Robust Design is an approach to reduce the effects of variation. There are numerous tools, methods and models associated with robust design, however, there is both a lack of a process model formalising the steps of a robust design process and a framework tying the models together. In this paper we propose a framework for robust design and variation management by combining central models to Robust Design, namely, the Quality Loss Function, the Transfer Function and the Domains of Axiomatic Design. The Variation Management Framework (VMF) shows how variation can be mapped from production right through to quality loss in the market place and identifies areas where action should be taken against variation. An additional benefit of the framework is that it makes the link between visual/sensory/perceptual robustness, product robustness, and production variation (Six Sigma). Seven levers which can be activated to increase product quality are described and positioned on the VMF. Proposals for combining with complexity analysis and a set of linked quality and robustness metrics are proposed.

For complex and integrated products, companies experience difficulties in achieving a satisfactory and consistent functional performance. When a design has “contradicting” parameter/property requirements it often requires fine tuning with numerous design iterations and complex optimizations to find the “sweet spot” where all functional requirements are fulfilled. This often leads to a lack of robustness, where tight tolerances are required and small defects have knock-on effects throughout the product. In this article we propose the Contradiction Index (CI) to gauge how contradicting the requirements of the different parts are with respect to the different functions. This article provides a step-by-step guide for how to estimate the CI for a design. The method is applied to a case study — the FlexTouch®, a Novo Nordisk insulin injection device. When analyzing the CI for each part, against the number of part design iterations, a positive correlation was found. Furthermore, when correlating the CI against the number of challenging tolerances statistical significance was found (p=0.01). It is envisaged that the CI will be a powerful approach to estimate and compare development difficulty and to guide development and design improvements.

The robustness of a design has a major influence on how much the product's performance will vary and is of great concern to design, quality and production engineers. While ', 'robust design', 'robust function' and 'robust product'.

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Ever increasing functionality and complexity of products and systems challenge development companies in achieving high and consistent quality. A model-based approach is used to investigate the relationship between system complexity and system robustness. The measure for complexity is based on the degree of functional coupling and the level of contradiction in the couplings. While Suh's Independence Axiom states that functional independence (uncoupled designs) produces more robust designs, this study proves this not to be the case for max-/min-is best requirements, and only to be true in the general sense for nominal-is-best requirements. In specific cases, the independence axiom has exceptions as illustrated with a machining example, showing how a coupled solution is more robust than its uncoupled counterpart. This study also shows with statistical significance, that for max-and min-is-best requirements, the robustness is most affected by the level of contradiction between coupled functional requirements (p = 1.4e-36). In practice, the results imply that if the main influencing factors for each function in a system are known in the concept phase, an evaluation of the contradiction level can be used to evaluate concept robustness.