| The primary goal of this research was to develop methodologies to understand the interactions of design parameters and producer's life cycle costs, thereby aiding product designers in proactively mitigating life cycle costs of products before the design leaves the design stage. In achieving the primary goal, feature based design models in spreadsheet form were developed and tested. With the models, a designer can input features of a product yet to be manufactured and generate estimates of future life cycle costs. The models are proactive because they are based on common features that will exist in future products the company will produce; therefore a design that has never been produced can be objectively evaluated before it enters production.;The methodology is presented as a straightforward "road map" that can guide a researcher through developing the models. The methods used are relatively simple and understandable by most designers and accountants. Among the methods is Pearson's Bivariate Correlation Analysis, Forward Stepwise Multiple Linear Regression Analysis and Two Stages Linear Least Squares. Within the methodology, the possibility of simultaneous interactions between investments is addressed through simultaneous equations.;With current versions of the models, designers at the research sites have an empirical tool other than their own intuition and experience to estimate life cycle costs based on feature additions and deletions from designs. Other benefits include improvements in costs, quality and design time. Costs are reduced by better understanding of the impacts of features on life cycle costs. Quality is improved through better understanding of the tradeoffs between investments and failures. Design time is reduced through better understanding of a design's context, thereby reducing the time it takes a designer to explore the search space. |
