2012
DOI: 10.1177/0037549712451776
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Modeling and simulation for product design process

Abstract: Descriptive simulation finds the performance measure of a system, given a particular value for the input parameters. Inverse simulation reverses this and attempts to find the controllable input parameters required to achieve a particular performance measure. This paper proposes using a ‘stochastic approximation’ to estimate the necessary design parameters within a range of desired accuracy. The proposed solution algorithm is based on Newton’s methods using a single-run simulation to minimize a loss function th… Show more

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Cited by 3 publications
(4 citation statements)
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“…A 3D CAD model of the satellite antenna is formed by the method of reverse engineering, which is made opposing air in the conditions of use of the technical system [4][5]. The simulation model is based on the factor of the speed of the airflow and the data are valid for the area in which the device is used.…”
Section: Input Parametres For 3d Modelingmentioning
confidence: 99%
See 1 more Smart Citation
“…A 3D CAD model of the satellite antenna is formed by the method of reverse engineering, which is made opposing air in the conditions of use of the technical system [4][5]. The simulation model is based on the factor of the speed of the airflow and the data are valid for the area in which the device is used.…”
Section: Input Parametres For 3d Modelingmentioning
confidence: 99%
“…The satellite antena in this study was designed in SolidWorks 2011 software tool ( Figure 4) and passed through a simulation tool flow SolidFlow (located in the professional package SolidWorks 2011) [4]. The results obtained by the simulation were compared with the results of tests of the real models of the satellite antenna that is made at the Aeronautical Technical Institute in Belgrade.…”
Section: Set Of Satellite Dishes Air Opposingmentioning
confidence: 99%
“…Analyzing the dynamic characteristics of the product development process is crucial for accurate prediction and control. Simulation methods are effective for solving complex dynamic problems, such as Petri nets [18] and Monte Carlo simulations [19]. These methods evaluate the performance (cost, lead time, risk, etc.)…”
Section: Introductionmentioning
confidence: 99%
“…The sample size for this particular survey was determined based on the central limit theorem (Arsham, 2005) which considers an amount of, n > 30, to be a sufficiently large sample to represent a large population. Here; "n" represents the sample amount obtained at a particular moment in time.…”
Section: Sample Size Determinationmentioning
confidence: 99%