Experimental assessment of a clamp actuation intensity analysis model

Wei Xie, Shabbir Choudhuri, Subramanian Vallapuzha, Edward Demeter, Martin Wesley Trethewey

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Abstract

The application of a clamp actuation intensity analysis (CAIA) model is a rough cut technique used to compute the minimum clamp pre-loads necessary to keep a workpiece from slipping within a fixture throughout a machining cycle. A CAIA model is based on the simplistic assumption that a fixture-workpiece behaves as a system of contacting rigid bodies subject to Coulomb friction at the joints. To date, little research has been carried out to ascertain how well these models predict minimum pre-loads for actual applications, or how their limitations can be overcome in order to improve their performance. This paper describes an experimental study that was used to the assess: (1) the impact of including all contact regions, regardless of rigidity, within a CAIA model, (2) the sensitivity of the CAIA model to known variations in coefficient of friction, and (3) the accuracy of predicted pre-loads for actual milling operations. The major conclusions drawn from this study are: (1) only the stiffest contact regions of a fixture-work-piece system should be included in a CAIA model, (2) there is nearly a one-to-one correspondence between the variation of the clamp pre-loads computed by the CAIA model and the variation of the inputted friction coefficients, (3) the clamp pre-loads computed by the CAIA model for a series of milling experiments were within 25% of the actual values for the majority of experiments, and (4) a reduction in the coefficient of static friction at fixture workpiece joints appears to occur during the application of milling forces, this is especially true for planar tip fixture elements.

Original languageEnglish (US)
Pages (from-to)4611-4633
Number of pages23
JournalInternational Journal of Production Research
Volume38
Issue number18
DOIs
Publication statusPublished - Dec 15 2000

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All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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