Quality prediction and compensation in multi-station machining processes using sensor-based fixtures

José V. Abellan-Nebot, Jian Liu, F. Romero Subirón

Research output: Contribution to journalArticle

43 Scopus citations

Abstract

New fixture technologies, such as sensor-based fixtures, will significantly improve part quality through cutting-tool path compensations in multi-station machining processes (MMPs). Successful application of sensor-based fixtures depends on the development of new variation reduction methodologies to predict part quality in MMPs and detect the critical machining stations whose critical manufacturing variations can be estimated by installing a suitable sensor-based fixture. In this paper, a methodology is proposed to facilitate the implementation of sensor-based fixtures in MMPs. This methodology involves three key steps: (1) an identification of station-induced variations; (2) a sensor placement optimization method for designing sensor-based fixtures; and (3) a compensability analysis. A case study is conducted to demonstrate the effectiveness of the methodology.

Original languageEnglish (US)
Pages (from-to)208-219
Number of pages12
JournalRobotics and Computer-Integrated Manufacturing
Volume28
Issue number2
DOIs
StatePublished - Apr 1 2012

Keywords

  • Compensability
  • Sensor-based fixtures
  • State space model
  • Variation propagation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Mathematics(all)
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

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