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Introduction to Simulation Technique
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2006 oncampus Fachhochschule Lbeck/ Luebeck University of Applied Sciences, Stephensonstr.3, 23562 Luebeck, GermanyAll rights reserved
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Unive rs it y: UniversityDuisburg-Essen
Country: Germany
Prof. Dr.-Ing. Bernd Noche
University: University of AppliedSciences Kiel
Country: Germany
Prof. Dr.-Ing. Hans Janisch
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This learning object (LO) gives a brief introduction to simulation technique.
The objective of this LO is to familiarize you with several important issues in
simulation concerning material flow and logistics, such as:
Reasons and limitations for applying simulation technique
The basis of definitions and principles
Range of applications
The procedure and steps of simulation technique
In addition, the first example of a simulation study is discussed in order to gain
first insights to possible questions and approaches.
1 Why Simulation?
2 Definitions and Guidelines
3 Range of Applications
4 The Procedure of a Simulation Study5 Steps of a Simulation Study
6 An Example of a Simulation Study
7 Utilization of Simulation Technology
8 Benefits of the Simulation Technique
9 Control Questions
In total the module requires 4 hours of your time.
Overview
Learning Objectives
Table of Contents
Duration
Learning
Objectives
Table of
Contents
Duration
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To maintain their competitiveness, todays companies are forced to newly
design their production structures or flexibly adapt existing structures in ever
shortening cycles.
During this process, the structures are becoming increasingly complex, and themutual influence of the individual factors creates dynamics which are difficult to
manage by people without instrumental support.
The simulation on the screen allows dynamic and complex processes to be
made transparent. For instance, rationalization potentials, investments and
breakdowns can be simulated, and reactions can be tested.
Herein, it must be noted that the utilization of simulation only brings advantages
if it is carried out in a competent and efficient manner.
Simulation in Material Flow and Logistics
Simulation is used in numerous ways in the field of material flow and logistics.
Aside from assembly systems, conveyor technology and working systems,
even entire factories and distribution centers are tested, right through to Supply
Chain Management. To carry out simulation studies effectively, special
knowledge is required in the field of simulation technology and logistics. It
ensures that the fields of application for simulations are correctly delimited, and
the type of use and point of utilization are correctly selected.
The questions which are to be clarified with the aid of simulations must beasked precisely. Using the question, it is possible to collect the required data in
order to then carry out the required experiments after modeling. Simulation
projects often suffer from communication difficulties between the customer and
the simulation expert. Increased time requirements and substantial costs are
detrimental for all participants, and the simulation results are often
unsatisfactory. Simulation technology is fundamentally costly; that is, it is
necessary to consider in advance whether more favorable methods may be
able to deliver the desired results.
1 Wh Simulation?
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The VDI Guideline 3633 defines simulations as follows:
Simulation
Simulation therefore describes the model of an object and the experiments
carried out on it.
2 Definitions and Guidelines
Definition of Simulation
Simulation is a process for patterning a system with its dynamic processes in
an experimentable model to obtain knowledge which can be transferred into
reality. In a wider sense, simulation is understood as the preparation,
realization and evaluation of targeted experiments with a simulation mode.
With the aid of simulation, the timewise process flow behavior of complex
systems can be examined.
VDI 1996
A model is a simplified imitation of an existing or imagined (or past) system
with its processes in another comprehensible or representational system.
With regard to the characteristics that are being examined, it is, in terms of
the relevant characteristics, different from its role model only within
tolerances which depend on the goal of the examination. It is utilized to solve
a certain task whose realization through direct operation on the original is no
longer possible, or too costly.
VDI 1996
Definition
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Modeling
In slightly simplified terms, this means that modeling in simulation includes the
realization of an existing or imagined system into an experimentable model
which is also defined as the simplified imitation. Correspondingly, simulations
usually depict only those characteristics of a process which is relevant for the
desired knowledge. For this reason, they often remain abstract and are similar
to the process which they depict only in some aspects. Therefore, thepossibility of an observer confusing the simulation with reality is excluded in
these cases.
System
In DIN 19226, a system is marked by system limits towards its environment.
The system limits define entries and exits from the system to its environment.
