Predictive modeling of machining line variation

Data processing: generic control systems or specific application – Specific application – apparatus or process – Product assembly or manufacturing

Reexamination Certificate

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

C700S174000, C700S193000, C700S121000, C703S022000

Reexamination Certificate

active

11106041

ABSTRACT:
A multistage machining process includes a plurality of stations. Workpiece feature quality is predicted based on decomposition of the machining process into sources of variation, reticulation of the machining process into machining stations and error models that account for significant contributions to feature quality including from categorical sources of variation.

REFERENCES:
patent: 4520595 (1985-06-01), Diener
patent: 5084660 (1992-01-01), Sasaki et al.
patent: 5199158 (1993-04-01), Wioskowski et al.
patent: 5691909 (1997-11-01), Frey et al.
patent: 6306011 (2001-10-01), Perry et al.
patent: 6349237 (2002-02-01), Koren et al.
patent: 6883158 (2005-04-01), Sandstrom et al.
“Multi-Operational Machining Processes Modeling for Sequential Root Cause Identification and Measurement Reduction” -Wang et al, ASME vol. 127, Aug. 2005.
Chandra et al., Finite Element Based Fixture Analysis Model for Surface Error Predictions Due to Clamping and Machining Forces, MED-vol. 6-2, Manufacturing Science and Technology, vol. 2, ASME 1997, pp. 245-252.
Chase et al.,Least Cost Tolerance Allocation for Mechanical Assemblies with Automated Process Selection, Failure Prevention and Reliability,ASME, DE-vol. 16, 1989, pp. 165-171.
Choudhuri et al., Tolerance Analysis of Machining Fixture Locators, Journal of Manufacturing Science and Engineering, ASME, vol. 121, May 1999, pp. 273-281.
Djurdjanovic et al., Linear Space Modeling of Dimensional Machining Errors, Trans. of NAMRI/SME, vol. XXIX, 2001, pp. 541-547.
Fainguelernt et al., Computer Aided Tolerancing and Dimensioning in Process Planning, CIRP Annals, 1986, vol. 35/1, pp. 381-386.
Frey et al., Swept Envelopesof Curring Tools in Integrated Machine and Workplace Error Budgeting, CIRP Annals, 1997, vol. 46/1, pp. 475-480.
Kawlra et al., Development and Application of a Methodology for Minimizing Costs Based on Optimal Tolerance Allocation, Ph.D. Thesis, University of Michigan, 1994.
Lee et al., Tolerances: Their Analysis and Synthesis, Journal of Engineering for Industry, ASME, vol. 112, May 1990, pp. 113-121.
Maier-Speredelozzi et al., Selecting Manufacturing System Configurations Based on Performance Using AHP, Trans. of NAMRI/SME, vol. XXX, 2002, pp. 637-644.
Speckhart, Calculation of Tolerances Based on Minimium Cost Approach, Journal of Engineering for Industry, ASME, vol. 94, May, 1972, pp. 447-453.
Spotts, Allocation of Tolerances to Minimize Cost of Assembly, Journal of Engineering for Industry, ASME, vol. 92, Aug. 1973, pp. 762-764.
Weill et al., The Influence of Fixture Positional Errors on the Geometric Accuracy of Mechanical Parts, Proc. of CIRP Conf. On PE & MS, Sep. 1991.
Zhang et al., Graph-Based Setup Planning and Tolerance Decomposition for Computer-Aided Fixture Design, INT. J. Prod. Res., 2001, vol. 39, No. 14, pp. 3109-3126.
Gu et al., A Model for the Prediction of Surface Flatness in Face Milling, Journal of Manufacturing Science and Engineering, v. 119, pp. 476-484, 1997.

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Predictive modeling of machining line variation does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Predictive modeling of machining line variation, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Predictive modeling of machining line variation will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-3774594

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.