Robust Design Methodology (RDM), a subset of Quality Management (QM), is an approach applied to the design phase of product development in order to manage variability in product performance by creating insensitivity to noise factors. Noise factors are sources of variation that cannot be readily controlled. RDM is an approach that can be characterized by principles, practices and tools. The main principles of RDM include an awareness of variation and creating insensitivity to noise factors. Further, it is necessary to continuously apply the main principles of RDM throughout product development. Previous research on RDM has mainly focused on the design stage of product development, i.e. the front-end, and on the application of front-end design tools. There is a lack of RDM practices focusing on the back-end of product development. RDM, if applied continuously to product development, can contribute to reduced scrap and waste. At the same time, industries face the challenge of addressing sustainability considerations in product development. One way to face this challenge is to integrate sustainability considerations into existing methodologies and tools, such as QM, as an approach towards sustainable product development (SPD). The purpose of this thesis is to contribute to an extended application of RDM by using back-end data for front-end improvement and by exploring how RDM might contribute to SPD. The empirical setting of the case study was a medium-size Swedish manufacturer. Customer claims data at the organization constituted the back-end data of product development. The principal data collection method involved semi-structured interviews supported by a review of internal documents and the claims database. Other methods included participant observations and the compilation of unstructured verbal information through an affinity exercise. Exploratory Data Analysis (EDA) was used for the quantitative analysis of claims data. Further, to understand and clarify the contribution of RDM efforts towards SPD, a conceptual study was carried out by reviewing and comparing the underlying theoretical ideas of RDM and SPD. Possible front-end improvements were suggested by the use of back-end data in two major ways: first, a systematic analysis of claims data tied to a problem-solving tool such as Failure Mode and Effects Analysis (FMEA); second, analysis of claims data based on a product life cycle approach to identify possible noise factors in all stages of a life cycle. Both practices contributed to the continuous applicability of RDM throughout product development and product life cycle stages. Further, the identification of noise factors in product life cycle stages was one way in which RDM efforts might contribute to SPD. The conceptual study resulted in possible links between RDM and sustainability. The extended application of RDM by the use of back-end data for front-end improvement and sustainability support requires a shift in current views; an increased focus on back-end data, an increased focus on practices, and the adoption of a life cycle approach. The extension of RDM applications to the back-end, such as customer claims analysis, facilitates front-end improvements in product development. Moreover, adopting a life cycle approach to identify noise factors opens up a wider range of opportunities to involve RDM efforts in product development activities.