Operations Management - Assignment Example

Finally, they can be used to develop systems to automate the processes they model (Gieskes, 2001). In the last case, programmers may use the process model as a guide in developing the information system or more recently, some process models can be run though process execution engines that automate the process directly from the model. A great deal of customization is often required in simulation systems modeling. From initial appearance, no system bears exact semblance to another and each time a new model is to be developed, the designer is compelled to begin from scratch.

Simulation presents designers with powerful modeling tools which help in coming up with efficient systems. Interesting, even with these tools at the modelers’ disposal, they still get the feeling that they are reinventing again and again. There is always the suspicion that maybe the model they are about to design already exists or may be there already exists a model that sufficiently resembles the model to be designed. Either way, simulation provides a useful tool through which systems can be simulated.

A number of techniques are often used in implementation of simulations. This project explores a specific type of simulation, a discrete event-based simulation, whereby events take place according to a schedule set on the fly as simulation plays out, with the main aim being to focus on points in time whereby interesting events take place and skip the dead spots in between the processes. For sparse simulations, where only a few events occur at irregular intervals, event-based simulation is extremely efficient.

In the simulation described in this report, the dry cleaning establishment’s inner workings are modeled. Although taking note of the fact that an actual dry cleaning establishment is a physical store which not only occupies physical space, but is also complete with machinery, workers, customers, and other variables, there are further complexities than a typical model can incorporate. This simulation therefore operated a simple model but still captured the entire essential ongoing in dry cleaning process.

To keep the simulation simple and reasonable, it is assumed that all garments to be dry cleaned are identical in size, weight, and material despite the fact that realistic differences are available in the process. It is assumed that over the course of time, the difference will even out. An average time is assumed for the clothing. Spreadsheet model versus ARENA modeling Discrete event modeling/simulation is largely use in generation of system predictions of states during time intervals, which are flexible in examination of what if situations.

For instance, it is regularly used in evaluation of client waiting lines often referred to as a queue. The question typical of such models and simulations is how long customer will have to wait (averagely) in a line before a customer representative attends to him/her and if this wait time is too long, explore possible ways of reducing it. Solutions may include adding servers. Modeling and simulation help explore these questions without the need to actually create and assess a physical situation as such a move could prove extremely expensive.

Among the approaches often adopted in modeling are spreadsheet modeling and ARENA modeling. A model spreadsheet is defined as a ubiquitous software packages element available on many networked as well as personal microcomputer systems. It is primarily applied in