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Engineering changes (ECs) are inevitable for businesses due to increasing innovation, shorter lifecycles, technology and process improvements and cost reduction initiatives. The ECs could propagate and cause further changes due to existing system dependencies, which can be challenging. Hence, change management (CM) is a relevant discipline, which aims to reduce the impact of changes. EC assessment methods form the basis of CM that support in assessing system dependencies and the impact of changes. However, understanding of which factors influence the changeability across value chains (VCs) is limited. This research adopted a VC approach to EC assessment. Dependencies in products and processes were captured, followed by risk (i.e. likelihood x impact) assessment of ECs using change prediction method (CPM). Four industrial case studies were conducted (3x automotive, 1x furniture manufacturing) to identify design (product) and manufacturing (process) elements with high risk to be affected by ECs. Based on the case results, characteristics were identified that influence changeability across VC. This contributed to the CM domain while businesses could also use the results to assess ECs across VC, and improve the design of products and processes by increasing their changeability across VC e.g. by proactive decoupling or reactive handling of system dependencies.

Abstract. In this paper we describe an approach to efficiently evaluate the usability of an interactive application that has been realized to support various platforms and modalities. Therefore we combine our Multi-Access Service Platform (MASP), a model-based runtime environment to offer multimodal user interfaces with the MeMo workbench which is a tool supporting an automated usability analysis. Instead of deriving a system model by reverse-engineering or annotating screenshots for the automated usability analysis, we use the semantics of the runtime models of the MASP. This allows us to reduce the evaluation effort by automating parts of the testing process for various combinations of platforms and user groups that should be addressed by the application. Furthermore, by testing the application at runtime, the usability evaluation can also consider system dynamics and information that are unavailable at design time.

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