When using connectivity models to assess the potential impacts of component changes on other parts of a product, plausible inferences are readily assessed when such products are represented at the appropriate level of granularity to support specific queries. In this paper, we describe the development of a prediction algorithm, which enables coherent computations of the likelihoods of change propagating on several levels of detail of product description given component level change probabilities. The results show that a multilevel approach to change prediction supports an increased range of design queries beyond that achievable with a single level model. Such change prediction capability is useful when carrying out a comprehensive change impact assessment.@en

In 2002 the UK Ministry of Defence introduced Network Enabled Capability (NEC) as its response to US designs for Network Centric Warfare. NEC as a paradigm poses a number of requirements on systems in the battlefield and defence companies are expected to deliver systems that meet these requirements. Requirements such as agility or interoperability can be achieved by improved change planning. At the same time, the effects of change can be unpredictable. Scoping the effects of change before a change is made can be crucial for delivering products or services in time and in budget. This paper investigates how operational requirements of NEC impact industry tasked with designing network enabled products from a change perspective.@en

Bringing successful innovative products to the market is in many cases a balance between targeted innovation and the reuse of existing technology. If this integration fails designers also need to look for innovative solutions at the last minute to integrate new and old parts. To avoid this 'emergency' innovation, designers need to understand how different parts of a product are connected to each other and how changes to one component affect other components. This paper reports on a method to predict how change propagates through existing products to assess the risk of innovation. A product is represented as a square matrix and the pair wise dependencies between components are captured with likelihood and impact values, such that indirect risk can be calculated. Using various graphic representations of the structure of the product, designers can explore dependencies between components and avoid design choices that might force them to change highly connected parts.@en

Reliable change propagation is the key for successful change management. However, only a small number of support tools exist for the analysis of change propagation information. As change propagation data has many different facets, a set of different visualisation techniques is needed to assist designers in predicting change in complex products. In this paper we introduce different views on change propagation data. We show how this can be visualised using the CPM (Change Prediction Method) tool, a software tool currently under development for predicting change propagation. On the basis of an example case study at a UK diesel engine manufacturer, we show how different graphs can benefit design change management and which graphs are suitable for displaying which aspects of change propagation data.@en

Planning of large scale design projects is difficult due to complex interdependencies between tasks and uncertainties concerning task duration, rework likelihood, rework behaviour, requirement changes and resource availability. This paper examines how different task rework behaviour affect project duration and considers the impact of varying task orders subject to resource constraints. Results of design project simulation, generated using the signposting approach, show how modifications to task rework behaviour have a major impact on project duration and that appropriate task ordering can reduce task rework.@en

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.@en

Most designs are modifications from previous products and lessons learned from earlier designs can be beneficial when developing new products. This paper introduces a support tool for the conceptual design phase, which is based on connectivity models of past designs and allows designers to assess the risk of change spreading between components and facilitates a visual analysis of these change models. Based on the example of a new generation of diesel engine design, this paper shows how the ability to predict change propagation can guide designers through conceptual design allowing them to analyse design alternatives and foresee potential problems arising from the product architecture.@en

Functional product models in design so far were built up by asking for the main function of a product first and then breaking the main function down into sub-functions, until an appropriate level of granularity was reached. A problem of this approach is that a product often provides even more functions which are not subordinate to the main function. This paper presents an approach how these functions can be captured in a reliable and structured way, using the requirements of a product as a superstructure. The improvements of this new approach are demonstrated by predicting change propagation based on an improved functional product model and comparing it to the results of a change prediction using the conventional functional product model.@en

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.@en

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.@en