditions, or on the
TotalCost = ∑ni=1 t i ∙ Cpertimeunit + qi ∙ Cperitem (2)
actual demand schedule. These scheduling modules can
calculate some certain evaluation measures, also can put
the execution of the schedule to the simulation model to
get a complete operation results by capturing the dynamic
Total Cost- total processing cost
Cpertimeunit- unit time processing cost
Cperitem- fixed cost of every processing a product
qi - total products exited from the module
situation of real world. That is generating any sure
schedule for the whole simulation scope, or producing
B． OPTIMIZATION
internal schedule obey to the model commands and the set
time or conditions in advance in the entire operation[6].It
can be showed in the model what is the demand degree, as
well as the state of all products in the whole time range.
The simulated optimization, also named goal seeking,
is seeking the optimal answer to the question
automatically, or the optimal value of parameters. In
parameter range given in the model, we can run the model
repeatedly to search the solution space and find out the
best parameter-values that satisfy the conditions as well as
reach the decision target. In the optimization model
including an Optimizer module, the issue is usually
presented as a target function or a cost-profit equation. In
order to realize the cost minimization or the profit
maximization, the ExtendSim simulation models help
researchers not only find the best solution automatically
but also put out of the long boring process that repeated
trying different parameter-values[10].
The running conditions can be changed in the
optimization model. For example, we can set the value
range, value method and constraint conditions of
parameters by limiting value scope of decision-making or
defining constraints equations. We can also affect the
solving precision by the setting run parameters, such as
deciding the total sample cases, the search times of each
case, when to check convergence, and optimal number of
member cases in the convergence[11]. Optimizer does not
have the function of refusing faults, so any Optimizer
maybe converges to the second best solution not the first
best solution, especially when its running time is not long
enough. So we should consider to run more times and get
enough operation results, and ensure getting the same
convergence to close to the optimal solution before using
the best solution for actual application.
V. CONCLUSION
The simulation is a good tool to study the problems
of manufacture & packaging operation. It is because of
multiple factors interact through a variety of means.A
simulation model can provide more real ways to improve
decision effect than other research models. In fact, a
simulation model is just like a virtual factory to test the
new design idea, or assessment recommended projects.
The simulation model discussed in this paper is designed
in the ExtendSim condition. It can be used to optimize the
process of manufacture, package and logistics in the
factory.
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