Maximizing the number of shared components does not always produce cost-optimal product families. Shared components can yield economies of scale due to reuse of components, but also increases material cost due to over dimensioning. In this paper, we present an approach to identify a cost-optimal design for product families. It consists of two steps: (1) identifying a scheme to share components in the product family and (2) finding the cost optimal design for the product family.
Complexity in product design increases with little understanding of cause and effect. As a consequence, the impact of design decisions (or changes) on the product is difficult to predict and control. This article presents a model of cause and effect for design decisions that avoid circular dependencies: the so-called attribute dependency graph (ADG) models complex system behaviour and properties, and increases transparency by carefully distinguishing between what is realised and what is required. An ADG is a polyhierarchy, with design variables (directly controllable) at the bottom, quantities of interest (not directly controllable) on the top, and intermediate attributes. The dependencies represent causality in a simple sense: assigning values to design variables, representing the cause, will determine the values of the dependent attributes, representing the effect. ADGs do not account for what is required, but for what effects emerge by design activity. A set of rules makes them independent of designers’ views. They provide the structure for so-called INUS conditions, that is, insufficient but necessary parts of unnecessary but sufficient conditions that can be used for requirement development. The modelling approach is applied to one simple synthetic and then to two real-world design problems, the design of a water hose box and a passenger vehicle.
Companies offer products in different variants to reach more customers. This increases internal variety and cost. However, reducing those cost is difficult due to complexity. Complexity arises from: combinatorics; many design variables interacting with each other; coupling of technical and economical perspectives. This paper presents an approach based on (1) building a complex system model of modular models; (2) identifying the potential for standardization from a technical perspective; (3) cost-optimizing the degree of standardization. A product family of electric vehicles was optimized.
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