Abstract: Abstract The existence of a model of spatial dependence allows one to tackle the problem of estimating attribute values at unsampled locations. This chapter presents least-squares linear regression (kriging) algorithms that account for data related solely to the continuous attribute being estimated. Algorithms for incorporating secondary information are introduced in Chapter 6. Sections 5.1-5.4 introduce the linear regression paradigm and three of its most important variants: simple kriging, ordinary kriging, and kriging with a trend model. Estimation of average values over larger areas (block kriging) is addressed in section 5.5.

Abstract: The research reported in this paper illustrates the integration of product and disassembly process design via virtual prototyping. In this context, a virtual prototype is an information model consisting of a product model and one or more process models. Integrated product/process design is accomplished by defining a parametric design problem in terms of constraints/goals and coupling virtual prototypes and a multiobjective optimization code for solution. Application of optimization techniques to solution has proven difficult Problematic characteristics are highlighted, and an effective optimization algorithm is described. An automotive center console is used as an example. The focus of this paper is the formulation and solution of integrated product/process design problems, rather than the results of the center console design problem, per se.

Abstract: The objective of this thesis is to esta.blish a theoretical and empirical framework for the design of an agent which can maintain very large unstructured case bases, ensuring that they remain current and useful. With the dramatic proliferation of case based reasoning systems in many commercial applications, many case bases are now becoming legacy data sources. While they represent a significant portion of an organization's assets, they are large and difficult to maintain. There are many sources for the complexity of the maintenance task: case bases are created over a long period of time and are updated by different people; high industry turnaround suggests that the authors of a case base may not still be with the organization; cases may be obtained from different, even geographically diverse sources; and finally, industry markets change, implying that the case bases are highly time and market dependent. These factors contribute to the difficulties in ensuring a case base is current and useful. My solution to the maintenance problem is to develop a self cleaning agent which works with users in maintaining a legacy case base in a seamless fashion. This self cleaning module features a set of user entered guidelines for detecting redundant and outdated cases. The guidelines are written in a language that is easily manipulatable by any non-expert user. As the ability to contain the knowledge acquisition problem is of paramount importance, using this system allows one to express domain expertise naturally and effortlessly. Empirical evaluations of the system prove the effectiveness of the agent in several large industrial domains.