(VDI 1996)
Discrete Event Simulation
A simulation method defines the manner in which the time behavior of asimulation is considered. When carrying out a simulation run, the model
elements whose condition changes throughout the observed time period are
described. Fig. 1 shows the various simulation methods.
Image Continuous and discrete simulation
methods can be utilized to extrapolate
time within a model. In continuous
simulation, the models condition
variables are shown in a steady flow
over time, for instance to clarify
chemical processes.
In discrete simulations, the condition
changes are observed at discrete
points in time. A differentiation is
made between event-oriented
simulation, that is, the progress of the simulation is determined by the
beginning of an event, e.g. the start of processing. And then there is
time-controlled simulation, where the model is observed within a fixed time
period (Arnold et al. 2002).
Fig. 1: Taxonomy of conventional simulationmethods
Taxonomy of conventionalsimulation methods
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Simulation technology in Material Flow and Logistics can be applied anywhere
in the life cycle of a production site or factory. Simulation makes sense when
simple calculation processes are no longer sufficient, or when numerous
variants have to be researched.
Here, the utilization of simulation technology covers:
Planning facilities or factories,
Realization and start-up of logistics systems, and
Operation of the production sites.
Simulation is currently used most frequently in planning, and less frequently in
realization. Actual utilization within the framework of production planning and
control, e.g. in simulation-supported control centers, is particularly new.
With regard to fields of application, it is also true that simulation technology is
utilized in a variety of trades. The following are simulated in the chemical
industry, in machinery construction, in electronics, in shipping, in freight, in
commerce, etc:
Order picking systems,
Assembly systems,
Production systems,Sorting systems,
Work systems, and
Organization systems.
A trend can be observed here away from the individual systems and towards
the comprehensive analysis of entire factories. Simulation technology is
introduced in the following through a first simple example.
Since the field of application for simulation is very broad, it is therefore the taskof the potential user to recognize those cases in which its utilization makes
sense. The tool is currently finding application in practically all planning phases
from rough planning via fine planning through to realization. Table 1
summarizes significant questions again. The recommended time for utilizing
simulation is as early as possible.
3 Ran e of A lications
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Table
Applying Simulation Technique
The use of simulation must initially be planned independently from simulation
software. From goal planning, the projects goal is formulated, and it is verifiedwhether simulation makes sense for this question. It must be noted that simpler
and more cost-effective alternatives to simulation, e.g. table calculation, will
frequently provide a solution. In spite of the fact that simulation technology is
available for use, the rule should be: Only simulate when all other means of
calculation have been exhausted or can no longer be utilized economically.
The necessity for simulation results from the degree of complexity, for instance
networked links between cause and effect, or feedback effects.
The simulation tools which are currently available in the market offer every
conceivable comfort:
Simple entry mechanisms,
Vivid representation of results,
Animation for visualizing processes,
Interfaces for data transfer.
Use of simulation
Tab. 1: Use of simulation in the various project life phases
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Introduction to Simulation Technique - Page 6
Fig. 2 shows how simulation technology proceeds. The observed real system is
initially emulated in a model with the aid of simulation software. The various
questions can then be examined experimentally on this model through a
variation of parameters and attributes. The results are then interpreted andtransferred to the real system.
Image
Real / Planned System:
The starting point can be an existing or planned facility or manufacturing area.This system should be optimized by a simulation.
Simulation Model:
The production unit to be examined must be shown in a simulation model.
Aside form a determination of interfaces, this also includes a restriction to
significant features (reduction) and suitable translation into the available
simulation software (abstraction).
Formal Results:
Every simulation run creates output which is expressed in suitable figures andstatistics. To evaluate the value of a model, various test series (experiments)
must be carried out. At the commencement of a simulation study, an
experiment plan is created, among other things. However, experience has
shown that it will change several times in the course of a study depending on
the results of the individual experiments.
Conclusion for the Real / Planned System:
The statistics which are obtained must be compared to each other, and serve
to clarify the behavior of the facility. The interpretation of this result leads to the
conclusion (transfer) back into the real system.
This described cycle can be undergone several times perhaps because
further questions need to be clarified, or because the individual results have
4 The Procedure of a Simulation Stud
Fig. 2: Procedure in simulation
Procedure in simulation
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side effects which require further measures.
