With an increasing demand for product individualisation leading to increased product architecture complexity and -costs, modular kits are one common measure to cope with this issue. The management of such a modular kit as well as the methodical determination of a specific product variant is key to the manufacturer's success. As multiple influence factors need to be taken into account when configuring product variants, we propose a multi-dimensional geometric optimisation algorithm, allowing for prioritising varying customer demands and thereby determining the ideally balanced product variant.

With a constantly increasing market competition leading to high degrees of product individualization and customization, developing product architectures, which still offer competitive advantages is crucial to success. For the concept of modularization supplying one solution to this issue, there are many modularization approaches available. As these all lead to different modular product architecture alternatives when being applied, the decision of which alternative to finally implement becomes increasingly difficult with more and more complex product architectures. With this contribution, we propose a simulation-based approach using model-based systems engineering as a consistent root data system for product configuration systems in order to address both customer-and company perspectives for analysing the architecture alternatives' performances. Considering the multidimensional environment, a hyperspace algorithm for expressing individual architectures as geometric representations is used. Applying the simulation method to a medical stent as exemplary product, the implementation, results and capabilities of such a simulation is displayed.

As todays’ global market trends lead to an increasing demand for individualised products, manufacturers need to cope with a high degree of internal and external variety, which has a severe impact on complexity and therefore -costs. When implementing modular product architectures, it becomes obvious, that the actual Engineer-to-Order (ETO) processes cannot cope with the requirements of such a product architecture. It is crucial to develop a complying Configure-to-Order (CTO) process in order to make full use of its suppled benefits. As there is no existing approach about how to methodically change an existing ETO process into an adequate CTO process, we intend to fill this gap with this paper by showing an approach for the development of a CTO process for modular product architectures. Furthermore, we show the application and evaluation of this approach in a case study with a special equipment manufacturer (SME), that is already implementing modular architectures.

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Today more products are developed in the form of modular productfamilies with similar, but slightly different product variants. To improve the development process but also the use and lifespanning service of product families and individual products the usage of MBSE has been an uprising trend. Using system models implicate another benefit: The stored information can be accessed by applications and be used to improve the userinteraction. One example are product configurators allowing the user to create a product variant according to individual requirements. This link to the product family's information can also be used in later lifecycle phases, as it enables an ongoing information flow about existing products into a digital representation, preparing the development and use of digital twins.