Abstract
The assessment of the performance of inspection strategies is a crucial element in the design phase of product quality inspections of manufacturing companies. The aspects that inspection designers need to consider include: (1) the typology of quality inspection, (2) the inspection variables involved, (3) the potential interaction between variables and (4) the presence of inspection errors. In particular, low-volume inspection design is critical due to the lack of historical data and the inadequacy of traditional statistical approaches. By considering these issues, this paper proposes a novel approach to support inspection designers in the prediction of offline quality inspection performance. The development of a probabilistic model based on the analysis of the possible variable interactions and inspection errors and the definition of some performance measures may successfully help designers in the early design stages of inspection process planning. The approach is supported by a practical application in the Additive Manufacturing field.
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