Optimizing Product Design Through Linking Design Variables for Cost-Effective Manufacturing

In product design and development, achieving the desired performance requires meeting specific product requirements within defined boundaries. These requirements are encapsulated in the Product Definition Dataset, which consists of two key models: the Nominal Model and the Specification Model. The Nominal Model outlines the product’s properties, features, and relationships, while the Specification Model defines the targets, boundary conditions, requirements, allowable variation, and interrelationships essential for meeting these targets. This study focuses on the relationships between variable quantities and the limits set by geometrical product specifications. Currently, the limits defined within geometric specifications are considered static, excluding maximum and minimum material conditions. This implies that each variable is treated independently, meaning the actual state of one variable does not influence the functional limits of others. However, in actual parts and assemblies, variable quantities do affect each other, as they are not independent. In this paper, we explore the link between specifications and the variables they define through a case study, with the aim of fulfilling product requirements more effectively. By establishing these connections, it becomes possible to produce functional parts with greater allowable variation and reduced costs, while ensuring that specifications are grounded in actual performance requirements and physics. This approach aims to enhance the flexibility of product manufacturing and streamline the process of meeting both functional and cost-related objectives.