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The described process for executing a simulation study shows how simulation
techniques can be used to optimize the facilities. However, several steps are
necessary for creating a simulation model and carrying out suitable
experiments:
Clarification of relevant research goals
Data procurement (reduction)
Model creation (abstraction)
Model check
Experimentation
Documentation and presentation
Definition of Relevant Questions for the Investigation
The economic realization of a simulation study within the deadline is only
possible if the significant questions and research goals were formulated in
advance. This allows the formulation of conclusions regarding which partial
sector of production must re examined more closely (interfaces) and at what
level of detail one should make the representations. In principle, the following
applies: As precisely as possible, but not more precisely than necessary."
Reduction
The next step is data procurement. Depending on the problem, this includes a
description of processes, technical data such as speed, work time etc., cycle
rules of the products through the factory, control rules, batch sizes and
transport units, order algorithms, shift models, the layout of the production site,
order data or arrival data of pallets or work pieces, etc..
Example: Data structure for simulation in mechanical manufacture and
assembly
Abstraction
Model creation begins as soon as the model structure has been clarified.
Modeling also orients itself to the options of the available simulation tools.
However, it is not possible to do without relevant modeling aspects simply
because the software is incapable of them the simulation study would then
lose its purpose. If necessary, another simulation software must be used (or
possibly just rented). The users abstraction abilities and experience determine
the value of a model. The model must be as simple as possible (transparency)
and simultaneously record all characteristics which are important to the
examination (precision).
Validation of the Model
Verifying the validity of the model is an important step. For this purpose,
comparison data, plausibility checks and simple estimate calculations should
be utilized. Further possibilities for verification result from an examination of
partial models, following through the cycles of individual products, or
eliminating coincidental influences.
5 Ste s of a Simulation Stud
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Experimentation
The test series commence as soon as there is sufficient trust in the models
validity. Depending on the results, a great variety of questions is often
examined in an attempt to clarify effects, explain trends, etc., until all relevant
facts are eventually gathered.
Documentation and PresentationFundamentally, all simulation results must be documented. A presentation of
the results increases acceptance when realizing the obtained knowledge, and
also provides the necessary trust in the relevance of the results.
Documentation of the results should be structured as follows: Definition of the
task and goal setting, data foundation, modeling and depiction, experiment
progression and significant conclusions, as well as a clear summary.
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In the following, the progress and benefits of simulation technology will be
shown, using a small study as an example.
6 An Example of a Simulation Study
6.1 Real System
6.2 Modeling
6.3 Formal Results
6 An Exam le of a Simulation Stud
Table of Contents
Table of
Contents
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The material flow system which is to be analyzed through simulation
technology is sketched out in Fig. 3. It is a contour control of the type which can
be found in various places in automated systems, such as in goods receipt
areas.
Image
The contour control is operated manually. A certain percentage of pallets is
ejected when the contour control is triggered. These pallets must then be
moved by a worker.
The following questions are to be answered within the framework of the
simulation study:
What weak areas are there in the material flow system?
How large is the throughput in the desired solution?
What influence does the utilization of a second worker have on follow-up
work (re-palletizing)?
What throughput times result for the pallets in the material flow system?
How does the facility behave in the event of malfunctions?
Are the buffers sufficiently dimensioned?
How high is the working load on critical components?
6.1 Real S stem
Fig. 3: Example of a contour control
Example of a contour control
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Model creation took place with a component-oriented simulation system. The
following components were required: Source, accumulation conveyor, merging
switch, order picking station, distribution switch and sink. The layout of the
material flow system according to the modeling is shown in animation 1.
Rollover
There are initially no direct correspondences in reality for the source and sink.
These model elements are introduced for purely practical reasons. |they
represent the interfaces between the system which is being examined and the
environment. The pallets enter the material flow system via the source, and
vanish into a subsequent area again at the sink. Furthermore, the system load
can be easily varied with the aid of these interfaces.
The data of the small model are:
Arrival rate of the pallets: 30 sec.
Conveyor speed (accumulation conveyors and work station): 0.2 m/sec.
Pallet length: 1 m
Handling time for the pallets at contour control: 10 sec.
Handling time for the pallets in follow-up work: 30 sec.
Follow-up work quota 20 %.Number of workers: 1 person
Workers travel time 30 sec.
Priority of the combining station for the source.
Buffer capacity in re-circulation 1 place respectively.
