1. A Comparison of Discrete Event Simulation and
Excel Spreadsheets Methods for Optimizing
Factory Layout and Operations
urvival of any manufacturing industry in today’s competitive market depends upon the ability of the
industry to satisfy customer demand, with the use of a minimum number of resources in the least possible
time. Hence to obtain competitive edge, companies must extract every drop of value from their resources, to
derive maximum value. They must also have a deep analytical understanding of all aspects of manufacturing
operations and be able to visualize different scenarios possible; from impact of variations in product demand,
capacity consumption to machine breakdowns to draw optimum conclusions. To this end, it is essential to
have the right software tool to accomplish this task. The most commonly used tool used today in analyzing
manufacturing operations and manufacturing layouts are traditional Excel spreadsheets. This is because Excel
is a low cost solution that is available in almost all computer desktops and laptops in a typical factory, and
therefore has become the default tool when a requirement occurs to analyze manufacturing operations or a
new factory design layout for efficiency. Excel however, is very limited in its ability to accurately assess and
capture the many elements at play in a manufacturing system.
This is because; manufacturing processes are inherently discrete event processes. This means that the
operation of a system takes
place as a discrete sequence of
events, with each event causing
a change in the state of the
system. For instance, a machine
undergoes several changes in
state during the manufacturing
process, going from processing
to idle, to a possible breakdown
or maintenance state, to setup
and to a possible state of repair.
All these changes happen
during different periods of time.
Excel, as a primarily
mathematical spreadsheet tool,
lacks the fundamental
requirement of being able to track time or changes in state over a time interval.
S
Figure 1: Excel Sheet representation of a Factory Process
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2. Because, Excel cannot track changes in state behavior of various entities like machines process and set up
times, varying customer demand , shift timings, operators and material handling equipment travel distances
and speeds, maintenance schedules etc, it is limited in its ability to provide a proper analysis of a factory,
where every aspect of the manufacturing operation changes with time. As a result, the Excel user makes gross
assumptions to simplify calculations, resulting in large errors in estimation of results.
Excel also carries with it the
disadvantage of not being able to
visualize the dynamic nature of the
manufacturing system or its
behavior in real time. Real
manufacturing systems are highly
complex in nature, with multiple
requirements, such as routing logic,
processing priorities, task
sequences, shift timings, and more.
Capturing these hundreds of
nuanced complexities adds yet
another dimension of difficulty to
an Excel user, for it is not designed specifically for such a purpose. Thus no amount of formula manipulation in
an Excel spreadsheet can assess a factory performance in terms of factory throughput, need for additional
resources, such as operators or machine, areas where the production line is having a bottleneck etc.
With all these clear disadvantages in using Excel, what then can we turn to? The answer lies in discrete event
simulation or DES software. This type of software is specifically designed to simulate manufacturing processes
with great ease and accuracy. The great advantage of DES software over traditional spreadsheets is their
ability to capture change in state over a period of time. Furthermore, DES software technology in recent times
has made great strides in user-friendliness enabling a user to use it with a minimum amount of training.
Since, DES software is designed for simulation of manufacturing layouts and processes, all the aforementioned
shortcomings of Excel are overcome. A DES software user can easily add machines, CAD image files of the
factory layout, material handling equipment like cranes, forklifts, conveyors, elevator and workers etc, that
animate in real time with mathematical precision based on their respective speeds and acceleration in all 3
dimensions to ensure the analysis of the factory performance produces highly accurate results. Furthermore,
the DES user can also specify the path of travel and traffic rules that need to be followed by these materials
handling equipment to ensure safety during factory operations. These features put DES software heads and
shoulders above any spreadsheet. And since manufacturing processes are determined largely in part by many
Figure 2: A Factory Floor Plan can be imported in FlexSim
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3. unknown, random factors known only through statistical distribution, discrete event software takes this into
consideration and enables the ability to represent even these random events and situations.
The premier discrete event simulation software on the market today is FlexSim. FlexSim boasts all the
advantages of traditional discrete simulation software, and more. Using FlexSim, one can model almost any
manufacturing process with tremendous accuracy and ease. It has the ability to capture the movement of
operators and material handling machinery in 3 dimensions i.e. in x, y and z directions, taking into
consideration distance, speed, acceleration and deceleration. FlexSim utilizes simple drag and drop
technology, enabling users to use pre made objects in the FlexSim library, such as queues, processors,
operators, conveyors, cranes, and more. This enables users to build complex manufacturing models with little
or no programming. However, if factory operations are of a complex nature, a user can program in FlexSim
using C++ or the proprietary Flexscript language to deal with any difficult or unique situation that needs
addressing. FlexSim also contains libraries of all statistical distributions, to ensure an even higher level of
accuracy. The results obtained can be of 99% or more accuracy.
Figure 3: A Working Model of a Factory Floor in FlexSim
FlexSim even boasts the ability to add custom objects, a tremendously useful capability, as all manufacturing
plants either use unique machines, or obtain and employ new ones. This allows the user to configure machines
to a very exact specification, each with custom properties, and thus an entirely new custom library can be
created.
A simulation model is always tested under different conditions or scenarios to see what impact each variation
has on factory operations. A typical situation can be the impact on the factory performance by modifying the
size of a given WIP area or adding a new machine. In FlexSim, there is a built-in module known as the
'Experimenter', allowing users to test any desired scenarios easily, without making changes to the simulation
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4. model. In addition, a user can create a custom GUI, wherein a user can input data directly into the model to
determine the performance of the system for different values of input.
Figure 4: A Working Factory Layout Using Discrete Event Simulation Software
Reporting the results of a simulation model is of utmost importance, because this enables the user to decide
the future course of action needed to improve factory performance and to make optimum decisions. For
reports, FlexSim has a wide range of capabilities, such as create Excel based reports, real time dashboard
graphs, or integration with an external reporting application.
In today’s market environment, where competition is harsh, it is very important to optimize manufacturing
operations via a virtual 3d analysis of the factory layout before building the factory or executing the factory
orders on the floor. Thus FlexSim simulation software saves significant amounts of money to the organization
and provides a big return on investment.
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Head office: 3B Alps Estate, First Block, 460 / 1 Kaikodanahalli, Sarjapur Road, Bangalore 560 035, India
Tel: +91 98864 78720 email: mano@ccsstrategy.com
www.flexSim.com