This thesis seeks to extend the PDG methodology by developing a generalized formal method for nesting PDGs in an interconnected system. A procedure for decomposing an individual PDG into reusable modules will be defined and a software architecture will be presented which takes advantage of these reusable modules. This method breaks the PDG structure into discrete elements known as PDG objects, PDG modules and PDG services. Each of these elements forms a distinct unit of reuse and each can be seen as a "little" PDG. Two different industrial implementations of this method are presented. These examples show that it is possible to share PDG services amongst multiple PDGs and provide a mechanism to create a PDG for a complicated system.

Decisions Support Systems (DSSs) are used to enhance decision maker speed and effectiveness. However, without a view of an entire system, any decision may have unanticipated effects such as sub-optimal outcomes. The purpose of this research is to show that with a system-level analysis, more informed decisions can be made that take into account a larger system or greater number of dimensions or objectives. This research also explores the benefits of using a DSS over analysis of unprocessed data and the effectiveness of integrating a product design generator (PDG) with a business DSS, creating a system DSS, where system-level effects can be analyzed. These are connected using software which allows them to be interactive, and dynamically updating. After this DSS was developed a variation was also made and decision makers evaluated these tools to identify how they performed in comparison to each other. In one variation, aspects of the tool were split up, guiding the decision maker through the analysis while the other did not. Using survey questions and recording decision makers' actions, it was found that decision makers are significantly faster and came to better conclusions when using the DSS over unprocessed data. However, it was also seen that the difference between the two variants of the System DSS tests was insignificant. This suggests that the limits in potential interactions in the one variant of a system DSS did not substantially reduce the ability of a decision maker to explore and make good design decisions. Overall this research showed that having a system-level tool is better than the unprocessed data, and that more extreme differences in a DSS are required for improved comparisons to establish which visualizations and elements are most effective in a System DSS. Future effort should be made to completely isolate different portions of the System DSS and see how well users are able to make decisions with it compared to the full system analysis.

Custom software development and maintenance is one of the key expenses associated with developing automated systems for mass customization. This paper presents a method for reducing the risk associated with this expense by developing a flexible environment for determining and executing dynamic workflow paths. Strategies for developing an autonomous agent-based framework and for identifying and creating web services for specific process tasks are presented. The proposed methods are outlined in two different case studies to illustrate the approach for both a generic process with complex workflow paths and a more specific sequential engineering process.