Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 3 of 3
Full-Text Articles in Entire DC Network
Integrating Multiobjective Optimization With The Six Sigma Methodology For Online Process Control, Emad Abualsauod
Integrating Multiobjective Optimization With The Six Sigma Methodology For Online Process Control, Emad Abualsauod
Electronic Theses and Dissertations
Over the past two decades, the Define-Measure-Analyze-Improve-Control (DMAIC) framework of the Six Sigma methodology and a host of statistical tools have been brought to bear on process improvement efforts in today’s businesses. However, a major challenge of implementing the Six Sigma methodology is maintaining the process improvements and providing real-time performance feedback and control after solutions are implemented, especially in the presence of multiple process performance objectives. The consideration of a multiplicity of objectives in business and process improvement is commonplace and, quite frankly, necessary. However, balancing the collection of objectives is challenging as the objectives are inextricably linked, and, …
Multiobjective Design Optimization Of Gas Turbine Blade With Emphasis On Internal Cooling, Narasimha Nagaiah
Multiobjective Design Optimization Of Gas Turbine Blade With Emphasis On Internal Cooling, Narasimha Nagaiah
Electronic Theses and Dissertations
In the design of mechanical components, numerical simulations and experimental methods are commonly used for design creation (or modification) and design optimization. However, a major challenge of using simulation and experimental methods is that they are timeconsuming and often cost-prohibitive for the designer. In addition, the simultaneous interactions between aerodynamic, thermodynamic and mechanical integrity objectives for a particular component or set of components are difficult to accurately characterize, even with the existing simulation tools and experimental methods. The current research and practice of using numerical simulations and experimental methods do little to address the simultaneous “satisficing” of multiple and often …
Multiobjective Simulation Optimization Using Enhanced Evolutionary Algorithm Approaches, Hamidreza Eskandari
Multiobjective Simulation Optimization Using Enhanced Evolutionary Algorithm Approaches, Hamidreza Eskandari
Electronic Theses and Dissertations
In today's competitive business environment, a firm's ability to make the correct, critical decisions can be translated into a great competitive advantage. Most of these critical real-world decisions involve the optimization not only of multiple objectives simultaneously, but also conflicting objectives, where improving one objective may degrade the performance of one or more of the other objectives. Traditional approaches for solving multiobjective optimization problems typically try to scalarize the multiple objectives into a single objective. This transforms the original multiple optimization problem formulation into a single objective optimization problem with a single solution. However, the drawbacks to these traditional approaches …