A method for robust design of products or processes with categorical response

Download
2006
Erdural, Serkan
In industrial processes decreasing variation is very important while achieving the targets. For manufacturers, finding out optimal settings of product and process parameters that are capable of producing desired results under great conditions is crucial. In most cases, the quality response is measured on a continuous scale. However, in some cases, the desired quality response may be qualitative (categorical). There are many effective methods to design robust products/process through industrial experimentation when the response variable is continuous. But methods proposed so far in the literature for robust design with categorical response variables have various limitations. This study offers a simple and effective method for the analysis of categorical response data for robust product or process design. This method handles both location and dispersion effects to explore robust settings in an effective way. The method is illustrated on two cases: A foam molding process design and an iron-casting process design.

Suggestions

A Lagrangean relaxation based approach for the capacity allocation problem in flexible manufacturing systems
ÖZPEYNİRCİ, SELİN; Azizoğlu, Meral (Informa UK Limited, 2010-05-01)
This study considers the operation assignment and capacity allocation problem in flexible manufacturing systems. A set of operations is selected to be processed and assigned to the machines together with their required tools. The purchase or usage of the required tools incurs a cost. The machines have scarce time and tool magazine capacities. The objective is to maximize the total weight of the assigned operations minus the total tooling costs. We use Lagrangean relaxation approach to obtain upper and lower...
A discrete optimality system for an optimal harvesting problem
Bakan, Hacer Oz; Yilmaz, Fikriye; Weber, Gerhard Wilhelm (Springer Science and Business Media LLC, 2017-10-01)
In this paper, we obtain the discrete optimality system of an optimal harvesting problem. While maximizing a combination of the total expected utility of the consumption and of the terminal size of a population, as a dynamic constraint, we assume that the density of the population is modeled by a stochastic quasi-linear heat equation. Finite-difference and symplectic partitioned Runge-Kutta (SPRK) schemes are used for space and time discretizations, respectively. It is the first time that a SPRK scheme is e...
A simulative model for optimum open pit design
Erarslan, K; Celebi, N (2001-10-01)
Previous research in the area of open pit mine optimization has focused on profit maximization by optimizing pit limits or optimizing production schedules. However, these two approaches are interrelated and dependent on each other. Recent studies have recognized the limitation of this optimization approach, Consequently, there is a need for a more comprehensive modelling strategy. Such an optimization model should incorporate mining activities that are simulated (as they are expected to occur) as much as po...
A unifying grid approach for solving potential flows applicable to structured and unstructured grid configurations
Cete, A. Ruhsen; Yuekselen, M. Adil; Kaynak, Uenver (Elsevier BV, 2008-01-01)
In this study, an efficient numerical method is proposed for unifying the structured and unstructured grid approaches for solving the potential flows. The new method, named as the "alternating cell directions implicit - ACDI", solves for the structured and unstructured grid configurations equally well. The new method in effect applies a line implicit method similar to the Line Gauss Seidel scheme for complex unstructured grids including mixed type quadrilateral and triangle cells. To this end, designated al...
An adaptive simulated annealing method for assembly line balancing and a case study
Güden, Hüseyin; Meral, Fatma Sedef; Department of Industrial Engineering (2006)
Assembly line balancing problem is one of the most studied NP-Hard problems. NP-Hardness leads us to search for a good solution instead of the optimal solution especially for the big-size problems. Meta-heuristic algorithms are the search methods which are developed to find good solutions to the big-size and combinatorial problems. In this study, it is aimed at solving the multi-objective multi-model assembly line balancing problem of a company. A meta-heuristic algorithm is developed to solve the determini...
Citation Formats
S. Erdural, “A method for robust design of products or processes with categorical response,” M.S. - Master of Science, Middle East Technical University, 2006.