Optimisation of the shear forming process by means of multivariate statistical methods

Shear forming is a versatile process for manufacturing complex lightweight components which are required in increasing numbers by many different industries. Inherent advantages of the process are simple tooling, low tool costs, good external and internal surface quality, close dimensional accuracy, and good mechanical properties of the components. In times of free market economy, it is necessary to on the one hand fulfill the increasing demands toward the quality characteristics and on the other hand to reduce the development time needed to manufacture such a high quality component. Since shear forming is a complex and sensitive process in terms of deformation characteristics this is not an easy task. To assess the overall quality of a component several, mutually contradictory, quality characteristics have to be considered simultaneously. While conventionally each characteristic is considered separately, in this paper, a statistical approach is presented which copes with the above mentioned demands and provides the opportunity for an efficient, multivariate optimisation of the process. With a minimum of statistically planned experiments, mathematical models are derived which describe the influence of the machine parameters and their interactions on quantitative as well as qualitative component characteristics. A multivariate optimisation procedure based on the concept of desirabilities is used to find the best compromise between the mutually contradictory quality characteristics. With this statistical approach a workpiece for electrical industry is manufactured which requires a very good surface quality and close geometrical tolerances.