Showing 4 results for Parameters
A Azizi, V. Boppana , A.c. Clement,
Volume 22, Issue 4 (12-2011)
Abstract
This paper demonstrates a preliminary investigation of geometry, function and its relation to DFX principles, namely DFM (Design for Manufacturing). This is the starting point for research on the development of an expert system that assesses design goals along DFX principles in a feature-based CAD environment. There is a need for a deeper level of understanding of the relationship between geometry and its effects on function, in order to correct and improve the product concept before large amounts of resources are invested in the product’s development.
This paper is a preliminary investigation into geometry and function involving DFM as part of an early stage of research into geometric effects on function and DFX through the use of CAD/CAE/CAM.In this paper, a concept is chosen to develop a parametric solid model that will be used to investigate a set of defined function attributes using model variants, which are evaluated in terms of the defined function attributes and DFM. The investigation found that for the functions defined, geometric parameters had less of an effect than expected. This is mainly due to the fact that the defined function attributes under investigation were associated with material properties. This paper demonstrates a preliminary investigation at the early stage of research to develop a more detailed relationship structure between geometry and functional attributes and their relationship with DFX. The end goal is to develop an integrated methodology involving geometry, function and DFX principles through the use of CAD/CAE/CAM .
Sujit Kumar Jha,
Volume 27, Issue 2 (6-2016)
Abstract
Manufacturing process frequently employs optimization of machining parameters in order to improve product quality as well as to enhance productivity. The material removal rate is a significant indicator of the productivity and cost efficiency of the process. Taguchi method has been implemented for assessing favorable (optimal) machining condition during the machining of nylon by considering three important cutting parameters like cutting speed, feed rate and depth of cut during machining on CNC. The objective of the paper is to find out, which process parameters having more impacts on material removal rate during turning operation on nylon using analysis of variance (ANOVA). An Orthogonal array has been constructed to find the optimal levels of the turning parameters and further signal-to-noise (S/N) ratio has been computed to construct the analysis of variance table. The results of ANOVA shown that feed rate has most significant factor on MRR compare to cutting speed and depth of cut for nylon. The confirmation experiments have conducted to validate the optimal cutting parameters and improvement of MRR from initial conditions is 555.56%.
Zahra Karimi Ezmareh, Gholam Hossein Yari,
Volume 30, Issue 2 (6-2019)
Abstract
In this paper, a new distribution that is highly applicable in the fields of reliability and economics is introduced. Also the parameters of this distribution is estimated using two methods of Maximum Likelihood and Bayes with two prior distributions Weibull and Uniform, and these two methods are compared using Monte-Carlo simulation. Finally, this new model is fit on the real data(with the failure time of 84 aircraft) and some of comparative criteria are calculated to confirm superiority of the proposed model compared to other models.
Rezvan Rezaei, Gholam Hossein Yari, Zahra Karimi Ezmareh,
Volume 31, Issue 3 (9-2020)
Abstract
In this paper, a new five-parameter distribution is proposed that is called MarshallOlkin Gompertz Makeham distribution(MOGM). This new model is applicable in analysis lifetime data, engineering and actuarial. In this research, some properties of the new model such as mode, moment, Reyni entropy, Tsallis entropy, quantile function and the hazard rate function which is decreasing and unimodal, are studied. The unknown parameters of the MOGM distribution are estimated using the maximum likelihood and Bayes methods. Then these methods are compared using Monte Carlo simulation and the best estimator is proposed. Finally, applications of the proposed model are illustrated to show its usefulness.
