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Simulation models can only be fully successful if they are allowed to evolve along with the system being simulated. A fixed simulation model, which assumes that the design being simulated does not transform over time, is only doomed to fail. Therefore, a constantly shifting simulation model is desirable because industrial systems and engineering projects do not remain constant during the different stages of the life cycle of the project. The four basic stages of the life cycle of an average industrial systems project are concept design, engineering detail, installation and commissioning, and ongoing operations. The simulation of the industrial system should be modified regularly to incorporate the changes that occur for every stage of the system's life., If simulation models are to remain valid, they must develop concurrently with the project Simulation modeling is used with increasing frequency to analyze the anticipated behavior and performance of industrial [...]

Input data processors are useful in determining mathematical relationships involved in fitted distributions for simulation modeling. These software have their flaws, which arise when there is a dearth of data or if fitted distributions are used inappropriately, but input data processors definitely have a place in simulation modeling. To avoid the problems associated with the use of input data processors, simulation analysts should be meticulous in the generation or collection of data. Instead of simply running samples through an input data processor and blindly embrace its recommendations, analysts should actively involve themselves in the collection, analysis and modeling of data to ensure a successful project., Several years ago, one of the authors and a colleague were pondering the dearth of use of named statistical distributions in simulation modeling. They estimated that in 85 percent of [...]

The creation of a valid simulation model of real systems requires a certain degree of programming to be effective, contrary to what simulation software advertisers claim. As a definition, programming is the process of designing, coding and testing the procedures needed to emulate the actual behavior of the system, including actual system activities and logic. Simulation software that does not call for programming is quite application-defined, which means that it depends too much on prefixed constructs, which are usually generic, for typical activities and functions attached to that specific application. In contrast, models that require some programming allow an order list construct to be used., Simulation software advertisements often claim simulation models can be built quickly with 'no programming required.' It is our view, however, that building a valid simulation model of real systems does [...]

There are 12 steps that industrial engineers should follow if they want to become good simulation modellers. The first step in simulation modelling is defining the problem that needs to be solved, which is the most important but usually the most overlooked aspect of simulation modelling. This first step should be followed by understanding the system, determining the goals and objectives, learning the basics and verifying if simulation is indeed the appropriate tool. Then, engineers should get a commitment from management that they will support the modelling, examine software tools for simulation, identify the needed and available data, develop assumptions about the problem and ascertain what outputs are needed to solve the problem. Finally, they should determine if simulation should be conducted internally or externally and kick-off the project., Simulation modeling is similar to other engineering disciplines. It requires training and experience to become competent, and isn't really as easy as some people might have you believe. It's an [...]

There are 10 instances when simulation modeling is not the best option in solving industrial engineering problems. Simulation should be avoided when the problem can be handled through common-sense analysis, when the problem can be dealt with analytically or when direct experiments are easier changed or conducted on the real system. Simulation is also unnecessary when the cost of the simulation outweighs potential savings, appropriate resources are not available for the project, time resources are inadequate, or needed data are unavailable. Simulation should also be discouraged when the model cannot be verified or validated, project expectations cannot be achieved, or the behavior of the system is excessively complicated or undefinable.

Those who are tasked with selecting simulation software for their companies should assess the input, processing, output, environment, vendor and cost of available products. Input considerations are point and click capability, CAD translation, file importing and exporting, syntax, interface to another language, interactive run controller, and input data analysis capability. Processing variables to consider are powerful constructs, speed, runtime flexibility, random variate generator, reset, programming and portability. Factors related to output are standardized and customized reports, business graphics, database maintenance and custom performance measures. Considerations related to the environment are ease of use and learning, documentation quality, animation capability, and run only version. When assessing the vendor, one should look at its stability, history, track record and support. Cost considerations should also be reviewed., The vast amount of software available for discrete-event simulation can be overwhelming for the newcomer to the field. The selection process is especially complicated when you consider the 1996 IIE [...]

A growing number of manufacturing managers are starting to turn to simulation to solve production and material handling problems. Use of this technology is on the rise as it becomes more user-friendly, more powerful and more suitable for regular application in today's manufacturing environment. Many companies are discovering that the value of simulation software goes beyond its ability to offer a peek into the future. It has numerous other benefits, including its ability to help managers make better decisions, explore possibilities, understand why certain phenomena occur, identify constraints and diagnose problems. Simulation can also be used to visualize plans, build consensus, develop understanding, train teams and prepare for change., Similar to the manufacturing industry, competition within the computer industry has led to technological breakthroughs that are allowing hardware companies to continually produce better products. Practically every week another company [...]

I was at a car assembly plant in Mexico a few months ago. My host, Felipe, told me he had mentioned to his plant manager that he was taking my [...]

Programming skills are essential to anyone who wants to build a successful, flexible, and robust simulation model. But I am concerned about the capability of graduating students to write programs [...]

See beyond these 12 myths for a smooth simulation project The process of conducting real simulation studies differs from the idealized process often presented in marketing literature, textbooks, and many [...]

I was invited to make a presentation at IIE's Simulation Solutions Conference in May. Among the list of possible topics was 'Pitfalls in the Simulation Process.' Intriguing. The literal meaning [...]

For 30 years I taught simulation and other courses at Georgia Tech. Since July 1999 I have been working in the simulation software industry. There are distinct differences (and a [...]

I was talking with an acquaintance who sells simulation software and consulting services. I asked him who his major competitors area. The answer was a surprise: 'The major competition is [...]

About four years ago, I wrote an article about output analysis in which I begged readers to do more of it. Things have gotten better as simulation vendors have added [...]

The Winter Simulation Conference that was held in Phoenix this past December was fantastic: There were 12 tracks of nine sessions each; a 1,754-page proceedings; and about 30 vendors exhibiting [...]

Simulation consulting is a very lucrative field for budding industrial engineers. Practice in this field allows young industrial engineers to solve major problems, gain experience in a broad range of industries, and deal with problems until they are solved. They are also able to hone their skills in data collection and analysis, system analysis, technical writing, and proposal writing. Moreover, they also get to travel only once in a while, use the latest software and hardware, and gain knowledge of an industry. Finally, simulation consulting provides new industrial engineers with advancement and networking opportunities. Skills required in simulation consulting include detailed analysis, systems understanding, and technical writing proficiency. Persons who are analytical, logical-thinking, well-organized and possess good memory are ideal for this type of work. Skepticism and persuasive speaking abilities are also desirable., When John Carson and I were operating our simulation practice, seeing the words 'consulting opportunity' made me jump at the possibilities. These days, consulting opportunities are running hot and heavy [...]