Buffer capacity at goods receipt (after the source) and goods exit (ahead
of the sink): 10 places
6.2 Modelin
In the online version an interactive multimedia element is shown here.
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After entering the components and the parameters into the simulation software,
a complete system blockage is shown after the first simulation (see animation
2).
Animation
As a reaction to the first simulation run, the re-circulation strand was now
prioritized in a second simulation run. This measure did prevent a system
blockage, but the load was not handled the buffers after the source filled up
after only approx. 30 minutes. Fig. 4 shows the fill level of the buffer and the
source. The buffer was continuously filled up to 100 % after only 2 hours. The
backup in the source is also evident. After 10 h, the source had a fill level of
approx. 60 %.
Image
Fig. 5 shows the buffer load ahead of the sink showing that it is utilized at
barely 50 %.
6.3 Formal Results
In the online version an interactive multimedia element is shown here.
Fig. 4: Buffer load
Buffer load
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Image
Fig. 6 shows the load on the work stations. Contour control has a load of
approx. 100%, and the follow-up work station has a load of 30 %. However, the
statistics also show high shares of the condition Waiting for Worker. That is,
the work stations are busy or the worker is busy at another work station at the
moment.
Image
The work station statistics of the worker in Fig. 7 show a load of approx. 85 %
with approx. 25 % travel path. The workers waiting time is created while thepallets are transported into the work stations.
Fig. 5: Buffer load ahead of the sink
Buffer load ahead of the sink
Fig. 6: Load diagram of work stations
Load diagram of work stations
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Image
The throughput statistics in Fig. 8 show the time shares of maximum and
minimum throughput times. The average throughput time (the middle bar)
rises from hour to hour this is an indicator that the small material flow system
cannot handle the prescribed system load.
Image
Of course, the results of these first two runs are not satisfactory. The material
flow system cannot handle its load. The causes might lie in the unfavorableload on the worker, who runs to the follow-up station whenever there is
follow-up work and therefore works very inefficiently for the facility would
have to be running, on a calculation basis.
Fig. 7: Work station statistics of the worker
Work station statistics of the worker
Fig. 8: Throughput time statistics
Throughput time statistics
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In the following chapter, practical examples will be used to explain the
relevance of simulation technology. Aside from the questions, the costs for
carrying out the study will also be shown.
7 Utilization of Simulation Technology
7.1 Advance Warehousing Zone with Driverless Transport System
7.2 Order Picking Advance Zone
7.3 Production System
7 Utilization of Simulation Technolo
Table of Contents
Table of
Contents
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We are looking at a production warehouse which is cleared out by a DTS
(Driverless Transport System). The small facility is shown in Fig. 9. It consists
of the warehousing areas, the stock removal nozzles, the transfer point to the
DTS, as well as the route of the vehicles.
Image
The system is described by the following data:
Block route length of the vehicle route 2.4 m,
Vehicle speed 0.8 m/sec,
Transfer time 22 sec (including positioning time).
The following questions should be answered with the aid of the simulation:
What is the maximum throughput?
How do variations in transfer times influence throughput?
How should the block route division be selected in order to further
increase throughput?
All relevant model elements are considered in the simulation model: The
source which offers sufficient vehicles -; the length of the block routes; the
intersection; the transfer times.
About 20 experiments are carried out: Various block route divisions, various
intersection controls (notification when the intersection is clear), different
variations in transfer times (rhythmic, normally distributed, exponentiallydistributed).
7.1 Advance Warehousin Zone with Driverless Trans ort S stem
Fig. 9: Sketch of the advance warehousing zone with the DTS route
Sketch of the advance warehousing zone with the DTS route
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Image
A result of the runs is shown in Fig. 10. Throughput is significantly influenced
by the variations in transfer time (up to approx. 15 % deviation).
The manual solution (normally distributed transfer times) shows a lower
throughput than an automatic conception. In an exponential transfer time (for
instance, by a person who is also utilized for other activities which are not
shown), the throughput worsens significantly once again. Due to the scatter in
the operation times, the required throughput is not reached in a manual system.
The requirement for this study is approx. 3 h.
Fig. 10: Throughput rates with different variants
Throughput rates with different variants
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The object being planned is an order picking advance zone in a plastics plant,
by the principle "Goods to Man". The layout of the order picking zone is shown
in Fig. 11.
