Planning and Optimization of a Numerical Control Machine in a Multiple Response Case

Abstract

This paper focuses on a specific case of experimental planning and optimization in a multiresponse case. Particularly, our attention is dedicated to a numerical control machine and our final goal is to improve this machine's measurement accuracy for a general dental implant. This work substantially aims at addressing two issues: the optimization methods in the presence of more response variables and the related problem of weighting according to the actual importance of these variables. About simultaneous optimization, we suggest an improvement by a new function which takes care of location and dispersion effects.

Assessment and Optimization for Novel Gas Materials Through the Evaluation of Mixed Response Surface Models

“…The optimization step is carried out by applying the method explained and applied in [35]. In literature many authors, among the others [36] and [37], suggest different measures of optimization to set an optimal solution, according to the different kinds of experimental situation involved.…”

Review of Multiresponse Process Optimisation Methods

“…RSM has been used in diverse applications for solving multiresponse optimisation problems, such as optimisation of numerical control machine (Berni and Gonnelli 2006), optimisation of various machining processes (Aggarwal and Singh 2005), modelling and analysis of laser drilling processes (Kuar et al 2006;Ghoreishi et al 2006), optimisation of laser shock peening process to improve performances of micro-electro-mechanical system (MEMS) (Zhu et al 2012), optimisation of laser welding of stainless steels (Khan et al 2012), predictive modelling and optimisation of Nd:YAG laser micro-turning of ceramics (Kibria et al 2013), optimisation of wire electric discharge machining (WEDM) in processing high strength low-alloy steel (HSLA) (Sharma et al 2013), optimisation of WEDM in processing a pure titanium , modelling of plasma spray coating process (Datta et al 2013), optimisation of selective laser sintering process used to produce PA12/MWCNT nanocomposite (Paggi et al 2013), and others (Tsui et al 2004;Kovach et al 2008;Timothy et al 2004;Robinson et al 2004).…”

Process Optimization of a Superfinishing Machine through Experimental Design and Mixed Response Surface Models

“…In the literature, many authors (Lin and Tu 1995;Tang and Xu 2002) suggest different measures of optimization in order to set an optimal solution, according to the different kinds of experimental situation involved. The method proposed by Berni and Gonnelli (2006) takes the estimated model and the target value into account. In general, according to the dual response approach, two surfaces are estimated, one for mean and one for the dispersion effect; in addition, weights could be introduced in the objective function.…”

“…The optimization step is carried out by applying the method explained and applied in Berni and Gonnelli (2006) and Berni (2010). In the literature, many authors (Lin and Tu 1995;Tang and Xu 2002) suggest different measures of optimization in order to set an optimal solution, according to the different kinds of experimental situation involved.…”