The days of material, product and process development using trial-and-error experimentation are waning rapidly. Empirically based trial-and-error development cycles typically require a long time to complete, and the complexity and large number of variables of most engineering problems makes it difficult if not impossible to reach an optimal solution.
As the complexity of a problem increases, the need for a powerful simulation system to replace current economically prohibitive trial-and-error development methods also increases. Simulation systems allow engineers to optimize process parameters and improve yield and reduce costs and development time for manufacturers. Decisions that influence the final quality of the product or process can be made rapidly, and customer requirements can be analyzed more efficiently and at lower cost.
Enter modeling. Modeling can be defined as a method to produce a representation or simulation of something using a computer to solve a problem. Increasing computing power is enabling modeling of things not possible before with greater accuracy and in shorter times. Modeling has truly changed the face of manufacturing, where the interrelationship of parameters makes it impossible to handle all of the scenarios without the use of a computer.
Today, modeling is being used in all areas of manufacturing, providing fast, accurate results to complex problems. Part design, manufacturing processes (e.g., how the material reacts in the rolling process, how it fills a forging die, how it flows through an extrusion die, how it fills an injection molding die, how it solidifies as a casting, how it reacts in the sintering process, etc.), the heat-treating process, quenching process including quenchant flow in the tank, part distortion, the combustion process, emissions, welding, surface treating, etc. are just some of the many manufacturing-related modeling applications. Each area requires knowledge of specific metrics, and the complexity of optimizing maybe hundreds of variables in a single study requires highly skilled analysts well versed in all the aspects of modeling.
Two stories in this issue are good examples of the use of modeling to solve engineering problems. One deals with optimizing the operating cost of a steel-reheating furnace and the other deals with optimizing the design of a centrifugal particulate emission-control device. Both of these problems also could have been handled in the traditional manner; that is, by trial and error, but at a high cost and with a high probability of a less than optimal solution to the problem. Traditional methods either can't deal with the interrelationship of parameters or can't feasibly measure all the desired conditions.
Advanced simulation techniques provide a clear representation and thorough understanding of the process. This eliminates costly trial-and-error development cycles and enables product design and manufacturing methods to be optimized for quality and reliability, while reducing production costs and minimizing lead times.
Also, as one practitioner notes, simulation offers the benefit of serving as an educational tool. The computer can serve as a "laboratory" to test solutions and to create processing windows. In addition, new players brought into a project can rapidly be brought up to speed on what works and doesn't work and the importance of specific parameters by simulating the process.
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