Image
The pallets run from the warehouse via the circular conveyors to the order
picking stations. Here, the goods are removed and re-packed into a waitingpallet (not shown). The pallet which was removed from the warehouse is then
re-warehoused with an automatic warehousing site specification. The system
consists of 4 warehousing aisles and 4 order picking stations. Empty and
complete pallets are removed from stocks on a special stock removal route.
Goods from production (delivery by truck) are brought into the warehouse from
time to time via a warehousing route.
The questions to the simulation study are:
How high is the turnover performance of the system?What effects does the monitoring of stock removal in the correct order
have on throughput?
What effects does the restriction of the maximum permitted number of
pallets have on the cycle?
How high is the load on the pallet sites?
What duplicity share shows itself in the shelf operation devices?
The procurement of data for carrying out this simulation takes place through the
customer. Planning is founded on estimated turnover volumes and order
picking time per item. The technical data are obtained from catalogues from
conveyor manufacturers.
7.2 Order Pickin Advance Zone
Fig. 11: Layout of the order picking zone
Layout of the order picking zone
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Model creation takes place with a simulation system which offers components
from the material flow field, namely work stations, compression conveyors,
combiners, ejectors etc.
The simulation runs show that the system does not provide the required
performance when strict adherence to the correct order is demanded.
Furthermore, it is determined that the load on the order picking stations varies
greatly: 80 % for order picking station 1 and 70 % for order picking station 4.
Significant savings can be realized by changing the division of the conveyor
segments and increasing the conveyor speed (the number of drives is cut in
half!) without reducing throughput. With the aid of the simulation, a system
specification for warehouse management is created.
Fig. 12 shows the system throughput in dependence on the maximum
permissible cycle load. It is shown that throughput is highest when the load on
the cycle is only approx. 50 %. With higher load rates, there are blockades
which range through to system standstills; with lower loads, the system"starves.
The requirement for this study is approx. 12 man days.
Image
Fig. 12: Throughput in dependence of maximum cycle load
Throughput in dependence of maximum cycleload
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The starting point is an existing production facility, consisting of 40 machines
which manufacture approx. 2,000 pallets of paper products, such as napkins or
tissues, daily (Fig. 13).
Image
There is a differentiation between 6 machinery groups; one machinery group is
determined for each product group. In principle, there is free assignment of
machinery to products within the product group sometimes with very
significant setup time.
The questions to the simulation are:
To what degree are the machines under load in a future order mix?
By how much can production be increased subsequently?
How large will the warehouse need to become?
What delivery service can be reached?
What effect do shift models have?
What happens when production planning is carried out daily (instead of in
a weekly rhythm)?
Model creation when depicting an entire factory includes scheduling (order
receipt and production program creation), production (machinery, setup times,
control center logic) and shipping (warehousing, shipping regulation).
Standardization when depicting entire factories is not yet far advanced. For thisreason, aside from utilizing the components, a significant share of programming
also becomes necessary for depicting the control strategies.
7.3 Production S stem
Fig. 13: Schematic layout of a production system
Schematic layout of a production system
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The results of the study show that the factory has already reached its
performance limits. Without purchasing additional machinery, neither
just-in-time production nor a production increase is possible. This result
surprised all participants in planning. The assumed reserves have been
completely utilized by the masters on site through an ingenious dispatching
strategy. The disadvantage of this strategy is, however, a high amount of
finished product stocks and low flexibility in reacting to customer wishes. The
warehouse space requirements can be reduced to 50 % of the planned base.
The requirement for this study is approx. 40 man days.
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It would be nice if the benefit of the simulation technology could be expressed
in Euros immediately before carrying out a simulation study. This, however, is
only rarely possible. The benefit of simulation technology is very widely spread
(VDI Guideline 3633).
