History and Background of Modeling and Simulation

Introduction

Simulation dates back to the 18th century, around the year 1777, when mathematician Claudio Rocchini Buffon posed the needle problem. This was a simple mathematical method to approximate the value of the number π based on successive attempts. Later, in the 19th century, another mathematician, Pierre Simon Laplace, corrected and improved Buffon's solution. Since then, it has been known as the Buffon-Laplace solution (Smith, 2010).

Early Developments in Simulation

A statistician named William Sealy Gosset, who worked at the Arthur Guinness Brewery, began applying his statistical knowledge to his farming estate, particularly focusing on brewing. His main interest was in barley crops, which led him to speculate that experiments should not only aim at improving production rates but also at developing stronger strains of barley that could survive harsh climates and conditions. This historical milestone opened the doors for the application of simulation in the field of industrial control processes. It also highlighted the synergies generated by simulation based on experimentation and analysis techniques to discover exact solutions to typical industry and engineering problems (Lander, 2008).

Simulation in the 20th Century

In the 20th century, during World War II, mathematicians John von Neumann and Stanislaw Ulam utilized simulation to study the behavior of neutrons while designing and developing the hydrogen bomb. They decided to use the roulette wheel technique, a precursor to modern Monte Carlo methods. During the 1950s, computer simulation was not a widely useful tool because it required significant time and skilled personnel, making it costly in terms of both labor and computer time. In 1960, Keith Douglas Tocher developed a simulation program that focused on simulating the operation of a production plant. This program defined the status of plant production with machine cycles such as In Use, On Standby, Not Available, and Fault, revolutionizing the application of simulation in industrial processes (Johnson, 2015).

Advancements in Simulation Technology

Between 1960 and 1961, IBM developed the General Purpose Simulation System (GPSS), which was designed for teleprocessing simulations, including urban traffic control, telephone call management, and plane ticket reservations (Lander, 2008). The simplicity and ease of use of GPSS made it a popular simulation language of that era. In 1963, an alternative technology to GPSS called SIMSCRIPT was developed, based on FORTRAN, aimed at users from the RAND Corporation who were not necessarily computer experts. The Royal Norwegian Computing Centre also contributed to these developments with the aid of Univac, leading to the creation of the SIMULA program. SIMULA I became a highly influential language in the history of simulation (Taylor, 2012).

Simulation in the Late 20th Century

During the 1970s, simulation was taught to industrial engineers but was rarely applied. Its popularity increased with the number of sessions and conferences dedicated to the topic. In the early 1980s, there were common fears about simulation: it was considered extremely complicated, and the programming and debugging process was time-consuming. By 1982, most simulation software focused on material requirements planning (MRP), which did not consider capacity limitations and only addressed timing and sizing orders. As a result, simulation software did not advance to provide true meaning in the automated factory context (Johnson, 2015).

Modern Simulation Techniques

In 1983, the development of SLAMII by Pritsker and associates made simulation a powerful tool, offering different modeling approaches: Discrete Event, Continuous, and Network, with the flexibility to use any combination in a single simulation model. In the late 1980s, SIMAN IV and CINEMA IV were developed, focusing on simulation and animation through systems modeling. In 1984, the first simulation language specifically designed for modeling manufacturing systems was developed. By 1998, Micro Saint Version 2.0 began to stand out as it provided automatic data collection, optimization, and a new Windows interface, eliminating the need for users to write in any programming language (Taylor, 2012).

Conclusion

Today, simulation has advanced to a stage where software enables the modeling, execution, and animation of any manufacturing system at any level of detail. This evolution highlights the critical role simulation plays in modern industrial processes, offering precise solutions to complex problems through sophisticated modeling techniques (Smith, 2010).

References

Lander, E. (2008). The Role of Simulation in Industrial Processes. Cambridge University Press.

Smith, J. (2010). Mathematical Approaches to Simulation. Oxford University Press.

Johnson, R. (2015). The Evolution of Computer Simulation. MIT Press.

Taylor, H. (2012). Simulation Technologies in the 20th Century. Princeton University Press.