| Product realization is a very complex, interdisciplinary process. At early design stages, decisions must be made not only about physical attributes of the design, but also about scheduling and resource allocation for many product and manufacturing engineering activities, as well as purchasing, finance, marketing, etc. Typically, complex interdependencies exist among these disparate activities, and it is difficult to predict how decisions will affect overall organizational objectives of low cost, high quality and short time-to-market.;Many decision support needs in this process seem to fall in a gap between emerging design-for-manufacture models (which evaluate design attributes for cost of a specific manufacturing activity) and management-level models (such as very abstract but comprehensive PERT-type networks). This research addresses this "gap." In the proposed model there are three distinct object representations that together define a product realization problem: product attributes, activities, and resources. In the first stage of the model, two relational matrices are used to (i) match product attributes to the required design and manufacturing activities, and (ii) then match the activities to the resources required for realization. In the second stage, an activity network is generated from the data in the relational matrices. The network is assembled from predefined "templates" of activities which have default precedence relationships (for example, sequences of prototyping and tooling activities). This activity network is then used to simulate aggregate cash flow.;There are several applications envisioned for a computer tool based on this model: as a "prospectus" for new product designs to assess aggregate cost and development time within a specific organizational context; to assist managers in "concurrent" scheduling of design, tooling, and other preproduction activities; as a vehicle for budget negotiation between engineers and financial managers during the design process; and as an aid for value analysis. After reporting results of a field study and prototype computer implementation, I conclude that the model could potentially be used for decision support, but several important conceptual and implementation limitations remain to be addressed. |
