Customized products are becoming increasingly common, and increasingly important for maintaining a competitive advantage in certain industries. Being able to quickly and accurately respond to unique customer requirements can provide a competitive edge or even be the only path to survival. In practice, configurators are commonly used to manage the customization process, gathering the customer’s requirements and suggesting feasible solutions to the customer’s problem.

Fostering and maintaining a viable product customization offering is not easy. A particularly challenging category of products is one where an extensive engineering effort might be needed to even produce a reliable estimate of the product’s price. These products are usually referred to as engineer-to-order (ETO) products.

Prior work has pointed out the potential of using optimization as part of configuration solutions for ETO products, but the literature is limited in its extent and does not clearly prescribe how to structure and approach such solutions.

This thesis outlines a conceptual and technical architecture for implementing optimization-based configuration solutions. Reusable primitives for supporting the routines involved in this architecture are provided. These findings are verified through application and evaluation within two industrial case studies, also yielding important industrial needs to cover in the future research and development of the proposed framework. By examining three additional case studies, common issues in the development and deployment of design automation (DA) systems are identified.

Successful implementation of the proposed framework for optimization-based configurators can lead to two main benefits. First, engineering configurator prototypes can be developed rapidly, to test the viability of configurator projects – a category of projects prone to expensive failures. Second, optimization-based configurators can be used to support rapid design space exploration in early product development stages, leading to enhanced product knowledge in a critical phase, and in turn, increased product value.