Challenges of using simulations
When we study how ticket counters are organized in a sports stadium and waiting times at the ticket counter and at the entrance gates, the use of simulation is a useful technique. Note that if the rate of audience arrival to the stadium is very regular, such as the arrival of spectators every three minutes, and the time for buying a ticket is also very specific, then we can dispense with simulation because we can calculate waiting times using simple calculations. But in reality, viewers do not arrive that regularly, and maybe one of them needed half a minute at the box office, and the other needed three minutes. The same applies to the study of industrial processes. If the operating times are fixed and the process consists of one stage, for example, then the use of simulation is not justified. But when the operating times change and the operating process consists of different stages that depend on each other and there may be a means of transportation such as a winch or a cart that transfers materials from one stage to another, simulation may be the appropriate method.
The application of simulation in the Arab world is very weak, and therefore the use of simulation faces many challenges. Examples of these challenges include:
Belief that the simulation will be a substitute for those responsible for the operation: Since the simulation is done using the computer and shows the industrial or service process via the computer, it seems impressive to those who do not have enough knowledge about the simulation. This fascination may make some officials think that simulation will issue decisions instead of them, and thus they start anti-simulation, throwing accusations at it, and trying to hinder its use. We must be aware that simulation is a method such as using an algorithm or a program to display data in the form of curves. These methods present results to those responsible for operation or management and do not give decisions. Simulation is a method that requires effort from the simulation specialist and those responsible for operation. The operation specialist is the one who proposes solutions, and the simulation specialist provides him with the expected results of these proposed solutions. In the end, humans – not the simulation program – make the decision.
Exaggerated expectations: As I mentioned in the previous point, sometimes there is a fascination with simulation programs, which makes some people imagine that simulation programs can do anything. A manager often wants to use simulations to determine the maximum productivity of a plant so that he knows if the operators are doing their jobs as they should. This requirement cannot be achieved by using simulation because simulation is based on actual operating times that determine the maximum productivity. Simulation cannot be used to calculate the optimal time for cutting a piece of metal with a manual or electric saw, nor can it calculate the optimal time for mixing two chemicals. It should be noted that there are other types of simulation – such as simulation of fluid flow or chemical processes – that depend on solving differential equations using computers, but these methods differ from process simulation. As for process simulations, they depend mainly on measured operating times and do not interfere with the chemistry or physics of the processes.
Low expectations: Due to some people’s inability to understand the principles of statistics and the basics of simulation, we may find those who cannot understand that simulation can resemble a complex process that requires a lot of effort and experience to analyze and predict its results. It is often difficult to understand the simulation program’s ability to simulate the randomness that occurs in the production process.
The lack of clarity of the purpose of using simulation: Once you start using the simulation model, you will find that there are many points that can be studied. Unless there is an administration that has specific and clear goals from building this model, it causes a lot of dispersion, which may lead to wasting a lot of time to study marginal things.
Lack of understanding of what should and should not be simulated: The simulation specialist and the operation manager can specify the parts of the process that must be simulated in all its details. the job. Some of the subtle details that affect the process under study must be simulated, while others can be simplified or neglected. For example, things that happen in rare cases – once or twice a year … – are not paid attention to in the simulation as long as the aim of the simulation is to study the natural-normal conditions. Not ideal and not rare – for the factory. Sometimes some insist on entering marginal details that do not affect the simulation model because they do not understand what should and should not be taken into account in the simulation model.
Difficulty obtaining accurate information: The simulation depends on the data that is fed into the computer, and therefore the accuracy of the results depends on the accuracy of the operating data. In addition, when using simulation, we want to simulate the changes that occur, and we do not want to simulate the ideal case, and therefore we cannot use the arithmetic average for many operating times, and this requires the necessity of accurate measurement of these times many times. Of course, it is not hidden from you the negligence in the accuracy of the data recorded by many of those responsible for the operation, and this may lead to inaccurate results or that accurate data is collected specifically for the simulation process by a person or group that understands the required accuracy and does not lack honesty.
Believing in all the results of the simulation program: Some people who are not familiar with the computer may not notice the necessity of testing the model to ensure its correctness before using it. Also, he may not notice the necessity of conducting several experiments on each case, because because of simulating the changes that occur in reality, the solution varies from time to time, and therefore the average of the results of several experiments must be taken for the model. Therefore, it is important to ensure the validity of the model and the validity of the methods used.
Using simulations to study obvious things: Sometimes problems are obvious or can be studied by mathematical methods, but they are not solved
simulations to study it. This represents a waste of money and effort, as simulation will not add anything new in these cases.
Interest in animation more than statistical results: Since the depiction of the dynamic movement of the process is considered unusual, so the focus may be on these graphics more than the analysis of the results. Simulation users know that statistical numbers are an important consequence of using simulations, while animation is only an aid.
Fear that the simulation will expose the lies of those responsible for the production process: The production manager or service department manager often resorts to deceiving his managers that the capabilities of the production or service process cannot exceed a specific production capacity – knowing that the capabilities of this process are higher than that. Of course, this manager will not welcome the use of simulations because he fears that simulations will expose his secrets.
Difficulty persuading management to buy simulation software: Simulation programs suitable for industrial use are no less than a few thousand dollars, and therefore sometimes there is difficulty in convincing management of the benefit of purchasing simulation software.
Scarcity of simulation specialists in the Arab world: Due to the modernity of industrial engineering in the Arab world, there are few engineers specializing in simulation, and it may be necessary to appoint a new engineer or engineers.
Despite these challenges, there are many simulation applications in the Arab world that could lead to saving millions of dollars or increasing profits by millions of dollars. As a result of not using simulation in the Arab world, there are many important matters – the consequences of which are very expensive – that are estimated by calculations that depend on the use of the arithmetic average of the times of operations, and therefore they depend on an ideal case that does not represent reality.
