Abstract
Nowadays, advanced manufacturing models, such as the stream-of-variation (SoV) model, have been successfully applied to derive the complex relationships between fixturing, manufacturing, and datum errors throughout a multistage machining process. However, the current development of the SoV model is still based on 3-2-1 fixturing schemes, and although some improvements have been done, e.g., N-2-1 fixtures, the effect of general workholding systems, such as bench vices or three-jaw chucks, has not yet been included into the model. This article presents the extension of the SoV model to include fixture and datum errors considering both bench vices and three-jaw chucks as fixturing devices in multistage machining processes. The model includes different workholding configurations, and it is shown how to include the workholding accuracy to estimate part quality. The extended SoV model is validated in a three-stage machining process by both machining experimentation and CAD simulations. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Part quality estimation in multistage machining systems is a challenging issue. The stream-of-variation (SoV) model is a straightforward model that can be used for this purpose. However, the current model is limited to fixture based on punctual locators, and common shop-floor devices are not considered yet. To overcome this limitation, this article extends the current SoV model to include vices and three-jaw chucks as workholding devices. The proposed methodology lets practitioners estimate the manufacturing capability of a process considering the technical specifications of these devices (e.g., parallelism and perpendicularity of vice surfaces and total indicator runout of chucks), or it can be used for diagnosing workholding issues. The model assumes that the workpiece acts as a rigid part and errors as deformations during clamping are assumed to be negligible in comparison with fixture- and datum-induced errors.
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