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SCONES (Stress CONcentration Expert System) software is used to predict stress concentrations. When dimensions and loads are modified it instantaneously updates the display, making the system easy to use. SCONES contains validated and extended data from various sources, including complex interacting features which augments SCONES role. However, the natural progression is to extend the research to the interaction of processes including, for example, surface processes like anodising. These process interactions will dovetail into, and enhance features within the strain life factors. This paper will describe new work which will extend current knowledge in feature interactions and strain life factors and will improve SCONES versatility.

The paper introduces a knowledge-based statistical approach to tolerance allocation, where a systematic analysis for estimating process capability levels at the design stage is used in conjunction with statistical methods for the optimization of tolerances in assembly stacks. The analysis employs detailed knowledge on the tolerance capability of a wide range of manufacturing processes, including the effects of material and design geometry, enabling realistic tolerance distributions to be modeled for key characteristics on designs. The optimization of tolerance stacks is based around achieving the lowest assembly standard deviation for the largest possible and most appropriate component tolerances. The method takes into account failure severity through linkage with Failure Mode & Effects Analysis (FMEA) for the setting of realistic capability targets. The application of the method is fully illustrated using a case study from the automotive industry.