Abstract
The influence of Engineering Change (EC) on a product depends on the life-cycle phase in which it is initiated. For instance, any change after the product is introduced in the market is usually deemed unacceptable, as it carries a high penalty since products must be recalled. Changes beyond this point are typically incorporated in the next model/version of the product. However, during the earlier part of a product life-cycle change can occur during any stage of development. It can take the form of a change in the requirements (clarification of tasks - occurring in any phase), in the functionality of the product (occurring during or after conceptual design), in the subsystem(s)/component(s) of the product (occurring during or after conceptual/embodiment design) or as rework iteration (occurring during the detail design). The nature of engineering changes is such that they tend to propagate (Eckert et al., 2001); several authors have discussed the need to assess change propagation through components in a product in order to manage such changes. Some of the methods that investigate the impact of changes in terms of how they propagate in the product are Change Prediction Method (CPM) (Clarkson et al., 2004), Change FAvorable Representation (C-FAR) (Cohen et al., 2000) and RedesignIT (Ollinger and Stahovich, 2004). All these methods consider the components of the products or physical properties of the components of the product and do not directly help investigate the impact of change on the design process. In the 2008 DSM conference, Gärtner et al. (2008) began to address this by proposing a simulation model for evaluating the impact of a change to a component during the design process upon that process's duration. Gärtner et al.'s approach includes a product-process DMM to connect the components with the design process but does not consider the functions of the product or its requirements and thus cannot directly help explore the impact of changes initiated in the earliest stages of design. In summary, therefore, no existing approach helps investigate changes initiated during different stages of design and assess their impact on the design process. This paper advances the argument that to manage an engineering change process effectively it is important to also consider how that change can then propagate through different phases of the development process. The authors show how this can be achieved through an MDM-based approach. This paper has proposed a framework to use multi-domain MDM models to capture information which is relevant to managing engineering change across different stages of the design process. The authors also showed how such models can help assess the effort of engineering change implementation processes. The proposed approach accounts for change propagation through the function structure and the design process - which is not explicitly accounted for in many existing change prediction techniques.