R. Keller
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10 records found
1
This paper introduces an approach which uses a modified House of Quality (HoQ) and the Change Prediction Method (CPM) to consider change propagation during the concept selection phase. The key idea is to capture the influence of unintended feature changes on product attributes which arises due to component change propagation, and present this information as an aggregate performance rating for each product attribute. The results from the case example indicate that the performance rating of product attributes can be different once change propagation is taken into account. The findings in this paper also provide an indication that ignoring change propagation in concept selection can result in project delays due to unexpected changes.
Network enabled capability as a challenge for design
A change management view
Predicting change propagation on different levels of granularity
An algorithmic view
Effective change management is a key to successful design development. As products and parts of products change, others can be affected, leading to further - often unexpected and costly - changes. These knock-on effects can jeopardise the timely delivery of projects and carry therefore a great risk for the entire design process. Predicting change propagation is difficult as designers do not have the overview and hidden dependencies between components are overlooked. This paper introduces simple graph theoretical heuristics as a means to predict knock-on changes. The heuristics are validated on the basis of the existing change prediction method and real world product models.
Unforeseen change propagation can have a major impact on products and design processes and cause project delays and excessive costs. However, current change management depends heavily on individual designers' typically limited product overview. For complex products, this approach is error-prone because the amount of data that is necessary to properly assess the risk of changes is too large. The information has to be broken down into smaller chunks so that it is easier to cope with. On the other hand, an overview over the entire product must be provided in order to be able to predict changes resulting from changes in other components. In this paper we discuss the CPM (Change Prediction Method) tool that incorporates a multiple view strategy to visualise complex change data and allows designers to run what-if scenarios in order to assess the implications of changing components in a complex product during the design process.