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In Smith and Eppinger's pioneering research on coupled design processes, the dynamics of design iterations is modeled by a linear model, which implies that there is no overlap between redesign work and allows redesign workload to be more than the original design workload. Actually, this overlap often exists in practice and, therefore, reduces the total redesign workload. In this paper, we propose a nonlinear model for a coupled design process with overlap between redesign work and ensure that redesign workload is less than the original design workload. Based on the model, the sufficiency condition for the convergence of such a design process is proposed. A heuristic rule is also given to reduce the possibility of considering a design process that converges as one that does not converge. Furthermore, we develop a sufficiency condition for estimating the number of design iterations before converging as such an estimate is important for planning product development projects. Another heuristic rule is also introduced to increase the accuracy of estimating design iterations. Finally, numerical experiments are conducted to examine the correctness and performance of the proposed sufficiency conditions and heuristic rules.

Many important technical and policy decisions are made by small groups, especially by deliberative committees of technical experts. Such committees are charged with fairly combining information from multiple perspectives to reach a decision that one person could not make alone. Committees are social entities and are therefore affected by any number of mechanisms recorded in the social sciences. Our challenge is to determine which of these mechanisms are likely to be encountered in the deliberative process and to evaluate how they might impact upon decision outcomes. In particular, we examine the role of committee deliberations on the U.S. Food and Drug Administration's (FDA's) advisory panels.

This paper addresses the methodology used to determine the amount of human resources needed to develop products. It is based on an empirical study of five firms in different industries. The methods rely on technical experts operating within budget constraints. The specific methods vary from relatively ad-hoc approaches to database-driven, centralized, and validated approaches. This variation is largely correlated with project and overall product development organization scale in a logical fashion in that larger projects and organizations move away from individual decision-makers toward centralized, objective, and validated methods. The project characteristics used by the experts and implicitly utilized in the database models to assess project complexity are also detailed in this paper. These characteristics are categorized based on a project complexity framework. We found that the scale of a project and the amount of "stretch" are the two most widely used characteristics for estimating project complexity. We found no utilization of the level of either component or task interactions in estimating project complexity by the firms studied. We also found no empirical evidence for interactions being a determinant of project difficulty despite a fair amount of theoretical concern with their importance in project complexity. In addition, we analyzed the accuracy of methods and conclude that since the accuracy at a higher level masks resource allocation problems at a lower level, the accuracy should be followed at multiple levels.