In capacity planning for a service operation, analytical models based on queueing theory allow the user to quickly estimate the capacity required and to easily experiment with different system designs or configurations, for a given set of input parameters. An input parameter of the model could be inaccurate or may not be known beyond a good guess. In order to determine if the analysis results (...

in this paper, multi-stage optimum design of composite pressure vessels is presented. the design variables for composite vessels include the head shape, the winding angle, the layer thickness, the number of layers, and the stacking sequence. a parameter called modified shape factor is introduced as an objective function. this parameter takes into account the effects of the internal pressure and...

Design of experiments is an established approach to parameter optimization of industrial processes. In many computer applications however it is usual to optimize the parameters via genetic algorithms. The main idea of this work is to apply design of experiment’s techniques to the optimization of computer processes. The major problem here is finding a compromise between model validity and costs,...

Recently 304 stainless steel finds many applications like Automotive, Aerospace, Nuclear, Chemical and Cryogenics. The cylindrical grinding parameters on 304 stainless steel are conducted using Taguchi design of experiments of L9 orthogonal array was selected with 3 levels with 3 factors and output parameter of Surface Roughness is measured. The quality of the surface describes the relationship...

The AGDISP Aerial Spray Simulation Model is used to predict the deposition of spray material released from an aircraft. The prediction is based on a well-defined set of input parameter values (e.g., release height, and droplet size) as well as constant data (e.g., aircraft and nozzle type). But, for a given deposition, what are the optimal parameter values? This problem is considered to be a pa...