Security gains:
Confirmation of planning specifications
Minimization of entrepreneurial risk
Functionality of the planned system
Functionality of control
Quality of the requirements specifications
More cost-effective solution:
Savings or simplification of system elements
Savings or simplification of control elements
Optimization of buffer sizes and warehouse stocks
Optimization of work processes (contents)
Better understanding of the system:
Parameter sensitivities
Ability to give reasons for the selected solution, and to verify it
Avoidance or elimination of bottlenecks
Training of plant personnel
Dynamic analysis and representation of the entire process (animation)
More favorable process control:
Decision-making support in operation problems
Process optimization in accordance with desired target functions (e.g.
throughput time, load, output)
Productivity increase
Optimization of facility controls
Minimization of standstill costs in case of failures
Shortened start-up phase
Judging by an analysis of numerous simulation studies and examinations, it
can be concluded that simulation studies have lowered costs in many cases in
which they were applied.
However, the prerequisite is that a professional course of action is chosen and
8 Benefits of the Simulation Techni ue
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the questions concern targeted aspects.
It is also important to secure the corresponding data quality. Animation 3
contains a summary of questions / examination aspects which, depending on
their field of application, were tested in simulation studies.
Click-InteractionIn the online version an interactive multimedia element is shown here.
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Question 1
Which iteration steps are repeatedly run through when planning with simulation
technology?
Show answer!
Question 2
Of which stages does a simulation study consist?
Show answer!
Question 3
Which advantages are offered by the utilization of simulation technology?
Show answer!
Question 4
The assembly of an electrical device (e.g. a vacuum cleaner, hair dryer,
shaver, iron) is to be researched in a simulation study.
Which data are commonly required?
Name data classes and one typical data set for each.
Show answer!
Question 5
Plant-internal transport is to be researched in a plant. What questions can
typically be expected? Please name 10 aspects.
Show answer!
Question 6
What is a system blockage?
Show answer!
9 Control Questions
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The cost and benefit of simulation technology have changed extraordinarily
over the past five years. On the one hand, high-performance simulation tools
(simulators) have appeared on the market; on the other hand, the
acceptance of results has increased considerably as well. The visualization
of results through animation has meant that the planners and operators of
production sites can estimate the proper depiction detail, and interpret and
realize results. Animation shows a momentary situation in the facilities.
Together with this, curve progressions, graphics and figures enable an
evaluation of a systems performance capabilities throughout the entire
simulation period.
To do a simulation, a system is created in a model, and this model is shown
on the computer with the aid of the software. By varying the parameters,
experiments are carried out, and the results are subsequently evaluated.
However, it must be noted that a complex process cannot be rendered less
complex through the utilization of simulations. The results of a simulation
depend on the model, the underlying data, and the interpretation of the
results, and not on the utilized software.
The utilization of simulation technology only brings advantages if it is applied
properly and efficiently.
Summar
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Introduction to Simulation Technique - Specialwindow
1. Order quantity structure
Order file with the following entries:
Product (type)
Number of items
Dispatch date
End date
2. Work plans
File which states the run through manufacturing for all relevant products:
Product (type)
Work order
Machine
Processing time
3. Item list
Composition of products for showing assembly:
Type assignment
Number of items (end products end figure)
4. Transport units
For showing transport intensity and storage requirements:
Type - container (if various are present)
Type - product (assignment to the container)
Number of items per container (maximum value)
5. Layout of the facilities
Machine, transport and storage arrangement
Machine identification
Buffer capacities
Machine control
Set-up times
Set-up logic (when does set-up or cleanup take place?)
Interruption rules
Failure times (where relevant)
Rejection quotas (depending on the machine?)
6. Conveyance technology data
Example: Data structure for simulation in mechanical manufactureand assembly
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Speeds of conveyance technology
- Shelf operating device
- Assembly lines (constant conveyor)
Control logic
- Keeping the transport or production batch together
- Branching logic (combining logic
7. Shelf facility
Technical data:
Capacities
Dimensions
Organization
Container distribution (zoning)
Reach-through (location)
Occupied places (blocked places)Operation range of the shelf operating devices
8. Process strategy in the manufacturing control system
Control logic
Order of the orders, depending on machine group
Handling logic for batches (splitting, overlapping)
Amount adaptation
9. Planning regulations of the PPS
Superior regulations
Batch sizes
Time of order clearance
Transfer times (planning times)
Order in which orders are dispatched (regulations)
10. Control station shelf facilityTasks of the control station:
In normal production
In malfunctions
For rush orders
What other manual tasks occur?
Process logic in the shelf facility
Strategy in shelf space occupation
Strategy of removal from storage (Which container when?)Strategy of placement in storage (Which order first?)